Hemp Growing

Chlopyralid is especially effective for control of legumes and composites such as Canada thistle , and yellow starthistle. Because it does not control many common broad leaf weeds such as mustards, it must be tank-mixed for complete control of the wide range of broad leaf weeds found in small grains. On wheat, clopyralid should be applied from the 3-leaf stage to early boot stage, complimenting the timing of 2,4-D and MCPA. Carfentrazone is a contact herbicide that controls weeds by disrupting cell membranes. It is effective at very low application rates on coast fiddleneck, little mallow, burning nettle, and other weeds that are difficult to control with other herbicides. Adding surfactants to carfentrazone often causes temporary crop burn. Tank mixing with UN-32 may enhance weed control. Tank-mixing carfentrazone with dicamba provides good control of common chickweed. Combining carfentrazone with phenoxy herbicides broadens the weed spectrum controlled, lowers herbicide application rates, and can reduce the risk of weeds building up herbicide resistance.Preemergent herbicides are not commonly used in small grains in California, but they can be effective in certain situations. Trifluralin is a preemergent herbicide used for wild oat and canarygrass control in wheat and barley. It is applied before or after sowing and must be incorporated no deeper than 2 inches . A double incorporation is more effective than a single incorporation. Small grains must be planted below the 2-inch herbicide zone . Results can be erratic if the zone of treatment does not have adequate moisture. Crop safety is marginal.Diclofop controls wild oat, canarygrass, and Italian ryegrass in wheat and barley.

Diclofop controls wild oat and ryegrass in the 1 to 4 leaf stage and canary grass in the 1 to 2 leaf stage. Avoid applications under saturated soil conditions or cold weather. Fenoxaprop ethyl controls canarygrass, wild oat, rolling benches for growing and several foxtails, including yellow foxtail and green foxtail . It also suppresses mustards. It has a wide window of application, providing effective control when applied between the 1 to 6 leaf stage of grasses. For best control of wild oat, delay application until most wild oat plants have emerged. A tank mixture with bromoxynil allows for a wide range of weed control at an early timing. Fenoxaprop cannot be tank-mixed with phenoxy herbicides since reduced grass control often results when such tank mixtures are used. Mesosulfuron controls most grassy weeds and many broad leaf weeds in wheat. It is especially effective on Italian ryegrass, wild oat, little seed and hood canary grass, and annual bluegrass. It controls ripgut brome and other brome species, depending on weed size at application. Most California wheat cultivars have good tolerance to the herbicide. However, wheat plants will turn a lighter green color for a couple of weeks following application. If soil nitrogen levels are low, this symptom will persist longer, and supplemental nitrogen should be applied. When treated beyond the 1 tiller stage, temporary growth suppression and shortening of the wheat plant will occur. The crop will recover more quickly from these symptoms under good growing conditions. Mesosulfuron is effective on certain broad leaf weeds, including common chickweed, wild radish, and mustards. It also provides partial control of many other broadleaf weeds, including common groundsel , little malva, coast fiddleneck, yellow starthistle, and blessed milkthistle. Mesosulfuron can be tank-mixed with bromoxynil and MCPA and may be applied from the 1 leaf to 1 tiller wheat stage and up to the 2 tiller stage of grasses.

A methylated seed oil or a nonionic surfactant is required; adding ammonium sulfate or low rates of UN-32 enhances weed control on difficult-to-control weeds. Restrictions on crop rotations are greater than with fenoxaprop.Weeds that have germinated can be chemically removed using paraquat and glyphosate before cereal planting or emergence. These non-selective herbicides have no soil-residual effects on germinating small grain plants as long as they are applied before plants emerge through the soil. If the herbicide comes into contact with wheat or barley plants, severe injury will occur. Glyphosate can also suppress perennial weeds such as johnsongrass, nutsedge , bermudagrass , and dandelion when they are growing before grains are planted or emerge.The presence of green weeds late in the season can cause harvest and post harvest problems. Green weeds can slow the progress of combines, raise the moisture content of the harvested crop, and discolor or even cause off-flavors of the harvested grain. Weeds that often cause problems at harvest include field bindweed, Russian thistle, five hook bassia , kochia, common lambs quarters, knot weed, swamp smart weed, and johnson grass. Problems with green weeds at harvest can be avoided by using a preharvest herbicide application or by swathing the crop before combining. In both cases the green weeds should be allowed to dry before the crop is combined. Soil temperature results gathered after steam application in the field were similar to other mobile steamer applicator studies . The premise of this research was to evaluate the pest control efficiency of steam applied in a band prior to planting. We found that weeds, pathogens, and hand weeding times were reduced in steam-treated plots, and yields improved in some cases. In trial 3, for 176 min, steam temperatures were above 70oC were obtained with the Steamy applicator, which used a rototiller as it was incorporating steam on flat ground.

Agitating the soil as the steam was incorporated allowed for better steam penetration targeting soil aggregates compared with trials 4 and 5 done by the Yuma Steamer. The Yuma steamer kept a steam temperature above 70oC for 98-105 minutes. The temperature duration time above 70oC for the Yuma steamer was not as long as the temperature duration in the Steamy applicator trial. The Yuma steamer has a bed shaper attached to it to ensure the bed tops stay firm after application and is faster than the Steamy.The results from the weed analysis indicate that steam disinfestation does an excellent job controlling weeds, especially on hairy nightshade, goosefoot, sheperd’s-purse, burning nettle, and common purslane. Another objective in this study was to evaluate steam + hydrogen peroxide applied as a band to determine whether this product improves the pest control efficacy of steam by raising the temperature. Hydrogen peroxide did not have a significant effect on weed and pathogen control, hand weeding time, and yields compared with the steam treatments. Because the trials used soils naturally infested with Pythium spp. and S. minor, we had varying levels of disease in the field trials. Steam + hydrogen peroxide did not significantly reduce the amount of Pythium spp. colonies or S. minor sclerotia compared with steam alone. In trial 2, upon steam application, temperatures stayed above 70 oC for a shorter amount of time compared to the other trials . The steam treatment had a significant effect on reducing S. minor sclerotia by 94% when compared with the control using the Steamy in trial 3, similar to findings in other studies . The steam treatment reduced Pythium spp. colonies by 99% when compared with the control using the Yuma steamer in trial 4, similar to another study that was done . Out of all the trials, trial 4 had the most diseased lettuce plants and the best reduction of Pythium spp. colonies. The lettuce plant size for the steam-treated lettuce was significantly larger with an increase in yield when comparing with the control in trial 4 and 2, cannabis dry racks suggesting pathogen suppression. Gross revenues for the lettuce trials in this research showed the potential steam has to increase lettuce yields. A steam study done in strawberry production by Michuda et al., suggested a maximum soil temperature of 62-63oC should be a standard for growers at a duration of 41-44 mins to maximize net returns and increase fruit yield. In our lettuce steam study we surpassed that reaching temperatures above 70oC which increased yield and gross revenue peracre. Better disease control likely resulted in greater lettuce growth with a gross organic revenue of $5,624 an acre for the steam treated lettuce vs. 4,042 an acre for the non-treated control lettuce. The difference was $1,582 an acre. For the gross conventional revenue, it was 5,066 an acre for the steam treated lettuce vs. $3,640 an acre for the non-treated control lettuce. The difference was $1,426. The cost of field application per acre is $971, which suggests steam treatment maybe economically feasible to use commercially in-field given the great gross revenues per acre, but we believe that there is room for improvement in this cost. Machine operator and worker wage will increase the operating costs of this field applicator as the cost of minimum wage increases in the future, so more research needs to be done to drive the costs of the applicator down.

Research and development should focus on the implementation of a rototiller to agitate the soil to target soil aggregates for better steam penetration. Improvements might include making the machine lighter so that there is less compaction. Ideally, machine development and construction should be done in the United States to reduce the overall price of the applicator. It is important to increase the speed of application, but it needs to be done in a way that the machine still heats the soil and makes adequate dwell time. Currently, it takes 9.07 hours to steam an acre, so if the time of application can be reduced, then the amount of fuel costs can be reduced as well. It will be of great benefit to work with a known industry leader like, TriCal Inc. because they specialize in developing new effective technologies and build products to control soil pests in California. Steam applicator development can be maximized with the help of contractors who have the capabilities of building a steam applicator who can lease out to farmers. Steam is also an option for organic farmers to make an applicator in house that can be of great benefit given the need for non-chemical ways of controlling soil pests.Nevertheless, my results indicate that with a greater reduction of pathogen inoculum and weed seeds in the soil using steam, this will allow more opportunity for the crop to thrive with less pest competition. Even though the hydrogen peroxide treatment was evaluated only in two of five trials, there was no significant advantage when compared to the steam treatment alone. Hydrogen peroxide still has potential to create an exothermic effect in the soil steaming process. As a recommendation for future studies if hydrogen peroxide is more thoroughly incorporated into the soil and the trial is pre-inoculated with soil pathogens, there may be a yield benefit. This work further shows the true potential of band steaming for weed and pathogen control in the field .Surface mulches are widely used in the production of strawberries and certain high value vegetable crops. Polyethylene mulch is used on virtually all tomato and strawberry production in Florida and is also widely used in the production of other crops such as peppers, eggplant, and melons throughout much of the southern United States. Researchers at the University of Florida estimate that more than 100,000 acres of vegetable crops in that state currently use plastic mulches annually, making Florida the national leader in this production system . In California, the majority of strawberry and staked tomato production uses polyethylene mulch. Peppers, eggplant, and melons also use mulches in certain situations, especially when earliness is desired. Field management and research related to plastic mulches in these production regions is now quite developed. Potential benefits as well as drawbacks of polyethylene mulches for vegetable crop production are given in table 1. The use of intercrop cover crop residues as surface mulches is a more recent and far less widely used production practice. It has recently gained considerable interest in a number of commercial vegetable crop production regions in the United States. Potential advantages and disadvantages of this vegetable crop production technique are summarized in table 2. Reflective plastic and some cover crop mulches share similar features relative to crop production: insect and disease management, weed management, fertilizer availability, and water conservation. In order for production practices using either polyethylene or cover crop mulches to be successfully adopted in California, specific production goals must be carefully matched with specialized management know how and experience.Plastic mulches have been commonly used for commercial vegetable crop production for more than 30years.

Few California soils in sunflower growing areas have shown yield limiting K deficiencies; sandy soils are the most likely to show K fertilizer responses.Sulfur deficiency, though rarely observed in sunflowers, is characterized by slow growth and overall uniform light green color of the plant. It is generally only observed once every 5 to 7 years, and may occur only after high rainfall, prolonged wet soil conditions, and cooler soil temperatures from January to March, especially in wheat. In the Sacramento Valley, some soils may show temporary deficiency of S, and most irrigation water contains little or no sulfur. Fertilizers such as ammonium sulfate, a common source of S in the past, are no longer being used as commonly as non-S-bearing aqua ammonia and other high-analysis fertilizers and therefore S deficiencies might occasionally occur. Broadcast and incorporate elemental S into S-deficient soils at a rate of 50 to 100 pounds of S per acre to provide a correction that will last several years. Elemental S is best applied in the fall when the fields are bedded up to allow time for oxidation to sulfate-S, the form used by plants. The time necessary to oxidize elemental S depends on soil temperature and moisture, as well as on the size of the particles applied. Particle size may cause the timeline to change from a few weeks to several months before the applied elemental S becomes effective. Other materials such as gypsum , which is about 17% S, provide the readily available sulfate form of S and can also be used. These materials should be applied at a rate that supplies about 25 to 50 pounds of S per acre and should be incorporated into the top 2 to 3 inches of soil to be most effective.Although soil moisture can be assessed by using the “look and feel” method, rolling benches for growing soil moisture sensors can provide more accurate information. There are many sensor options available to growers, including tensiometers and gypsum blocks, that are accurate and relatively easy to use and inexpensive.

Tensiometers indicate soil moisture levels by measuring the soil moisture tension, or how strongly water is held onto soil particles. Therefore, low soil moisture tension indicates moist soil, and high soil moisture tension indicates dry soil. Gypsum blocks buried in the soil measure the electrical resistance of water, which can be converted into a soil moisture tension value. Soil moisture tension is usually expressed in centibars . Soil moisture sensors must be installed in areas that are representative of the field; that is, the site must have a soil type that is typical of the field and needs to receive full irrigation coverage. Sensors should be installed to the depth of the active root water uptake zone, which for sunflowers would be 4 feet. Monitor soil moisture at 1 foot, 2 feet, 3 feet, and 4-feet deep to determine when to irrigate and to ascertain the depth or adequacy of an irrigation. It may also be useful to monitor at 5 feet to determine whether excess irrigation water is being applied, causing water to percolate past the sunflowers’ 4- to 5-foot rooting depth. The threshold level for soil moisture in the root zone for sunflowers and irrigation needs depend on soil type, irrigation system , growth stage, and amount of deep moisture in the soil profile. General guidelines for soil moisture monitoring can be given based on limited experience with sunflower production in clay loam soils in the low desert of California. For heavy soils, the upper limit for soil moisture depletion in the top 2 feet of the root zone is 90 to 120 cb. Irrigation should be applied when soil moisture content reaches this threshold level. If soil moisture is depleted beyond this level, the crop will be under stress.

