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6 results for “hairy vetch”
Climatic and agronomic factors affecting seed yield of hairy vetch (Vicia villosa Roth) in a temperate agroecosystem
<p>Crop management, soil, climatic and crop growing traits on hairy vetch (Vicia villosa Roth) seed yield in temperate agroecosystem</p>
Field data of seed dormancy and pod dehiscence in Hairy Vetch (V. villosa)
<p>Hairy vetch (Vicia villosa Roth), a winter hardy annual legume, is a promising cover crop. To fully leverage its potential, seed production and field performance of V. villosa must be improved to facilitate producer adoption. Two classic domestication traits, seed dormancy (hard seed) and dehiscence (pod shatter), are selection targets in an ongoing breeding program. This study reports a genome-wide association study of 1,019 V. villosa individuals evaluated at two sites (Knox City, Texas and Corvallis, Oregon) for proportion of dormant seed, visual pod dehiscence scores, and two dehiscence surrogate measures (force to dehiscence and pod spiraling score).Trait performance varied between sites, but reliability (equivalent to heritability) across sites was strong (dormant seed proportion: 0.68; dehiscence score: 0.61; spiraling score: 0.42; force to dehiscence: 0.41). A major locus controlling seed dormancy was found (q-value: 1.29 x 10 -5 ; Chromosome 1: Position: 63611165), which can be used by breeding programs to rapidly reduce dormancy in breeding populations. No significant dehiscence score QTL were found, primarily due to the high dehiscence rates in Corvallis, Oregon. Since Oregon is a potentially major V. villosa seed production region, further dehiscence resistance screening is necessary.</p>
Field data of seed dormancy and pod dehiscence in Hairy Vetch (V. villosa)
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Data from: LiDAR and RGB-image analysis to predict hairy vetch biomass in breeding nurseries
Hairy vetch is a fall seeded annual legume that can be used as a forage and cover crop. As a cover crop, it can provide numerous ecosystem services, such as soil erosion reduction, carbon sequestration, and pollinator habitat, but also agronomic services such as weed suppression and N fixation via soil rhizobium species. To improve cover crop function, traits such as biomass production are especially relevant, making it a first priority trait for cover crop breeders. However, direct phenotypic methods for biomass production are destructive. Breeders have thus relied on subjective, visual scoring methods for biomass, which are generally correlative, but are not quantitative or absolute. In this study, we evaluated two low-cost remote sensing tools, LiDAR and RGB-image analysis, for their effectiveness at predicting biomass in vivo. We evaluated these tools in two common forage breeding scenarios, spaced-plant and sward-plot nurseries, at three Minnesota locations following the winter of 2016/2017. Ground cover, determined from RGB image binarization using the Canopeo application, had a significant and linear relationship with above-ground biomass in spaced-plants (R2=0.93), and sward-plots (R2=0.89). Once the image area became saturated with vegetative pixels, a near-exponential relationship with biomass would occur. Because of the low-growth habit of hairy vetch, RGB image analysis was more appropriate at lower plant densities, such as spaced-plant nurseries. LiDAR measures of sward-plot height were also linearly and strongly related to dry-matter biomass in sward-plots (R2=0.80). The dimensionality of LiDAR sensing gave it greater predictive ability at higher plant densities, where RGB analysis could not detect vertical increases in biomass production. Lastly, we combined RGB and LiDAR data to predict sward-plot biomass in a multiple mixed-effect regression model. By doing so, we were able to explain more biomass variation than with use of either phenotypic tool as a single predictor (R2=0.94).
Data from: LiDAR and RGB-image analysis to predict hairy vetch biomass in breeding nurseries
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Hairy Vetch–Based Green Manure Improves Yield and Grain Appearance Quality in High-Yielding Japanese Rice Cultivars with Lodging Resistance Conferred by Functionally Weak GA20ox alleles
GEO Series GSE313855. Oryza sativa. 14 samples. Type: Expression profiling by high throughput sequencing.
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