However, roots can extend beyond 4 feet and this threshold could be reached and the crop may not show signs of stress if there is moisture in the deeper soil profile or a shallow water table available up to 6 to 8 feet below the soil surface. In experiments conducted at the UC Desert Research and Extension Center from 2016 to 2018, sunflower plots that were subjected to 60 percent deficit irrigation practices showed no stress and yields were not affected by the reduced water applications due to the presence of a shallow water table 6 to 8 feet below the soil surface.In some years, soil pests that live at or below the soil line, such as variegated cutworm , wire worms , and seed corn maggot , can seriously damage seedlings and cause significant stand losses. These pests tend to be sporadic in time and space; they tend to be more troublesome in wet years when weed vegetation is heavy, and they have a patchy distribution in fields. They are often problematic in the same field year after year, so monitoring and being familiar with the history of the field is important for managing these pests in crop rotations. Use of insecticide seed treatments, such as Cruiser 5FS will help control early-season soil-dwelling pests. Sunflower Moth Sunflower moth, also known as sunflower head moth , is the most serious pest of sunflower in California and other U.S. sunflower growing states. The adult sunflower moth is grayish, ⅜ inches long, and rests with wings clasped tightly to the body, giving it a slender cigar shape . Eggs are difficult to find because they are usually laid at the base of florets in the flower head. The newly hatched larvae are pale yellow but darken to shades of brown with longitudinal white stripes and a light-brown head capsule. Insect excrement and tangled mats of webbing on the flower heads indicate larval activity . Mature larvae drop to the ground on a strand of silk, crawl into cracks in the soil, spin cocoons, pupate, and later emerge as adults.

There can be 3 generations of head moth per year. In California, the sunflower moth likely overwinters as a larva in the cocoon stage in the soil. In colder climates, such as Midwestern states, the moth is migratory. In the Sacramento Valley, the moths begin to emerge in June and are generally most troublesome in July and August. Early-planted fields sometimes escape moth damage, as moths seem to build up on early planted fields and disperse into later planted fields when they reach greater numbers. In the Imperial Valley, plantings are generally early enough that they escape head moth flights, but if one occurs, it would be in May. Significant outbreaks of sunflower moth can occur, with yield losses of 30 to 60 percent and occasionally 100 percent in fields where the moths are not controlled. The only way to effectively and economically manage this pest is through insecticide treatments. There are no effective cultural practices, and bio-control cannot be relied on because the primary brachonid parasitoid wasp in sunflowers cannot readily reach the head moth larvae deep in the florets with its ovipositor or break through the seed shell to reach the larvae and sting them. Sunflower moths can be monitored using Pherocon IIB pheromone traps baited with sunflower moth pheromone lures. Two traps are generally placed along the north and south side edges of fields, taking advantage of the prevailing winds to maximize trap catches. Traps should be monitored weekly, and more often during bloom when sunflowers are most sensitive to damage by the moths. When trap thresholds reach 4 or more moths per night, especially with July and later-blooming fields, the field should be treated with an insecticide to prevent damage and crop losses, cannabis dry racks especially from secondary pathogens. When using insecticides during bloom, it is critically important to protect honey bees to promote bee activity and crop pollination. If an insecticide treatment is needed, spray before hives are brought into fields prior to bloom or early in the morning before bees are visiting flowers. Insecticides that control head moth include Coragen , Warrior or Asana , and XenTari . Coragen does not control adult moths but gives good caterpillar control with recommendations to apply twice, once at the late flower bud stage and again at the very beginning of bloom , to ensure good coverage and protection. Coragen is relatively safe for bees, but applications should be made early in the morning when bees are less active to protect them from harmful effects of sprays.Lygus bugs are small plant bugs with a very distinctive yellow V on their back . They are serious pests of numerous crops, including strawberries, beans, and cotton. In confectionary type sunflowers, feeding damage causes brown spots known as kernel brown spot , reducing the quality of the seed for the snack food industry. However, the impact of Lygus on hybrid seed production is unclear. Lygus feeding damage may reduce sunflower seed germination, a focus of current UC ANR research. Western Flower Thrips Western flower thrips are tiny, slender, light-yellowish insects.

The nymphs are wingless, while adults have clear, slender wings . When they feed, they generally cause leaves to be deformed, but they also leave behind silver patches on the lower side of leaves with tiny black fecal pellets. Plants usually outgrow the problem, just as they outgrow severe leaf tattering from wind damage. However, high numbers of thrips and heavy feeding damage can injure seedling stands if temperatures are high and plants are water stressed, and they may require a pesticide treatment for control to prevent stand loss.Two-spotted Spider Mite Two-spotted spider mites are found in sunflowers, particularly later in the season as the plants senesce. Mites are small, pinhead-sized, oblong, and yellowish with two dark pigmented spots, and they have eight legs . The eggs of spider mites are whitish and spherical and can be seen with a hand lens. Spider mites are usually found on the underside of leaves, with colonies beginning on the lower leaves and moving upward on the plant. Spider mite feeding damage first appears as stippling on leaves. As numbers increase, spider mites spin fine webbing and move rapidly around the plant on the webbed area. Damage in heavily infested plants includes leaf desiccation with a whitish-gray cast and stunted plants. Infestations are usually associated with mature plants, dust along field edges from dirt roads, water stress, and natural senescence and control is generally not needed. Postharvest Storage Pests Sunflower seeds destined for export must be examined to ensure that they are free of stored product insect pests. These include dermestid beetles ; weevils ; lesser grain borer ; sawtoothed grain beetle ; red and confused flour beetles ; and slender and broad horned flour beetles . More information on stored product pests and their control can be found in the pantry pests notes and in Residential, Industrial, and Institutional Pest Control by O’Connor-Marer .California’s dry climate, and rich, irrigated soils provide excellent conditions for growing strong, healthy sunflowers that experience fewer diseases with less severity than sunflowers grown in the main oil-production areas of the Midwest under summer rainfall. Very few of these diseases lead to yield losses in California growing conditions, but many are of quarantine significance and thus would preclude seed from being exported to foreign countries. This could cause serious economic impacts, so it is important to monitor for diseases. The fungal diseases in California sunflower production classified as quarantine status by many foreign countries include downy mildew , rust , and Sclerotinia head and stalk rot . Fortunately, these diseases are very rare in California due to our hot, dry summers. In a 15-year study by Gulya et al. , only three quarantine-type diseases were found in sunflower in California, including rust in 4% of fields, Sclerotinia rot in 2.6% of fields, and downy mildew in 0.4% of fields. Each importing country has different pathogens that are excluded. Since U. S. companies may not know in advance where the seed will be exported, it is imperative to ensure fields are free from as many diseases as possible. If the pathogen involved is soilborne, rotate to a nonsusceptible crop to reduce the disease inoculum in the field. Downy mildew and rust are sunflower-specific diseases, so any crop is suitable to rotate for controlling them. However, for pathogens with a broad host range like Sclerotinia spp., nonhost monocots must be rotated to help reduce the sclerotia soil inoculum. For diseases such as Rhizopus head rot, rotation offers nohelp since the fungus is ubiquitous and persists as a saprophyte on any organic matter.

These two weevils are the most widely used biological control agents of water hyacinth, Eichhornia crassipes , a floating aquatic plant native to South America. Classical biological control of water hyacinth has been implemented across the globe, with some introductions resulting in significant reduction in water hyacinth cover and/or bio‐ mass, including parts of Australia, China, East Africa, the U.S. Gulf Coast, India, Mexico , and the lower elevation regions of South Africa . Releases of N. bruchi and N. eichhorniae from the native range began in the early 1970s, with initial and subsequent releases in 30 and 32 countries, respectively. These weevils have contributed substantially to the control of water hyacinth in at least 13 countries . Through their use as biological control agents, these two weevil species have often undergone multiple and serial introductions . For example, in the United States, weevils of N. eichhorniae released into northern California underwent four sequential importation steps from the original Argentinian population in the native South American region. Native Argentinian weevils were re‐ leased into USA: Florida in the 1970s, and the weevils in USA: Florida were used to found a population in USA: Louisiana, which were then used to found populations in USA: Texas. This USA: Texas population was the source for the northern California population released in the early 1980s . Similarly, in South Africa, there were multiple introductions of each N. bruchi and N. eichhorniae with each new release being sourced from a different location to which they had been introduced for biological control , cannabis drying racks rather than directly from the native range. These multiple introductions from the non‐native range represent serial bottlenecks in population size that could potentially reduce genetic diversity and limit adaptive potential.

Alternatively, these multiple introductions from different source populations could increase genetic diversity through genetic admixture of the different source populations . The latter may occur particularly if each source population had sufficient time to diverge or adapt to the region of introduction, resulting in increased genetic differentiation from its source population. Based on the importation history and documented releases of these two biological control agents, we proposed several hypotheses addressing our five study questions in turn. We hypothesized that hybrids of these two species would occur, as they have frequently been co‐introduced to the same geographic regions and individuals with morphological characteristics of both species have been found . We hypothesized that genetic diversity would be the highest in the native range compared to regions where the weevils were introduced as biological control agents. Similarly, we hypothesized that the populations from the native range would have more rare alleles than the introduced regions. We hypothesized that allelic richness would reflect the number of individuals released . Specifically, as the initial propagule size of N. bruchi was greater than that of N. eichhorniae in USA: Florida, we ex‐ pected that populations of N. bruchi in USA: Florida would be less likely than populations of N. eichhorniae to lose rare alleles and exhibit reduced allelic richness in the introduced range compared to the native range. In cases where multiple introductions were prominent, particularly regarding the introduced populations of N. eichhorniae in South Africa, we hypothesized that the geneticad mixture would increase genetic diversity and buffer against the negative effects of serial bottlenecks. On a global scale, regarding the number of serial introductions, we hypothesized that populations with more introduction steps away from the native range would harbor lower genetic diversity than those with fewer steps. As the initial releases occurred over 40 years ago, we hypothesized that despite originating from the same initial populations that most introduced populations would have diverged genetically from the native range and each other.Importation and release history were obtained from peer‐reviewed literature, government reports , shipment letters , unpublished quarantine records , and published quarantine records .

However, there were many gaps, as details in the importation and release history of biological control agents are often missing or not easily accessible to the public including the number of adults surviving shipments, the number used for mass‐rearing after quarantine inspection, the number ultimately released, the localities of the releases, and whether multiple releases occurred. From the shipment letters and quarantine reports pertaining to the initial exports from Argentina to USA: Florida , it appears that samples from at least two populations of N. bruchi and N. eichhorniae were collected from Argentina and released in USA: Florida. Initial shipments of N. bruchi received in 1974 to the USA: Florida quarantine consisted of 156 and 1,050 surviving adult weevils from collections in Campana Lagoon and Dique Lujan, Buenos Aires, Argentina, respectively. However, it is unclear whether or not individuals from Campana were used for mass rearing, based on notes about possible infections by nematodes. Additional shipments from these collection sites appear to have occurred around this same time, but it cannot be confirmed whether they were used for augmenting the populations that were eventually released. Samples from two populations of N. eichhorniae were collected and shipped in 1971, with the number of surviving adults arriving in the quarantine in USA: Florida documented as 10 from Campana Lagoon and 156 from Santa Fe, Argentina, with these collection sites c. 300 miles apart. An additional third population of N. eichhorniae may have been received, containing a mixture of 219 weevils from Campana and Dique Lujan Buenos Aires and arriving in 1975 . However, these reports indicated potential nematode and fungal infestation in this later shipment, and again it was not clear whether or not offspring from these weevils were included in augmentation of laboratory colonies or released. In 1980, following the quarantine and mass‐rearing periods in USA: Florida, 50 N. bruchi adults were released from USA: Florida in Wallisville Reservoir, Texas, USA . N. eichhorniae were found in this same reservoir as a consequence of westward migration from a biological control site in Louisiana .

In 1981, 500 adults of N. eichhorniae were imported from Louisiana populations and released in Wallisville, Texas . A total of 7,500 N. eichhorniae and 2,823 N. bruchi from the populations in Wallisville Texas were then released across four locations in the Sacramento–San Joaquin River Delta in California . All other importation data pertinent to this study are summa‐ rized in Figure 1 and further detailed in the Supporting Information Appendix S1.Potential microsatellite loci for N. bruchi and N. eichhorniae were identified using a Perl script, PAL_FINDER_v0.02.03 , and Primer3 to analyze 150‐bp paired‐end Illumina sequences from extracted DNA enriched for mi‐ crosatellite loci at the Savannah River Ecology Laboratory . From this, primers were designed for 48 loci, using only those with tri‐ and tetranucleotides and those with at least six repeats. For each species, the final loci for analysis were tested on DNA extractions from 24 adult weevils ranging across several collection sites. A set of 10 and 11 microsatellite loci for N. bruchi and N. eichhorniae, respectively, met the criteria of selection, that is, purerepeat, polymorphism, and amplification by PCR. Following amplifi‐ cation by PCR, eight and 10 loci, respectively , were kept for the statistical analysis due to the high occurrence of null alleles in two loci for N. bruchi and one locus in N. eichhorniae. After the initial screening, weed growing rack primers were combined in three multiplex reactions per individual for each species. For each 96‐well plate, we included a negative control and an internal control of aliquoted DNA from an individual weevil that was used on every plate for the respective species. PCR multiplex reactions were run separately for the two species to avoid cross‐contamination. Pig‐tails were added to the 5′ end of each reverse primer, and one of four different universal tails was added to the 5′ end of each forward primer . The system of universal tailed primers was used to introduce a fluorescent dye during the PCR according to Blacket et al., and Culley et al. . Initial single plex and subsequent multiplex PCRs were in a final volume of 10 μl containing 50–70 ng of DNA, 5 μl of Qiagen Multiplex PCR Master Mix, 0.2 μM of reverse primer, 0.05 μM of for‐ ward primer, and 0.2 μM of the corresponding fluorescent primer using fluorescence‐labeled oligos , and the addition of 2 μl of Qiagen Multiplex Q‐solution for several of the multiplex reactions . PCR was performed at the following conditions: 95°C for 15 min; 35 cycles of 94°C for 30 s, the optimum annealing temperature of each primer for 1.5 min, 72°C for 1 min, and a final extension of 30 min at 60°C. Following successful amplification, 0.5 μl of the amplified prod‐ uct was added to 11 μl of solution containing 10.5 μl Hi‐Di formamide and 0.5 μl Liz size standard. Fragment lengths were measured in comparison with the GeneScan™ LIZ® 600 Size Standard v. 2.0 and genotyped on an Applied Biosystems 3730XL DNA Analyzer at the DNA Sequencing Facility at the University of California Berkeley. Fragment lengths were manually scored and binned using the Microsatellite Plug‐in for Geneious Pro v. 5.6.2 . We re‐ran multiplex reactions and subsequently re‐genotyped samples if clear peaks were not obtained in the first run. Genotype scores were checked with the program MICRO‐ CHECKER v. 2.2.3 to identify possible null alleles and genotyping errors due to stuttering and large allele dropout .We re‐examined the relevant raw genotype data and either corrected the peak calls, or removed individuals that had poor quality peaks based on the recommenda‐ tions of MICRO‐CHECKER. Genotype scores from the two wee‐ vil species were divided into two datasets for each species as the microsatellite markers did not overlap for weevils with diagnostic morphological characteristics for N. bruchi and N. eichhorniae. The dataset for N. bruchi consisted of genotype scores for 171 weevils from eight independent collection sites among five countries. The second dataset for N. eichhorniae consisted of genotype scores for 267 weevils from 11 independent collection sites among seven countries . Final genotype scores for each individual, species, and collection site are in the Supporting Information Appendix S4. We used the program GenAlex and the R packages, “poppr” v. 2.5.0 and “adegenet” to convert genotyping results into formats suitable for analysis in R . We calculated the null allele frequency from the final datasets in the R package “pop‐ genreport” . As some statistical tests assume linkage equilibrium and Hardy–Weinberg equilibrium , we assessed deviations from LE with “poppr” and deviations from HWE across all sites for each locus with the package “pegas” . We constructed genotype accumulation curves with the R packages “poppr” and “vegan” to test whether sufficient sampling had been performed for each species and collection site.To evaluate whether co‐introduction of these two related weevils species resulted in hybridization, we first identified individuals for each species that had ambiguous markings on the elytra that contrasted the typical morphological characteristics for that species . Then, we tested both sets of species‐specific microsatel‐ lite markers on 12 weevils with ambiguous morphological characteristics, as well as on weevils that had the typical species‐specific morphological characteristics for comparison. Hybridization is inferred from at least two of the species‐specific markers from each species amplifying in the same individual .As bottlenecks in population size can reduce genetic heterozygosity through processes of genetic drift and inbreeding, we estimated the average observed and expected heterozygosity, deviations from HWE , and the average “inbreeding coefficient” for each collection site across all loci with the R package “diveRsity” . Here, we use FIS to estimate increases in ho‐ mozygosity due to genetic drift caused by a larger population being separated into sub‐populations, rather than due to consanguineous mating . Thus, we used “g2” to test for inbreeding within populations of each weevil species by using 1,000 permutations in the R package “InbreedR”. In populations with inbreeding, g2 is significantly greater than zero, indicating correlated heterozygosity among pairs of loci . We compared total and aver‐ age allelic richness and the number of private alleles among collection sites . To compare genetic diversity among the introduced and native populations, we tested for the effects of population on genetic diversity by fitting linear mixed models with the lmerfunction in the lme4 package . Implementing an LMM accounts for the variability of the mi‐ crosatellite loci by modeling locus as a random effect, and collection site as a fixed effect with allelic richness or expected heterozygosity as the response variables in separate models.

Twenty-seven weedy rice plants were chosen for genotyping along with 12 accessions of temperate japonica varieties that are cultivated in California. Leaf tissue from the outdoor grown plants was excised and desiccated for shipment to Clemson University for DNA extraction. DNA was extracted from desiccated leaf tissue using the Macherey-Nagel NucleoSpin 96 Plant DNA extraction kit . Purified genomic DNA was diluted 2:1 in nuclease-free water for polymerase chain reactions . PCR was carried out using standard conditions to amplify 48 gene fragments selected by [21] from 111 sequenced tagged sites developed by [38]. PCR products were checked by gel electrophoresis and cleaned up using Exonuclease and Antarctic phosphatase treatment following the method described in [39]. Direct sequencing in both the forward and reverse directions was carried out by the Clemson University Genomics and Computational Biology Laboratory. Sequences were assembled into contiguously aligned sequence ‘contigs’ and assigned quality scores using Phred and Phrap. Contigs were aligned and inspected visually for quality and heterozygous sites in BioLign version 4.0.6.2 . Heterozygous base calls were randomly assigned to two pseudo-haplotypes, which were then phased using PHASE version 2.1. Due to low levels of heterozygosity in the data set, haplotypes were inferred with very high probabilities and consistency across five runs. All sequences have been submitted to NCBI GenBank . Phased haplotypes were aligned with sequences obtained from [21]. These additional sequences consist of the same 48 STS loci for a broad range of AA genome Oryza species including 58 weedy rice accessions sampled over a 30 year period from Arkansas, Louisiana, Mississippi, Missouri, and Texas. Also included in this dataset are sequences from the major cultivated groups from Asia and Africa , vertical racking as well as wild species sampled from Asia , Africa , Central America , and Australia.

Genetic structure and divergence. Summary statistics for each STS locusincluding nucleotide diversity at silent sites using the Juke’s Cantor correction, Watterson’s θ at silent sites, number of segregating sites S, and Tajima’s D were calculated in DnaSP version 5.0 . Arlequin version 3.5 was used to calculate pairwise FST and ФST estimates with 10,000 permutations to assess significance.Bonferroni corrections were used to determine Pvalue cutoffs. Recombination break points in each locus were determined using the four gamete test in SITEs. The population-mutation parameter FST is an estimate of genetic divergence within and between groups and was used to test for the extent of genetic differentiation. To better estimate divergence betweenCaliforniaweedy rice and other rice groups, the population mutation parameter ФST was used, which is similar to FST but uses distances between haplotypes, not just haplotype frequencies. Genetic diversity was measured by computing the average nucleotide diversity , total number of segregating sites, and Watterson’s θw within each field as well as within all fields combined. Population structure was inferred using InStruct, which was designed to allow for inbreeding by not assuming Hardy-Weinberg equilibrium within populations. Using STRUCTURE for inbreeding populations results in inappropriately higher rates of inferred splitting between populations . Five permutations for each number of populations were set from 1 to 22 with 500,000 steps and a burn-in period of 100,000 steps. In Structruns were completed on the Clemson University Condor computing cluster. Log likelihoods for each run were compared to determine the best fit K value. Distruct version 1.1 was used to create the graphical display from the results obtained with InStruct. Isolation with Migration modeling was used to test for best fit models of isolation-migration and simultaneously estimate effective population sizes , migration between populations , ancestral population size and time since divergence .

California weedy rice was compared on a pairwise basis to California cultivated rice , strawhull weedy rice, blackhull weedy rice, O. rufipogon and O. nivara. Recombination was only detected in O. rufipogon, so the longest nonrecombining blocks were only utilized in the comparisons including O. rufipogon. Each comparison was run in M-mode with wide value cutoffs for all parameters to determine where posterior probability distributions ranged. After the initial run, three runs were conducted with different random number seeds and smaller cutoff values that were based on the distribution of parameter values from the first run.All runs had 100,000,000 MCMC steps after a burn-in of 100,000 steps. Each run had 10 chains with a mixing rate of five chain swaps per step. All three M-mode outputs were checked for convergence and L-mode runs were conducted on the tree files to test nested models. The maximum likelihood estimates were scaled into demographic values based on a mutation rate of 1 × 10−8 and a generation time of one year, as done with previous work, based on. All IMa runs were computed on the Condor cluster at Clemson University using primarily an extensive web-enabled system to simultaneously manage and monitor performances of each set of input priors. Use of a cluster allowed for more than 28 simultaneous runs, where priors could be checked and adjusted as needed. Multivariate analysis of trait variance. The goal of these phenotypic analyses was to elucidate genotype-phenotype relationships between California Oryza cultivar and weedy riceecotypes. Thus, we determined the most influential phenotypic footprints of rapid divergence in domestic and wild-like traits of rice and its conspecific weed within the California floristic province. To characterize trait variability and by extension morphological relationships among domesticated and weedy rice ecotypesin infested fields, we quantified phenotypic diversity by first describing the variance partitioning of weedy populations and comparing the adaptive traits which characterized weedy rice to those that defined cultivars. To more accurately characterize dimensionality in weedy or feral rice morphology, a subset of unique gourmet varieties were added to the medium-grain cultivars in the rice dataset for the phenotypic diversity analyses.

Qualitative descriptors were transformed using the PRINQUAL procedure of SAS with the OPSCORE option for optimal scoring and MONOTONE option for monotonic preservation of order. Principal Components Analysis with maximum total variance was performed on the combined quantitative and transformed qualitative descriptors. The variables describing cultivars were reduced by eliminating any that did not vary by descriptive statistics and then using both random and a priori sampling to preserve group partitioning while identifying the eigenvectors which most clearly separated groups. UPGMA hierarchical clustering using the CLUSTER procedure of SAS was performed to confirm separation of clusters on PCs and to generate a dendrogram using average Euclidean distances. Qualitative transformations, PCAs, and MANOVAs were executed in SAS1 Version 9.3 . Average estimates of genetic differentiation between weedy rice in California rice fields are very low, ranging from 0 to 0.0026 . There are no significant differences in FST estimates for any of the 48 loci. The highest FST estimate was 0.077, betweenCRR1 and CRR4 at STS085. These low values indicate no population structure and no divergence of weedy rice in the fields sampled, which supports the appropriateness of a genetic diversity assessment for California weedy rice . Measures of genetic diversity for California weedy rice within each field as well as for weedy rice within all fields combined are also very low , rolling benches consistent with a recent founder event, or strong population bottleneck. These values are a full order of magnitude lower than what was calculated for strawhull and blackhull weedy rice ecotypes collected from the southern US. Due to the lack of population substructure and low genetic diversity, we placed all California weedy rice into one group for the remaining analyses. Values for average population differentiation estimates across all 48 loci indicate high divergence between California weedy rice and all other sampled groups. The lowest mean value is with O. rufipogon collected from Southeast Asia . Taking the median values across the 48 loci allows better understanding of the patterns across all loci. The lowest divergence was between California SHA weedy rice and BHA and SH; median ФST values indicated that for at least half of the loci tested divergence was an order of magnitude lower than the mean estimates . This indicates that the mean ФST is high due to divergence at a few loci, and that California weedy rice does share some similarity to weedy rice from the southern US at several loci.The most recent divergence of California weedy rice from other Oryzasis from California rice cultivars , which was estimated at about 118 generations ago . The other divergence estimates were over an order of magnitude older . Interestingly, both SH and BHA weedy rice from the southern US have very old divergence estimates: approximately 30,000 and 17,000 , respectively.

These numbers are likely inflated compared to the reported origin of domesticated rice approximately 10,000 generations ago due to interactions among other closely related genotypes. This follows work examining model testing performance of IMa under several scenarios,which showed that divergence estimates inflate when gene flow from other populations is included in the model. A model of relative divergence times shows a shallow, recent coalescence of California weedy rice and California crop rice alleles, whereas SH and BHA southern US weedy rice and Chinese O. rufipogon show a much older divergence from California weedy rice . Migration estimates between California weedy rice and all other groups were quite low, with higher estimates of migration into California weedy rice in all cases. Indeed, these data should not be interpreted as absolute numbers but instead as relative values. Any overestimation of the generation values could otherwise indicate that the divergence actually happened even more recently. The effective population size for California weedy rice is very small in all cases,supporting a recent founder event or bottleneck.California weedy rice differs morphologically from other southern US weedy rice ecotypes. California weedy rice has a straw-colored hull with long awns , whereas only 7%of SH weedy rice in the southern US has awns. Nevertheless, California weedy rice shares important weedy traits with those of southern US weedy rice including high seed shattering and a red-colored pericarp in addition to tall stature and high tillering habit.Principal components analysis reduced the set of observed variables for California weedy and cultivated rice by loading them on orthogonal lines of fit based on contributions tovariance. No variation was observed amongst weedy and cultivated rice for leaf texture and angle, ligule shape, ligule color, ligule pubescence, auricle color, node color, or panicle secondary branching, so these traits were excluded from the analysis. When multiple traits represented the same metric, we chose the variable with the highest eigenvector value to represent each group or suite of highly correlated traits, although each group member or variable has an impact when describing the underlying mechanism responsible for phenotypic selection differences between the cultivar and weedy rice in California. Importantly, pericarp color clearly distinguishes weedy from cultivated rice in California , but is not highlighted in the dimension-reducing PCA because it was scored as a qualitative trait following International Rice Research Institute descriptor guidelines. The remaining phenotypic traits included vegetative growth habit characters, reproductive morphologies, and yield metrics related to grain morphology. Principal components analysis was conducted on these informative traits, excluding highly correlated variables . A second PCA was performed on a reduced dataset, which included the five traits with highest eigenvector values for each principal component in the initial analysis . Principal Components 1 , 2 , and 3 together account for 45.18% of the total cumulative variance in cultivated and weedy rice in the first PCA . Traits most greatly discriminating California weedy from cultivated rice include panicle type, leaf width ,flowering , awn color, and culm length ; lemma pubescence, texture of the panicle axis, length of the first leaf below the flag leaf, length/width ratio of grain, and width of flag leaf ; 100-grain weight of the field-collected mother plant, awn length of the field-collected and offspring plants, spikelet fertility , and grains per panicle described most of the variation along PC3. Because we were interested in the contribution of suites of traits describing each statistically significant orthogonal vector, the 15 traits contributing most to variance along the first three PCs in PCA 1 were subjected to a second analysis. In PCA 2 of “key discriminating traits,” principal components 1 , 2 , 3 , and 4 account for 74.91% of the cumulative variance in the phenotype of California weedy rice . Since components or dimensions with an eigenvalue greater than one are statistically relevant to the result , we report four principal components for this second PCA.

Restriction digestion of the target region-specific PCR product from lines 1, 2, 5 and 11 revealed that lines 1 and 5 were fully resistant to BsrI digestion, whereas line 11 showed partial digestion. However, line 2 showed complete digestion of the PCR product, similar to the wild type . Sequencing analysis of the target region PCR product from T0 lines 1, 2, 5 and 11 revealed the presence of different kinds of mutations in each line. Line 1 had a 1-nt deletion and line 2 had a 3-nt deletion; the 3-nt deletion in line 2 regenerated the BsrI restriction site, resulting in BsrI digestion of the PCR product in this line. In addition, these lines showed a single peak in the Sanger sequencing chromatogram, suggesting that they represent homozygous mutants for the CCD8Cas9 locus . However, lines 5 and 11 showed multiple peaks in the sequencing chromatogram, suggesting that they are either biallelic or chimeric mutants . Purified non-digested CCD8Cas9 target regionPCR fragments from lines 5 and 11 were cloned into a TA cloning vector. Sanger sequence analysis revealed that lines 5 and 11 are biallelic and contain four types of mutations: a 6-, 5- or 4-nt deletion, or an A insertion. Interestingly, in line 5, both alleles lost the BsrI restriction site whereas in line 11, one of the alleles restored the BsrI cut site after Cas9-mediated editing of the target . T0 transgenic tomato lines were grown to maturity and self-pollinated to generate T1 progeny. T1 progeny from lines 1, 2, 5 and 11 were designated with a small letter next to the line number . Genomic DNA was extracted from the T1 progeny and the target region of CCD8Cas9 was amplified using PCR primers fanking the target.

When this analysis was performed on T1 lines, results were similar to those with the T0 lines: lines 2a and 2b were completely digested, vertical racking indicating that the BsrI site was preserved; however, lines 1a, 1b, 5a, 5b, 5c and 11a gave PCR fragments that were resistant to BsrI digestion, indicating that the CRISPR-generated mutations in these lines were inherited from the T0 lines . Sanger sequencing of the non-BsrI-cut fragments showed deletion mutations of various lengths upstream of the PAM sequence, similar to T0. Lines 1a and 1b each contained the same 1-nt deletion and lines 2a and 2b each had the same 3-nt deletion. Moreover, biallelic mutations were detected in lines 5a, 5b, a 4-nt deletion was observed in line 5c, and a 6-nt deletion was found in line 11a . At least 15 plants from each of the T1 lines were examined for genotype at the target site using Sanger sequencing of target-site PCR products. All T1 plants from two T0 homozygous lines were homozygous for the same mutations. In contrast, the biallelic T0 lines of the Cas9-generated mutants were segregated in the T1 generation according to classic Mendelian genetics, and the ratios between the two mutations in a biallele were close to 1:2:1 as reported previously. The existence of the same mutations in sibling progeny suggested that the CRISPR mutation event occurred prior to meiosis in T0. Inheritance of the mutations in homozygous and biallelic T0 plants by T1 plants suggested that most, if not all, of the mutations resulting from genome editing activity are highly stable in nature and can be inherited in subsequent generations. Moreover, examination of transgenic region in some of the T1 generation plants suggest that 35% of line 2 and 25% of line 5, T1 plants were detected to be transgene free . The results indicated that CCD8Cas9 targeted mutations inherited to next generation in transgene free plants. The putative of-target sites associated with CCD8sgRNA were evaluated by CRISPR-P program using the CCD8sgRNA sequence against the tomato genome.

We analyzed three potential of-targets sites with high scores, which occurred in the intergenic and CDS regions of the tomato genome. Two plants from each line were selected from the T1 generations of CCD8Cas9-edited tomato plants. Sequencing of PCR products from these regions revealed no changes in the putative of-target sites in the CCD8Cas9–mutant lines .Previous studies on SL biosynthesis using rice dwarf mutants have reported that SLs regulate plant growth and morphological architecture. Furthermore, ccd8 a SL-deficient mutant of pea is known to exhibitincrease in shoot branching, lateral roots and overall dwarfing. We also observed similar phenotypic profile in CCD8Cas9 mutated lines such as highly branched shoots, increased lateral roots, decreased shoot heights and reduced fruit sizes as compared to the wild type plants . Although, morphologically, all CCD8Cas9 mutant lines showed highly branched shoots irrespective to the type of mutation but no significant differences were found in the root mass between CCD8Cas9 mutated and control plants . Interestingly, CCD8Cas9 mutated tomato lines produced considerable more number of fruits with reduced sizes as compared to the non-mutated wild-type plants . To analyze whether the CRISPR/Cas9-generated mutations in the CCD8 gene confer resistance to P. aegyptiaca, independent transgenic tomato plants from T1 lines representing the CCD8Cas9 knockout phenotypes, were triggered with P. aegyptiaca seeds. Randomly chosen T1 progeny of each lines, irrespective of their zygosity were transplanted into small pots containing soil infested with P. aegyptiaca seeds and grown for 3 months in a greenhouse. Two separate experiments with four replicates per treatment were conducted. To measure the resistance of the CCD8Cas9 mutated lines, we counted only fresh and viable parasite tubercles which are larger than 2 mm in diameter from each plant. The numbers of attached parasitictubercles and shoots were significantly reduced in the CCD8Cas9 mutated lines relative to the wild-type plants. However, the decrease in P. aegyptiaca in some of the line 11 mutants was less pronounced relative to the wild-type plants than that observed for lines 1, 2 and 5 .The tomato host plant produces different kinds of SLs—mainly orobanchol, didehydroorobanchol isomer 1 and 2, and the aromatic SL solanacols, including the recently identifed orobanchyl acetate, 7-hydroxyorobanchol isomers 1 and 2, and 7-oxoorobanchol. However, Orobanche preferentially utilizes orobanchol as the most active germination stimulant , whereas solanacol and 7-oxoorobanchol are weak stimulants.

To explore the connection between SL biosynthesis in the CCD8Cas9 mutants and their resistance to P. aegyptiaca infection, we analyzed the total orobanchol content in the roots of wild-type and CCD8Cas9 mutated T1 lines by LC–MS/MS. Orobanchol levels were significantly decreased in the CCD8Cas9 mutated lines 1b, 2a, and 11b compared to the wild type, whereas orobanchol was not detectable in lines 1a, 2b, 5a, or 5c . This is consistent with line 5 showing the highest resistance to P. aegyptiaca. In addition, although CCD8 was modified in line 11a, and the plant exhibited the typical dwarfing and shoot-branching phenotypes of reduced SL, its orobanchol content was higher than in the other modified lines. The higher orobanchol content was consistent with its lower resistance to P. aegyptiaca. To assess the higher orobanchol content in line 11a, we analyzed the DNA mutations and resulting amino acid sequences in all CCD8Cas9 mutated lines that were sampled for LC–MS/MS analysis after PCR products ligated to the TA cloning vector . The type of DNA mutation and the amino acid sequence in line 11a demonstrated that only 2 amino acids, His- 243 and Pro-244, were deleted due to Cas9 editing in the target CCD8 gene, while the rest of the coding sequence was similar to the wild-type protein .Carotenoid biosynthetic pathway derivatives all trans β- carotenoid leads to production of SL. Since CCD8 catalyze a key step in SL biosynthesis from carotenoids; hence, we are interested to discover whether CCD8Cas9 mutation affects carotenoid content and its upstream biosynthetic pathway. A simplified scheme of the correlation between carotenoid and SL biosynthesis pathways and furidone target site is illustrated in Fig. 6a. First, rolling benches to explore whether CCD8Cas9 mutation affect the carotenoid content, the content and type of carotenoid present in the root of wild type and CCD8Cas9 mutated lines were analyzed by HPLC method. Interestingly, CCD8Cas9 mutation altered the profile of differenttypes of carotenoids and its derivative, such as total carotenoids, lutein; β-carotene were substantially altered from the wild type . To further gain insight into the above results, we analyzed the expression of prominent gene Phytoene desaturase-1 and Lycopene cyclase 1-β , involved in the carotenoid biosynthetic pathway which acts upstream of CCD8. Results obtained using quantitative real-time PCR demonstrated that expression of PDS1, LCY-β and CCD8 was upregulated in CCD8Cas9 edited T1 lines as compared to the wild type .These results demonstrate that a decrease in SL content in the root of CCD8Cas9 mutants, affect the carotenoid profile by modulating expression of the gene involved in carotenoid pathway.Biotic stresses induced great economic challenges for farming and food production worldwide. Broomrapes that affect the roots of many economically important agriculture crops throughout the semiarid regions of the world especially the Mediterranean and Middle East, are regarded as some of the most serious pests in vegetable and feld crops. Efective means to control parasitic weeds are scarce and lack of novel sources of resistance limits our ability to manage newly developed, more virulent broomrape races. Therefore, an innovative solution to the problem is greatly needed.Recent work utilized the power of CRISPR/Cas9 to engineer the rice plant architecture through genomic editing of OsCCD7 gene, having decreased SL and reduced Striga hermonthica germination. Utilizing similar CRISPR/Cas9 genome-editing strategy, we have developed non-transgenic tomato mutant plants with no “foreign-DNA” that exhibits resistance to P. aegyptiaca. We designed a CCD8sgRNA construct to target the second exon of the tomato CCD8 gene to disrupt SL biosynthesis.

Several independent T0 transgenic tomato lines—1, 2, 5 and 11—were generated, of which lines 1 and 2 were homozygous mutants whereas lines 5 and 11 were biallelic in nature. In general, T0 mutants presented somatic mutations; to avoid this, T0 plants were self-pollinated to generate T1 homozygous plants. In the T1 generation, we found homozygous deletions and insertions in the target gene that were biallelic in the T0 plants without any new mutation detected. T1 lines 1, 2, 5 and 11 were selected for further analysis because of their stable genetic modification. Te different types of mutations observed in the different lines may be due to the differential activity of Cas9, depending on the transgene insertion site, as shown previously in tomato. In addition, Sanger sequencing of potential of-target sites with mismatches of less than 4nt with CCD8sgRNA did not identify any mutations. Te CRISPR/ Cas9 system has emerged as a powerful gene-editing tool and has been successful in more than 20 crop species to date. The heritability of the mutated genes and the generation of transgene-free plants are of major concern when using the CRISPR/Cas9 system. To follow heritability, the gene PDS1 was used to demonstrate the inheritance of mutations induced in Solanum lycopersicum. Tose authors showed that the CRISPR/Cas9 can efficiently induce heritable mutations in tomato plants from the T0 to T2 generation, and that homozygous and biallelic mutants are generated, in the first generation. In our study, we also showed that the CCD8Cas9 mutations induced in T0 lines are inherited by the T1 generation. Previous reports on the morphology of tomato SlCCD8 knock down plants by gene silencing have shown an increase in shoot branching, altered lateral adventitious root growth and decrease in plant height. Similarly another studies on SL bio-synthetic gene SlCCD7, demonstrates the SlCCD7 anti-sense tomato lines also display increased branching, reduced SL content and significantly decreased germination rate of O. ramosa, however no changes in carotenoid content in the roots were observed. Our results were partially consistent with the previous studies, we observed similar phenomenon in the CCD8Cas9 tomato plants. Mutated-plants displayed a dwarf phenotype, an increased number of shoot branches, and an increased number of adventitious roots compared to the wild-type plants. In contrast to the previous report, here we discovered that CCD8Cas9 mutants have altered carotenoid content and differential expression of genes involved in carotenoid bio-synthetic pathway. An explanation for the contradictory results could be due to the differences between mechanisms of siRNA and CRISPR/ Cas9 systems. We hypothesize that absence of CCD8 gene followed by mutation in tomato plants using CRISPR system, will not restore feedback regulation. However, a small percentage of functional CCD8 gene that could escape gene-silencing system will provide feedback regulation and restore the carotenoid level upstream in the carotenoid pathway.

Recombination was only detected in O. rufipogon, so the longest nonrecombining blocks were only utilized in the comparisons including O. rufipogon. Each comparison was run in M-mode with wide value cutoffs for all parameters to determine where posterior probability distributions ranged. After the initial run, three runs were conducted with different random number seeds and smaller cutoff values that were based on the distribution of parameter values from the first run.All runs had 100,000,000 MCMC steps after a burn-in of 100,000 steps. Each run had 10 chains with a mixing rate of five chain swaps per step. All three M-mode outputs were checked for convergence and L-mode runs were conducted on the tree files to test nested models. The maximum likelihood estimates were scaled into demographic values based on a mutation rate of 1 × 10−8 and a generation time of one year, as done with previous work, based on. All IMa runs were computed on the Condor cluster at Clemson University using primarily an extensive web-enabled system to simultaneously manage and monitor performances of each set of input priors. Use of a cluster allowed for more than 28 simultaneous runs, where priors could be checked and adjusted as needed.The goal of these phenotypic analyses was to elucidate genotype-phenotype relationships between California Oryza cultivar and weedy rice ecotypes. Thus, we determined the most influential phenotypic footprints of rapid divergence in domestic and wild-like traits of rice and its conspecific weed within the California floristic province. To characterize trait variability and by extension morphological relationships among domesticated and weedy rice ecotypesin infested fields, grow rack we quantified phenotypic diversity by first describing the variance partitioning of weedy populations and comparing the adaptive traits which characterized weedy rice to those that defined cultivars.

To more accurately characterize dimensionality in weedy or feral rice morphology, a subset of unique gourmet varieties were added to the medium-grain cultivars in the rice dataset for the phenotypic diversity analyses. Qualitative descriptors were transformed using the PRINQUAL procedure of SAS with the OPSCORE option for optimal scoring and MONOTONE option for monotonic preservation of order. Principal Components Analysis with maximum total variance was performed on the combined quantitative and transformed qualitative descriptors. The variables describing cultivars were reduced by eliminating any that did not vary by descriptive statistics and then using both random and a priori sampling to preserve group partitioning while identifying the eigenvectors which most clearly separated groups. UPGMA hierarchical clustering using the CLUSTER procedure of SAS was performed to confirm separation of clusters on PCs and to generate a dendrogram using average Euclidean distances.Average estimates of genetic differentiation between weedy rice in California rice fields are very low, ranging from 0 to 0.0026 . There are no significant differences in FST estimates for any of the 48 loci. The highest FST estimate was 0.077, betweenCRR1 and CRR4 at STS085. These low values indicate no population structure and no divergence of weedy rice in the fields sampled, which supports the appropriateness of a genetic diversity assessment for California weedy rice . Measures of genetic diversity for California weedy rice within each field as well as for weedy rice within all fields combined are also very low , consistent with a recent founder event, or strong population bottleneck.

These values are a full order of magnitude lower than what was calculated for strawhull and blackhull weedy rice ecotypes collected from the southern US. Due to the lack of population substructure and low genetic diversity, we placed all California weedy rice into one group for the remaining analyses. Values for average population differentiation estimates across all 48 loci indicate high divergence between California weedy rice and all other sampled groups. The lowest mean value is with O. rufipogon collected from Southeast Asia . Taking the median values across the 48 loci allows better understanding of the patterns across all loci. The lowest divergence was between California SHA weedy rice and BHA and SH; median ФST values indicated that for at least half of the loci tested divergence was an order of magnitude lower than the mean estimates . This indicates that the mean ФST is high due to divergence at a few loci, and that California weedy rice does share some similarity to weedy rice from the southern US at several loci. The most recent divergence of California weedy rice from other Oryzasis from California rice cultivars , which was estimated at about 118 generations ago . The other divergence estimates were over an order of magnitude older . Interestingly, both SH and BHA weedy rice from the southern US have very old divergence estimates: approximately 30,000 and 17,000 , respectively. These numbers are likely inflated compared to the reported origin of domesticated rice approximately 10,000 generations ago due to interactions among other closely related genotypes. This follows work examining model testing performance of IMa under several scenarios,which showed that divergence estimates inflate when gene flow from other populations is included in the model. A model of relative divergence times shows a shallow, recent coalescence of California weedy rice and California crop rice alleles, whereas SH and BHA southern US weedy rice and Chinese O. rufipogon show a much older divergence from California weedy rice .

Migration estimates between California weedy rice and all other groups were quite low, with higher estimates of migration into California weedy rice in all cases. Indeed, these data should not be interpreted as absolute numbers but instead as relative values. Any overestimation of the generation values could otherwise indicate that the divergence actually happened even more recently. The effective population size for California weedy rice is very small in all cases,supporting a recent founder event or bottleneck. California weedy rice has a straw-colored hull with long awns , whereas only 7%of SH weedy rice in the southern US has awns. Nevertheless, California weedy rice shares important weedy traits with those of southern US weedy rice including high seed shattering and a red-colored pericarp in addition to tall stature and high tillering habit.Principal components analysis reduced the set of observed variables for California weedy and cultivated rice by loading them on orthogonal lines of fit based on contributions to variance. No variation was observed amongst weedy and cultivated rice for leaf texture and angle, ligule shape, ligule color, ligule pubescence, auricle color, node color, or panicle secondary branching, so these traits were excluded from the analysis. When multiple traits represented the same metric, we chose the variable with the highest eigenvector value to represent each group or suite of highly correlated traits, although each group member or variable has an impact when describing the underlying mechanism responsible for phenotypic selection differences between the cultivar and weedy rice in California. Importantly, pericarp color clearly distinguishes weedy from cultivated rice in California , but is not highlighted in the dimension-reducing PCA because it was scored as a qualitative trait following International Rice Research Institute descriptor guidelines. The remaining phenotypic traits included vegetative growth habit characters, reproductive morphologies, and yield metrics related to grain morphology. Principal components analysis was conducted on these informative traits, excluding highly correlated variables . A second PCA was performed on a reduced dataset, which included the five traits with highest eigenvector values for each principal component in the initial analysis . Principal Components 1 , 2 , and 3 together account for 45.18% of the total cumulative variance in cultivated and weedy rice in the first PCA . Traits most greatly discriminating California weedy from cultivated rice include panicle type, leaf width ,flowering , awn color, and culm length ; lemma pubescence, texture of the panicle axis, length of the first leaf below the flag leaf, length/width ratio of grain, and width of flag leaf ; 100-grain weight of the field-collected mother plant, awn length of the field-collected and offspring plants, spikelet fertility , and grains per panicle described most of the variation along PC3. Becausewe were interested in the contribution of suites of traits describing each statistically significant orthogonal vector, vertical racks the 15 traits contributing most to variance along the first three PCs in PCA 1 were subjected to a second analysis. In PCA 2 of “key discriminating traits,” principal components 1 , 2 , 3 , and 4 account for 74.91% of the cumulative variance in the phenotype of California weedy rice . Since components or dimensions with an eigenvalue greater than one are statistically relevant to the result , we report four principal components for this second PCA.Traits in Californiaweedy rice plants that mimic both medium-grain and gourmet specialty cultivars include erect leaf angles, cleft ligule shape, culm strength , green node color, panicle exertion , and ligule pubescence .

Crop traits in weedy rice specific to co-occurring medium-grain cultivars include basal leaf sheath color and hull color . Crop traits grouping weedy rice with gourmet specialty varieties include intermediate tillering or spreading growth habit . These crop-like traits are presumably carried by the immediate progenitors of the weedy rice, the crop, and have not been lost by the crop. When shared between weedy and cultivated rice, some of these traits could reinforce weed persistence and adaptation to cultivation by visually disguising the weed, thus preventing detection.Wild-like traits in California weedy rice traits exhibit high variance and differentiate this nascent feral population from both medium-grain cultivated varieties M-104, M-202, M-204, and M-205 as well as gourmet varieties in several ways. Compared with medium-grain cultivars, California weedy rice has a purple pericarp, long fully developed awns, lower seed set but with more grains per panicle, open panicles with scabrous texture, more tillers and panicles, spreading growth habit, long culm with gold internodes and delayed and extended flowering period . The medium-grain cultivars in California have brown pericarp; short awns, , high seed set, less tillers and panicles than weedy rice, have compact panicles, are less than 100 cm tall, flower earlier than weedy rice, and have erect culms. Distinct clusters within the California weedy rice population can be resolved by a multivariate analysis of variance . UPGMA cluster analysis confirmed morphogroups based on the key partitioned traits identified through PCA . The number of clusters N was given as three for several clustering methods. More clusters could be resolved amongst the weedy rice, but an additional split did not offer more information when co-occurring rice cultivars were included .Weedy rice in California is a newly established and distinct group in the USA. Isolation with migration modeling suggests that California SHA weedy rice diverged from California rice cultivars approximately 118 generations ago. The relatively recent divergence, distinct morphology, and small genetic relatedness with other US weedy rice indicate that this unique population has evolved separately from a cultivated ancestor. The recent origin of California weedy rice suggests that the population has differentiated since the establishment of rice cultivation in California and is in the early stages of segregating weedy traits, such as more tillers, extended flowering, and pigmented pericarp. Across all loci, we find no haplotypes in California cultivated rice that are not present in other japonicas . Further, there are no additional shared polymorphisms between California weedy rice and other japonicas that are not shared between California weedy and California crop rice. California weedy rice either diverged from japonicas outside of the US and was brought in to California after becoming weedy or diverged from California japonica cultivated in California. The former argument that this weed was brought in is highly unlikely due to strict laws in rice seed import into California. Regardless, California weedy rice is distinct from the other US weedy rices and our coalescent IM estimates point to a recent de-domestication from the California japonica line. Indeed, while the generation values may be inflated , this does not necessarily mean that the estimate is greater than it should be. The relative values are indicative of the relatively recent divergence, which was our objective with this analysis. This result does not demonstrate definitively that time since divergence between California cultivated and weedy rice is different from that between BHA and California weedy rice; however, it is clear that California cultivated rice and California weedy rice have different origins, and more importantly, that the divergence of California weedy rice is more recently from cultivated rice in the same area than that from all other Oryza groups investigated.

As required for layer stacks, the imagery was resampled to a single scale using cubic convolution. The increase in pixel size brought the grain of the images and that of the field evaluations of vegetation composition to a similar scale, and one that was appropriate for the degree of geopositional error in our measurements .To develop and test the classification methods examined in this study, we used ground-truth points that represented locations with known geographic coordinates in patches in which vegetation was nearly pure weeds or forage. These points were extracted according to specific criteria from a broader multi-year database of vegetation points that included points collected both randomly and to represent particular vegetation types or features across a large watershed. The measures at each georeferenced point included cover of key vegetation groups within 1-m radius circle, as well as individual species of interest. Cover estimates were made using Daubenmire classes: < 5%, 5.1–25%, 25.1–50%, 50.1–75%, 75.1– 95% and 95.1–100%. To create and ground truth the image classifications for our study area, we selected all data points from our vegetation database that were in our study area and for which the vegetation composition was strongly dominated either by invasive weedy or by annual grass forage species, as represented by Daubenmire cover classes of 5 or 6, or equivalent, with no other species present in substantial amounts. In effect, weed drying rack these “pure” points represent the purest patches of each vegetation group we could locate and thus provide the clearest characterization of vegetation properties. Such dense near-monospecific patches are also important targets of weed control efforts.

We identified 98 such points for the 2008 analysis , and 119 for 2009 . For each year, each set of “pure” points was then stratified by ranch property and half of the points within each of the three properties were randomly assigned to a single combined training data point set to support initial vegetation classification, or to a similar test set for later evaluation of classification effectiveness. This stratified approach ensured that training and test ground truth sets shared similar geographic distributions.The success of phenological-based mapping depends on the identification of phenological differences in the spectral properties of target vegetation groups. This study was motivated by field observations indicating that the invasive weedy grass species generally remain green a little longer than the forage grasses at the end of the growing season ,although this window of difference can be very short. To characterize and differentiate the weedy grasses’ phenological signature, we compared NDVI values from the imagery at locations of known weed and forage patches in peak spring and at the end of the season in both study years. To test whether the signal from weed-dominated vegetation was distinct, we used repeated measures MANOVA with NDVI values in March and May as the time-repeated response variables with between-subject factors of year, vegetation type, property, and year x vegetation type and within-subject factors of month, month x year, month x vegetation type, month x property, and month x year x vegetation type. In the primary analysis, we compared values using the mid-May image for 2009 , which was most similar to the date of image acquisition in May 2008. However, because weed senescence may occur quickly in May, we also evaluated how NDVI values differed between two dates in May 2009 . Finally, in addition to considering the March and May NDVI characteristics of the vegetation types, we also considered the March—May NDVI differences.

After characterizing the phenological signature of weed-dominated vegetation, the next step was to determine whether a phenological-based approach could perform consistently enough over time to serve as a reliable tool for multi-year detection of weed persistence, expansion or contraction. Our first questions centered on the choice of imagery inputs. Could a single NDVI image provide enough classification power? If so, which month for image acquisition would be best: March , when vegetation is most likely to be green? Or May , when weed-dominated patches are most visible to a field observer? Alternatively, would using two images improve classification accuracy enough to merit the extra costs and processing time? If so, was it most effective to stack the two images and evaluate the two-layer set simultaneously as two bands of a single image? Or rather was it more effective to create a difference image that would highlight the phenological changes in which we were most interested? ΔNDVI contains less information than stacked NDVI , but that information focuses specifically on temporal NDVI changes relevant to a phenology-based analysis. To test these questions, we compared the robustness of classifications that used these four different types of imagery inputs, all used after conversion to NDVI-analogues: March NDVI alone ; May NDVI alone ; a two-layer stack of March and May NDVI, classified together as two bands of a single image ; and ΔNDVI, a single-band difference image made, as previously described, by subtracting May NDVI from March NDVI . With these four types of inputs, we tested both unsupervised and supervised classification methods to delineate vegetation types. For simplicity, all classifications relied solely on NDVI imagery and ground truth data; none utilized additional information . Throughout, the same mask was used to remove water, trees, roads, and structures from the classification.

To conduct a supervised classification on raster data, the operator must provide the software with information necessary to determine the vegetation type represented by each pixel, often by providing georeferenced “training” sites that exemplify the properties of the target vegetation to be identified. We conducted parallelepiped supervised classifications on all image sets using the training set of weed- and forage-dominated “pure” ground truth points previously described . Iterative testing indicated that the most effective classifications were produced when we used a standard deviation of 2.0 for the weed classes and 1.0 for the forage classes, although a small number of pixels fell outside the standard deviation constraints and were unclassified. We conducted additional supervised classifications in ENVI using maximum likelihood classification, which required at least two image layers per analysis; the maximum likelihood classification was thus conducted only with the two-layer stacked NDVI image inputs . Results were not strongly sensitive to threshold choice; we used 70% for consistency with the unsupervised approach . Unsupervised classification. Unsupervised classification is easier than supervised classification for the operator to initiate, as the computer simply generates the specified number of map classes from imagery inputs using one of several algorithms. However, then the operator must determine which, if any, of the computer-generated map classes best represents the target vegetation type. Here we conducted unsupervised isodata classifications in ENVI 4.7 on all image sets. Each classification was run for 40 iterations with a pixel change threshold of 2.0% to create 8 classes, as previously determined in iterative tests to be effective. After the unsupervised classifications were produced, rolling bench we assigned vegetation types to the computer generated map classes by comparing the distribution of the classes to the same training set of “pure” ground truth points used to produce the supervised classifications. A map class was designated as weed-dominated if at least 70% of the “pure” ground truth points falling within its extent were weed-dominated points. All other classes were designated “Non-Weeds,” which included both forage-dominated pixels and heterogeneous weed-forage mixes. In a few cases, unsupervised classification produced a map class that did not contain any ground-truth points, in which case that class was assigned the identity of the majority class surrounding it. Metrics for comparison of classification accuracies. To quantify classification accuracy, we compared the weed maps produced for each combination of imagery and classification approach with the “test” or “validation” set of ground-truth data points that were distinct from the training points used to produce the classification. Following the classic methods of Congalton, we used an error matrix to calculate four metrics, based on the distribution of weed and non-weed class pixels and ground truth points: Overall accuracy and the Kappa statistic describe the general accuracy of a classification. Overall accuracy is the percentage of test points for which map classes and field data agree, across all map classes. The Kappa statistic adjusts overall accuracy to take into account agreement that might occur solely by chance. It is calculated as: /, where Observed = Overall Accuracy. Expected is calculated as the product matrix divided by the cumulative sum of the product matrix . In the Kappa analysis, we used the Z-test to determine if each classification was better than random at α = 0.05. For the Kappa statistic, values above 0.60 indicate good to excellent agreement between the classification and the ground truth data. Producer’s accuracy measures the percentage of a specific target vegetation on the ground that the map properly describes .

It is calculated as the percentage of ground-truth points correctly identified as the target vegetation out of the total set of ground-truth points for that vegetation type. For example, if there are 100 ground-truth points on the ground that represent weed-dominated vegetation and only 80 of them fall within the map’s weed class, then the producer’s accuracy for the weed class in that map is 80% and the map has missed 20% . User’s accuracy describes the purity of a specific map class. For example, if the map says that a particular area is best classified as weed-dominated, how true is this in the field? What percentage of the vegetation in the field area corresponding to the map class “Weeds” is in fact weed-dominated? User’s accuracy for a target vegetation type is calculated as the percentage of all ground-truth points within the field area corresponding to a map class that correctly match the map class type. For example, if within the field area delineated by the map’s weed-dominated class there are 80 ground-truth points representing weed-dominated vegetation, but also 40 ground-truth points representing vegetation dominated by other species or by vegetation mixes, then the user’s accuracy for weed-dominated cover is 80/ or 66.7%. To identify which mapping approaches were most robust to changing environmental conditions, we calculated the accuracy metrics for each classification method x NDVI image input type combination for each of the two years and the two May dates . For each combination, we then calculated the mean and coefficient of variation of the accuracy metrics that resulted from using imagery inputs from these different dates. In our judgement, the best mapping approach would combine high accuracy with strong consistency , which would support its application in study of cover changes over time.After determining which mapping approach had the greatest and most consistent accuracy, we used this approach to compare weed distributions in 2008 and 2009 across the study site. We evaluated the percentages of the landscape that were dominated by weeds in each year and how much gain or loss of weed-dominated area occurred between years. We then analyzed cover distributions by management unit. The study site included four separate management units that represented a serendipitous pre-existing gradient of grazing intensity from west to east. At the time of imagery acquisition, the westernmost management unit was used for turkey hunting and for more than five years had experienced no grazing, except by an occasional animal that broke through a neighboring fence. A second central management unit on a separate property had likewise been set aside for most of the preceding five years, and had only been grazed briefly on a few occasions by a small number of sheep. In contrast, another unit on that same property had been moderately grazed by sheep and cattle on a regular basis; and the eastern unit had been moderately to intensely grazed for more than 8 years by sheep, cattle, and goats, largely with managed intensive rotational grazing. For M3 and M4, the estimated mean stocking rates were 0.4–1.3 animal units ha-1; short term stocking rates in sub-areas of M4 were higher during rotations. As a case study to evaluate application, we used the most effective mapping approach to compare the extent of weed-dominated cover in the largely ungrazed management units with that in the regularly grazed units . While the units we studied were not established with experimental research in mind and replication was limited, each grazing category spanned similar soils and topography and included management units from two different properties. Moreover, the study site offered an opportunity for realistic application: the management units were large and part of independent working ranches managed for diverse commercial purposes.

When dealing with fast maturing crops, the grower can prevent weeds from dispersing seeds . Since weeds adapt to continuous use of the same tools, implementations of other integrated management plans are crucial .Using more than one management strategy increases the probability of weed control success like implementing a form of physical control like hand weeding integrated with herbicides can control weeds . In the produce industry 42% of total weed control expense is due to labor costs . Organic vegetable farmers are extremely limited in the choice of registered herbicides they can use, making it necessary for growers to explore more options to manage weeds . California passed legislation in 2016 that increased the minimum wage by a $1.00/hr. per year until it reaches $15.00/hr. in 2022 . With this change in place, the agricultural industry will face higher labor costs . Costs associated with hand weeding, in general, are between $300-$700 per hectare, which has continued to increase in prices as much as 64% in the last ten years . Because there are few herbicides for lettuce production, hand weeding labor costs will get even higher . Tillage and cultivation Tillage combined with herbicides can be an effective integrated treatment method . Seedbeds that are firequently cultivated will generally have higher weed populations, leading to more weed outbreaks . When dealing with soil that is cloddy the weeds are protected by the clods of dirt and need to be broken down further when prepping a field for crop seeding . Using a mechanical weed cultivator in a high-density spinach field can cause crop injury, cannabis dryer which is why spinach must be hand-weeded . There are drawbacks when it comes to mechanical cultivation . Studies have shown that even the more advanced weeding machines have a hard time removing weeds close to crop plants . 

Intelligent robotic weeders are another method currently being implemented, but these can be challenging to use in high density crops and wet conditions . Even with more advanced machines available, these robotic weeders are expensive and only the larger growers can adapt to the technology and afford high fixed costs while small growers struggle to invest . Some cultivators can only control small weeds, but it is challenging to take out older, deep-rooted weeds in lettuce production . In conclusion, cultural, physical, and chemical control methods cannot be separated and work best when used together in an integrated pest management plan.Organic agriculture is a sustainable production system that considers long-term effects involving preserving biodiversity, soil health, and the environment. There is a growing demand for organic vegetable crops for consumers who don’t want to be exposed to pesticide residues, especially on food for children . While the demand for organic produce continues to increase, it’s challenging to find effective ways to manage soil pathogens and weeds with few good pest control tools. Some challenges include high weeding costs because there are few organic-compliant herbicides, and effective management of soil pathogens is difficult. Research in weed and pathogen management for organic systems is not a high priority for many researchers and does not receive much attention, especially in production dealing with high yielding produce crops in an ever-growing marketplace . There is constant worry about persistent weed infestations in organic agriculture due to many weed escapes . In organic leafy crop production, there is a couple strategies they can use to control persistent weed infestations, one way to reduce surface seed bank is by deep burial.

This method is called plowing, which involves incorporating weed seeds into the ground, which prevents weed seeds from germinating . Plowing can create a problem because it involves burying weed seeds deep into the soil and will eventually be brought back to the soil surface during future field cultivations, so other organic production methods should be incorporated . The timing and depth of cultivation can have an effect on different weeds in a seedbank . Some weeds depend on light in order to germinate and is why weed seeds can be viable for so many years when buried deep into the soil where they are not exposed to light . Farmers have adapted to increased food production using intensive land cultivation during the green revolution and saw how productive and efficient it was to produce crops . Yet, extensive land cultivation can create more problems if not planned accordingly, so farmers learned how efficient it was to grow crops in rotation after harvest as another strategy to control pathogen inoculum and weed seeds in the soil as a common practice in organic production . Some organic practices that are used in lettuce production in coastal areas of California are crop rotations with mustard family species, into their integrated pest management program to help enhance soil fertility in an area of extreme soil disruption . Rotational crops are planned months before planting, and farmers need to have high returns to offset land and high production costs with greater risk of aphids and diseases in organic production .In spinach production, the most common herbicides used are phenmedipham and cycloate . These herbicides control grasses and broad leaf weeds, but they only control 2 out of 5 important weeds . Phenmedipham canbe used at the three true leaf stage of spinach but often cause crop injury for a short period and is labeled for processed spinach in California .

Therefore, growers need to know their weed seed bank to determine what methods would work best in their weed management plan. For preplant fumigation, which involves applying a product such as Metam sodium before the spinach is planted . However, Metam sodium is not preferred because it is restricted and has a 14-day wait before planting . Cycloate is the main preemergent herbicide used after seeding but before emergence and can also be pre-plant incorporated into the soil . In lettuce production, herbicides like Benefin is also used as a preplant herbicide applied with the help of machine incorporation on the tops of lettuce beds . Using this herbicide comes with precautions because it can persist in the soil for months and can affect rotational crops like spinach, onion, corn, and sugar beets . Incorporating the herbicide too deep can result in poor weed control . Bensulide is an important lettuce preemergence herbicide that controls annual grasses but is weak on pigweed . Pronamide is the most common preemergence herbicide for lettuce organically registered in 1969 . The herbicide does not need to be incorporated into the ground . Kerb provides excellent control of grasses and weeds in the mustard family . In addition, Kerb partially controls goosefoot and purslane in the nightshade family, malva and pigweed does not control weeds in the sunflower family like common sowhistle and common groundsel . Many growers have trouble with Kerb, especially in Yuma, Arizona because it leaches too deep in the soil profile when lettuce is irrigated, causing poor weed control . In addition, Kerb is a possible human carcinogen and has been found in groundwater . In today’s herbicide market, herbicides have been regulated and banned, leaving those that are more than 40 years old and subject to cancellation in the future . Cycloate and Dual Magnum are the only pre-application products in the market that can be used in spinach production, but Dual Magnum is not used much . Lati stated Cycloate controls broadleaf weeds well but can be difficult to control weeds in warm conditions due to increased volatility and loss. Growers continue to use herbicides because it benefits them by reducing the number of weeds in the field. Therefore, it requires less labor to hand weed in leafy crop production. Dual Magnum, an herbicide that was registered in 1977 and has a pre harvest interval timing of 50 days and is too long because spinach can be harvested in as little as 25 days . In addition, Fennimore argues that weeds like purslane can be problematic and thrive under heavily cultivated soils and in Salinas Valley’s Mediterranean climate. When herbicides like Pronamide and Bensulide were introduced in the late 1960s, there was an improvement in control . However, cannabis growing systems growers continue to have problems where reoccurring purslane infestations are persistent . Developing a new herbicide can be very difficult and expensive. The process takes 9 years and involves studying the environmental impacts of the chemical and proper development and rigorous field trials before it can be registered to be used. Sometimes chemicals going through this process do not make it successfully. Other alternatives to control weeds include using biotechnology to make herbicide-tolerant lettuce. Fennimore found that using glyphosate tolerance lettuce could control weeds better than Bensulide and Pronamide. In general, it can becostly to take this type of biotechnology to a commercial scale, but the lettuce industry soundly rejected roundup ready lettuce before it was introduced.Steam application to the soil is a method to disinfest soils by killing pathogens and weed seed in the soil. The concept of heating the soil started in greenhouse flower production dating back to the 1800s and even as far as ancient times .

Steam disinfestation first came into use in the United States in 1893 to treat greenhouse pots and eventually, as technology started evolving, different types of machine steamers were created . For example, mobile steamers come in tractor-towed or self-propelled models. Several different types of steaming techniques have been developed and evaluated in terms of costs and pathogen and weed suppression . The average cost of steaming was $4,883.24 an acre compared to the cost to use chemicals like methyl bromide or 1,3 chloropicrin application that would cost $7,324.86 per acre . Extensive research on the efficacy of steam opened new opportunities for improved steaming techniques in greenhouse production . Steam was used widely in the 1950s and 1960s, but in the 1970s, high fuel costs made steam more expensive than fumigants and so greenhouses switched to fumigants like hot gas methyl bromide . With increased chemical use regulations in greenhouse and field settings and the loss of methyl bromide, growers have renewed interest in steam. Chemical fumigants came into use in the 1960s when farmers soon found fumigants to be a cheaper and more efficient way of killing weeds and soil pests than steam . However today, it is difficult and expensive to use chemical fumigants in California agriculture due to strict regulation. Steam on the other hand, provides an alternative and is not regulated. Many argue steam is a viable alternative to methyl bromide, but better steam application methods and applicators are needed . One concern about using steam disinfestation is overheating the soil, killing beneficial microbes key in soil nitrification . Wherever steam is used, steam needs to reach a temperature of 60-70 °C for 20-30 mins dwell time to control soil pathogens and weeds effectively . Because romaine lettuce and spinach are shallow-rooted crops grown in rows, the depth of steam injection application using a banded steam technique is set to 19 cm or shallower in depth .Studies done by Baker and Van Loenen et al., evaluated the effects of various temperatures and exposure times on soil pathogens by soil type using dry steam. Dry steam is created by generating steam with one pass through the boiler followed by a second pass so that the temperature is higher and there are no water droplets . Baker found that when steaming soil in pots that were dry at a lower temperature, it took longer to reach the appropriate temperature to kill soil pathogens. In contrast, Baker also observed that when potted containers were moist just before steam application and steamed at a higher lethal temperature dose for 30 mins he observed higher kill rates of soil pathogens.Sheet steaming is one of the oldest methods of steam application and is still used in greenhouse production . The downfall of this technique is that the steam process takes 8 hours, and the performance of steam is better in clay soils, according to a study done in Italy by Gay et al. . To heat the deeper layers of the soil takes long to reach the appropriate temperature to kill soil pathogens but gave the best results in steaming the top 15 cm of the soil . Sandy soils were the most challenging soil type to steam with this method .

The effect of depth on 1,3,-D concentration was most evident in water seals and bare soil plots. HDPE and VIF plots had more uniform distribution of the fumigant through the soil profile than the water seals plots, especially 48 hours after treatment. However, 1,3-D concentration under the VIF tarp was markedly higher than in all other treatments, which suggests that there could also be differences in the top 5 centimeters of soil. These results imply that the use of a highly impermeable tarp can lead to a more uniform distribution of fumigants in the soil profile and may allow satisfactory pest control with reduced application rates . Soilborne pest control. Pest control data from the 2007 KAC emissions trial and a related 2008 emissions trial were reported previously and are not shown here. In general, however, there were few differences in pest control attributed to the fumigant application shanks used in the trial. Pythium species populations were lower in all treatments than in the untreated control, but no statistical differences were noted in Fusarium species populations among treatments. The high 1,3-D rates and well-prepared soils resulted in complete control of citrus nematodes in the bioassay bags in all treatments and depths. Weed populations were variable among treatments but tended to be lowest in methyl bromide plots and 1,3-D plots sealed with VIF and highest in the water seals and dual 1,3-D application Treatments.Nematodes and soilborne pathogens. All treatments of 1,3-D or methyl bromide effectively controlled citrus nematodes in bio-assay bags buried at 12-, 24- and 36-inch depths in each plot. However, these results, ebb and flow system which were obtained in well-prepared sandy soils with low pest and pathogen populations, may not apply to more challenging field conditions .

Applications of 1,3-D sealed with HDPE or VIF and dual application 1,3-D treatments reduced Fusarium and Pythium species propagules in the soil compared with the untreated plots . These treatments were comparable to methyl bromide in controlling Fusarium and Pythium species. Soil pathogen control with 1,3-D followed by metam sodium and 1,3-D with intermittent water seals was inconsistent between the two experiments, which suggests that specific micro- and macro-level differences in environmental and field conditions may contribute to greater treatment variability and risk to growers. Weed density. When 1,3-D was sealed with HDPE and VIF, broad leaf weed density was reduced to less than 6 weeds per square meter, which was comparable to methyl bromide . These results are similar to a previous nursery study that indicated 1,3-D or 1,3-D plus chloropicrin sealed with HDPE or VIF resulted in weed seed viability and hand-weeding time comparable to methyl bromide . Generally, intermittent water seals after a 1,3-D application resulted in broad leaf weed density similar to the untreated control. Most weeds germinate near the soil surface, thus techniques such as intermittent water seals that limit upward fumigant movement into surface soils can adversely affect weed control. The other surface treatments 1,3-D dual application and 1,3-D followed by metam sodium had intermediate broad leaf weed densities compared to untreated plots and methyl bromide. All fumigation treatments reduced grass weed populations compared to the control plots; however, the greatest reductions were observed in plots treated with methyl bromide, 1,3-D sealed with HDPE or VIF, and 1,3-D followed by metam sodium. It was clear in this study that effective surface treatments can greatly increase weed control with 1,3-D; however, even the best treatments will likely require supplemental weed control to meet grower expectations. Stock vigor and performance. Effects of surface seal treatments and 1,3-D soil fumigation on nursery stock vigor and performance in two nursery trials were evaluated in 2007 to 2010 . In the rose nursery trial, all treatments had similar rootstock vigor and number of marketable plants except when 1,3-D was followed by metam sodium.

During the 2008 growing season, roses grown in plots treated with 1,3-D followed by metam sodium had lower vigor than the other treatments; however, by harvest at the end of the second year, no differences in marketable plants were observed. In the tree nursery trial, tree rootstock vigor was reduced in plots treated with 1,3-D followed by metam sodium and1,3-D with intermittent water seals compared with the other fumigation treatments, but rootstock caliper at the end of the first growing season did not differ among treatments.Compared with some other fumigation-dependent industries, perennial fruit and nut nursery stock production systems face a more difficult transition to methyl bromide alternatives . Despite several years of research, the following significant challenges to widespread adoption of alternatives in the perennial crop nursery industry remain: National and international market expectations for nematode-firee nursery stock limit nursery stock producers to alternatives with very high nematode efficacy at significant depths in the soil. To meet California nursery certification requirements, producers are required to use approved fumigant treatments or conduct a post production inspection. A failed inspection may result in an essentially nonsalable crop. Most alternative treatment schedules are based on the use of 1,3-D , a fumigant that faces its own serious and evolving regulatory issues in California. No currently available alternative fumigant can be used in California to meet certification requirements in nurseries with fine-textured soil at registered rates. Methyl iodide, the alternative fumigant with performance most similar to methyl bromide, is not currently registered in the United States due to a voluntary withdrawal by the manufacturer. Concerns over control of weeds and fungal and bacterial pathogens in the short and long term may further limit adoption of alternatives with a narrower pest control spectrum. Containerized nursery stock production systems are being used in some parts of the industry, but the production costs, market acceptance and long-term viability of this system have not been addressed at the required scale. Adoption of methyl bromide alternatives, where they exist, in the perennial crop nursery industry will ultimately be driven by state and federal regulations and economics. Although it’s heavily regulated, 1,3-D is a viable alternative for growers with coarse-textured soil, but if 1,3-D becomes more difficult to use due to shortages or increasingly stringent regulations, it may be only a short-term solution. No viable fumigant alternatives exist for California nurseries with fine-textured soil, and some of them may be unable to produce certified nursery stock in the absence of methyl bromide. The cost of producing perennial nursery stock using more expensive, laborious or economically risky production methods will ultimately be passed on to customers and could have long-term impacts on the nursery, orchard, vineyard and ornamental industries.Weedy plants can be tolerant of herbicides due to a variety of temporal, spatial, or physiological mechanisms. For instance, a weed may avoid control efforts if it emerges after a burn down herbicide is applied or completes its lifecycle before a postemergence herbicide is applied. Similarly, large-seeded or perennial weeds can emerge from deeper in the soil and may avoid germinating in soil treated with a preemergenceherbicide. Other weedy species have physiological mechanisms of tolerance and avoid control through reduced herbicide uptake or translocation, rapid detoxification, or insensitive target sites. Regardless of the mechanism of tolerance, repeated use of an herbicide can lead to weed shifts in which weed populations become dominated by species that are not affected by the weed control measures used. A classic example of a weed shift in response to herbicides is the change from primarily broad leaf weeds to grass weeds in cereal production after the introduction of the broad leaf herbicide 2,4-D. Weed shifts can also occur following overuse of non-chemical weed control techniques, such as flame weeding or mowing, flood and drain hydroponics that tend to favor populations of grass weeds.Herbicide resistance in weeds is an evolutionary process and is due in large part to selection with repeated use of the same herbicide or products with the same mode of action. Herbicides do not cause resistance; instead, they select for naturally occurring resistance traits. On a population level, organisms occasionally have slight natural mutations in their genetics; some of these are lethal to the individual, some are beneficial, and some are neutral. Occasionally, one of these chance mutations affects the target site of an herbicide such that the herbicide does not affect the new bio-type. Similarly, mutations can affect other plant processes in a way that reduces the plant’s exposure to the herbicide due to reduced uptake or translocation or through more rapid detoxification.

Whatever the cause, under continued selection pressure with the herbicide, resistant plants are not controlled and their progeny can build up in the population . Depending on the initial firequency of the resistance gene in the population, the reproductive ability of the weed, and the competition, it may take several generations until the resistance problem becomes apparent.Two general types of mechanisms confer resistance to herbicides in weeds. Some mechanisms are related to the specific site of action of the herbicide in the plant, and others involve processes not related to the mechanism by which herbicides kill plants; these two types are known as target-site and non-target-site mechanisms, respectively. A certain weed bio-type may be resistant to more than one herbicide. Herbicide cross-resistance occurs when an individual plant is resistant to two different herbicides via the same mechanism of resistance. In this case, resistance is endowed by a single physiological process operating in common for all the herbicides involved. Multiple resistance results from selection by the simultaneous or sequential use of different herbicides, such that resistance to each herbicide is endowed by a different mechanism.Herbicides usually affect plants by disrupting the activity of a specific protein that plays a key role in plant biochemical process. Target-site resistance occurs when the target enzyme becomes less sensitive or insensitive to the herbicide. The loss of sensitivity is usually associated with a mutation in the gene coding for the protein and can lead to conformational changes in the protein’s structure. These physical changes can impair the ability of one or more herbicides to attach to the specific binding site on the enzyme, thus reducing or eliminating herbicidal activity. Although changes in protein structure occasionally result in reduced biological functionality of the enzyme and a related “fitness cost” , many target-site mutations do not have an observable fitness cost. Certain herbicide groups are particularly vulnerable to developing target-site resistance, because resistance can be endowed by several mutations, thus increasing the probability of finding resistant mutants in weed populations— even in those not previously exposed to that herbicide group. For example, specific mutations resulting in seven different amino acid substitutions in the acetolactate synthase gene are known to confer resistance to ALS-inhibiting herbicides in weed bio-types selected under field conditions. Something similar occurs with the grass herbicides that inhibit the enzyme acetyl coenzyme A carboxylase . In these cases, at least five point mutations are associated with cross-resistance patterns. These can be observed at the whole plant level and involve four classes of ACCase-inhibiting herbicides. The existence of so many mutations conferring resistance is the reason that resistance to these herbicides is firequently found and can evolve rapidly. Several mechanisms confer resistance to herbicides without involving the active site of the herbicide in the plant. Of these, the best known is the case of metabolic resistance due to an enhanced ability to metabolically degrade the herbicide. Non-target-site herbicide resistance has been well demonstrated for several gene families associated with cytochrome P450 monoxidases, glutathione transferases, and glycosyltransferases. Most of these non-target site resistance mechanisms are also present in cultivated plants and are the reason that many herbicides can be used selectively without injuring crops. Non-target-site resistance can evolve from the intensive use of diverse and unrelated selective herbicides that are similarly effective on a certain weed species and share a detoxification pathway or a mechanism precluding their accumulation at the target site that is relatively common in plants. The management of non-targetsite herbicide resistance often represents a greater challenge than management of target-site resistance, because a simple change in herbicide mode of action may not alleviate the problem. Reduced herbicide absorption or translocation can contribute to resistance in certain bio-types. These have generally been accessory mechanisms that contribute toward resistance in addition to major resistance mechanisms. However, recent evidence suggests that changes in absorption or translocation contribute importantly to glyphosate resistance in several weed bio-types.

If growers are to adopt alternative irrigation systems, understanding potential shifts in weed species’ composition will be critical to weed management. It is well documented that weed community composition can affect yields. The critical period of watergrass competition for rice in California is the first 30 d after planting, and yields can be reduced by as much as 59% when watergrass is uncontrolled . However, critical periods of competition for other weed species are not known, and differences in composition between early- and late-season weed communities and the impacts of late-season competition on rice yields remain to be seen. Using two alternative irrigation systems adapted for California rice, the primary objectives of this research were: to determine weed community composition in rice under different irrigation systems; to determine whether there are differences between early and late weed communities within a system; and to quantify differences in yields between irrigation systems in both the presence and absence of weed competition.Field preparation was standard for the California rice growing region and consisted of chiseling twice, followed by disking twice, to prepare a level seedbed . In the water-seeded alternate wet and dry and water-seeded control conditions, fertilizer was banded in by drill in strips before seeding. Fertilizer applications in the drill-seeded alternate wet and dry treatment were broadcast approximately 1 mo after planting . In all years, ebb flow tray nitrogen was applied at a rate of 171 kg ha−1 . Drilled nitrogen was applied as urea , and broadcast N was applied as ammonium sulfate .

Phosphorous was applied as triple superphosphate at a rate of 86 kg ha−1 in 2012 and at a rate of 45 kg ha−1 in 2013 and 2014. Potassium was applied as potassium chloride at a rate of 25 kg ha−1 in 2013 and 2014 only. The WS-AWD and WS-Control fields were broadcast seeded onto dry soil at a seeding rate of 168 kg ha−1 . The DS-AWD field was seeded to a depth of 2 cm at a rate of 112 kg ha−1 into dry soil. Rice seed for all treatments was pretreated with a 1 h soak in 2.5% NaClO solution to prevent infection with Bakanae disease [Gibberella fujikuroi Wollenw.]. Plots in all irrigation treatments across all years were seeded with M-206, a Calrose medium-grain rice variety widely grown in the region. The three main plot irrigation treatments were the DS-AWD, WS-AWD, and WS-Control. The DS-AWD treatment was initially flush irrigated for rice emergence and then flush irrigated once more when soil volumetric water content reached 35% .Immediately after the N fertilizer application at approximately 1 mo after planting, the DS-AWD was flooded to 10 cm above the soil surface, and water was held at that level to allow for N uptake. The WS-AWD and WS-Control plots were flooded to 10 cm above the soil surface within 24 h of broadcast seeding. The WS-AWD plot remained flooded until canopy closure of the rice, at which point water flowing into the system was shut off, and the standing water was allowed to recede into the soil. Canopy closure of the rice was determined to be when photosynthetic photon flux density reached or fell below 800 μmol m−2 s −1 , which is approximately where subcanopy PPFD stabilized. PPFD was measured every other day using a line quantum sensor at 15.2 cm above the soil surface, which was below the rice canopy.

Canopy closure was determined to be at 47, 49, and 54 d after seeding in 2012, 2013, and 2014, respectively. After being drained at canopy closure, both the WS-AWD and the DS-AWD treatment plots were flush irrigated again when soil VWC reached 35% . The WS-Control plot remained flooded until 1 mo before harvest, when it was drained to allow harvesting equipment onto the field . Soil VWC for irrigation purposes was measured at hourly intervals in each plot using EM5B data loggers and 10HS soil moisture sensors . The 35% VWC was determined using the average of the three replicates for each treatment. Further management details can be found in LaHue et al. .In 2012 there were only minor differences between irrigation systems in the weed counts taken at 20, 40, and 60 DAS. There were no significant differences in population densities of watergrass species, small flower umbrella sedge, and rice field bulrush between irrigation systems across all counts. Our results confirm previous research that showed watergrass plasticity and ability to germinate and emerge under both aerobic and anaerobic soil environments . There were three weed species with differences among irrigation treatments: redstem, ducksalad, and sprangletop. For redstem, there was an interaction between irrigation systems and count timing . Redstem was not present in any system at 20 DAS, but at both 40 and 60 DAS, the redstem density was greater in the WS-AWD than in the other two irrigation systems . Density was greater in the WS-Control system than in the DS-AWD system. The high redstem population in the water-seeded systems is consistent with earlier research showing redstem emergence under water-seeded but not under dry-seeded systems . Ducksalad density was greatest in the WS-Control and WS-AWD systems, irrespective of count timing . Sprangletop density was greatest in the DS-AWD system across all counts , though the difference was only significantly greater than the density in the WS-AWD system. These results are not surprising, since sprangletop emergence is reported to occur only under aerobic conditions in California .

Since it emerged in both the WS-AWD and WS-Control systems, further investigation of the species is warranted to elucidate whether water depth may affect emergence under flooded conditions, allowing the species to emerge under a shallow flood. Both species of sprangletop found in California, bearded sprangletop and Mexican sprangletop [Leptochloa fusca Kunth ssp. uninervia N. Snow], emerged from rice flooded to depths of 5 cm in Valencia, Spain . In Turkey, bearded sprangletop emerges at greater numbers and at a faster rate under flooded conditions than under dry conditions . Differences between weed counts at 20, 40, and 60 DAS indicate that certain species are emerging at different timings throughout the rice-growing season. Redstem did not emerge until 40 DAS across all irrigation systems. Sprangletop emerged by 20 DAS in the DS-AWD system, but did not emerge in the two water-seeded systems until 40 DAS. All other weed species emerged in significant numbers by 20 DAS, and then plant density was reduced by 40 and 60 DAS, presumably through competition for light as the canopy closed . RC and RDW. There were no significant interactions between irrigation system and years for either RC at canopy closure or RDW at harvest for all weed species and rice; therefore, only main effects are presented . RC of small flower umbrella sedge, flood drain tray watergrass species, and ricefield bulrush increased across systems from 2013 to 2014 , though the increase in rice field bulrush was not highly significant . The RC of rice also increased across all systems from 2013 to 2014. This increase may be due to the decrease in RC of ducksalad in 2014, since all other weed species increased in RC in 2014. In water-seeded Arkansas rice, ducksalad decreased yields by about 21% when germinating with rice . The decrease in RC of ducksalad in 2014 may be due to competition with other weed species, particularly watergrass, which had the greatest increase in RC of all weed species. There was a negative correlation between watergrass RC and ducksalad RC in 2013, but the relationship did not hold in 2014 . Thus, it is difficult to say with certainty why ducksalad cover decreased in 2014. Redstem and sprangletop RC were the same across years. At canopy closure the WS-Control and WS-AWD were dominated primarily by ducksalad and watergrass species, but both sedges were also present in small quantities . Sprangletop and redstem were present, but differences between systems were not significant . The only difference in weed composition between the two water-seeded systems at canopy closure was in the small flower umbrella sedge cover, which was significantly greater in the WS-AWD compared with the WS-Control. The weed species composition of the DS-AWD at canopy closure was significantly different from the composition of the water-seeded systems. It was dominated by watergrass species, and the only other species present was sprangletop . RDW of all weed species did not vary across years. There were only two species that were significantly different across irrigation systems: small flower umbrella sedge and watergrass species .

The RDW of small flower umbrella sedge was greatest in the WS-AWD, which was consistent with its RC at canopy closure. Ducksalad was not present at harvest, presumably because it had completed its life cycle and decomposed, although no information on longevity of this species is recorded in the literature. In Arkansas wet-seeded rice, Smith found that ducksalad matured by approximately 8 wk after seeding. In the DS-AWD system at harvest, the RDW of rice was 3% . In comparison, the WS-Control and WS-AWD systems had rice RDW measures of 72 and 77%, respectively. The differences in firequencies of weed species in the DS-AWD and the water-seeded systems corresponded to the differences in RC and RDW . Frequency of small flower umbrella sedge varied between WS-AWD and WSControl . The percentage contribution of small flower umbrella sedge to the dissimilarity between the irrigation systems was the greatest of all weed species at every measurement point, except at canopy closure assessment in 2013. Analysis of the two systems over time showed that although the firequency of small flower umbrella sedge was similar in the WS-AWD and WS-Control at canopy closure in 2013, the firequency of the species was consistently greater in the WS-AWD at all other assessment points . Small flower umbrella sedge cover was greatest in the WS-AWD treatment , and the relativecover of small flower increased in 2014 over 2013 . The relative dry weight of small flower umbrella sedge was greater in the WS-AWD than in the other treatments in both 2013 and 2014. Both the initial germinable seedbank assessment in 2012 and the plant density counts at 20 DAS in 2012 indicate similar germinable populations of small flower umbrella sedge in the WS-Control and WS-AWD irrigation systems. The increased density in the WS-AWD system at 40 and 60 DAS and the increased cover and biomass in both 2013 and 2014 may indicate that the drain at canopy closure affects small flower umbrella sedge germination or competitive ability. Small flower umbrella sedge germination is best under flooded conditions, though it appears to germinate well under saturated soil conditions as well . Preliminary evidence suggests that small flower umbrella sedge has a biphasic emergence pattern , and the relative growth rate of plants emerging under the second germination flush may be greater under the drier conditions of the WS-AWD. The irrigation system was shut off and the water was allowed to recede into the soil beginning at 47 DAS in the WS-AWD system in 2012. In 2013 and 2014 this occurred at 49 DAS and 54 DAS, respectively. Weed density counts were taken 1 wk before the irrigation shutoff in 2012, and weed relative cover ratings were taken 1 d before irrigation shutoff in both 2013 and 2014. Thus, it is possible that the increase in small flower umbrella sedge in the WS-AWD system may be unrelated to the irrigation system and was an artifact of greater population density in 2012. This could be related to the lower ducksalad density in the WS-AWD system that same year. Ducksalad may have a suppressive effect on small flower umbrella sedge, given that it quickly covers the canopy, blocking out light, which small flower umbrella sedge requires for germination . The two weeds had a similar density at the beginning of the experiment but small flower increased as the experiment continued .Rice relative cover increased from 2013 to 2014 over all treatments, yet the increase in 2014 at canopy closure did not correlate with an increase in rice biomass at harvest in 2014. This response confirms earlier research in California that showed competition with late watergrass after the critical period of competition further decreased rice yields . It is significant to note that despite statistically similar initial populations of watergrass species in all fields , rice cover and biomass were lowest in the DS-AWD compared with the water-seeded treatments, either indicating that the watergrass species are more competitive against rice under anaerobic conditions or confirming that rice is less competitive with weeds under anaerobic environments .