Abstract Estimating the botanical composition in mixed pastures is challenging due to resource‐intensive sampling methods overlooking grassland spatial variability. We aimed to (I) classify bahiagrass ( Paspalum notatum Flügge) and rhizoma peanut ( Arachis glabrata Benth.) in grass–legume pastures using aerial multispectral imagery and machine learning, (II) estimate the proportion of grass and legumes on an area basis, and (III) estimate the botanical composition on a dry matter basis to guide grazing management. Unmanned aerial vehicle‐based images were taken in the early and late warm seasons of 2023 and 2024. Field campaigns were conducted for ground‐truth species labeling ( n = 554) across nine paddocks under three treatments (fertilized grass, unfertilized grass, and grass–legume mixed) using a high‐precision positioning system. Ninety‐six points were harvested and manually sorted for ground truth botanical composition estimation on a dry matter basis. The classification dataset was split into training and testing using three different approaches to assess spatial generalization performance. A random forest (RF) was employed as the base model, and a convolutional neural network (CNN) was developed using fivefold cross‐validation on the training set. Our CNN model outperformed the RF model, achieving an average cross‐validated overall accuracy of 93% and 88% for grass–legume classification on the grid‐based and repeated spatial hold‐out testing set. Combining land cover classification, compressed height, and vegetation indices showed promising potential to predict total biomass ( R 2 = 0.85) and grass biomass ( R 2 = 0.83) in bahiagrass–rhizoma peanut pastures using stepwise multiple linear regression. This approach also enabled the estimation of legume proportion by difference.

Abstract Lentil ( Lens culinaris Medikus) is a nutrient‐rich, cool‐season legume crop grown in many regions worldwide. In the United States, lentil has yet to be adapted to southeastern (SE) regions, where it can be grown as a winter crop. The objective of this research was to identify candidate lentil genotypes for adaptation to organic production in the SE United States, with emphasis on low disease severity and the ability to compete with weeds. To achieve this, 238 lentil genotypes were grown at two locations in South Carolina for 3 years using an alpha‐lattice design, followed by quantification of disease severity, plant height, canopy cover, days to flower (DTF), days to maturity (DTM), and lodging. Mixed model analysis of variance indicated significant differences among genotypes and genotype × environment for all six traits, but differences among environments were more nuanced. Broad‐sense heritability estimates were high for plant height, DTF, and DTM, but were moderate for disease and canopy cover, and low for lodging. Hierarchical cluster analysis of all traits × environments revealed two clusters of 29 lentil genotypes with low disease severity, high plant height and canopy, and low lodging. Further screening these clusters using threshold values for four traits (disease severity < 50%, plant height > 25 cm, canopy cover > 15%, and lodging < 35%) identified 10 lentil genotypes best suited for organic production. Further research is required to test these genotypes across multiple environments to better understand how they respond to the unique combination of abiotic and biotic conditions.

Abstract Objectively selecting genotypes using genomic predictions for multiple traits warrants more empirical research. This study investigated how deployment of genomic prediction within the Clemson sorghum [ Sorghum bicolor (L.) Moench] breeding program would help to develop hybrids adapted to the eastern United States. Note that 9 years (2016–2024) of data collected on 1790 F 1 hybrids for grain yield, anthracnose resistance, days to anthesis, plant height, and test weight were used to calculate best linear unbiased estimates. Hybrid phenotypic data, in conjunction with genotype data for 1835 parents (983 R‐lines and 852 B‐lines), were used to train and test genomic prediction models. A model with general combining ability (GCA) effects only and a second with GCA and specific combining ability effects were used to estimate the breeding value of new parents and specific hybrid combinations, respectively. Prediction accuracy ( r ) using three cross‐validation strategies found that mean accuracies were high for plant height and moderate for grain yield, anthracnose resistance, days to anthesis, and test weight. An independent culling method using genomic prediction values for plant height and anthracnose was implemented to retroactively select seed and pollinator parents for testcrossing and specific hybrid combinations of superior seed and pollinator parents. Genomic selection of new F 4:5 parents resulted in approximately half of the total families within each fertility pool having one or more progeny advance to testcrossing, thereby avoiding overrepresentation of just a few pedigrees at the testcross phenotyping stage. Meanwhile, removing hybrids predicted above a height threshold and with an unacceptable level of anthracnose resistance led to 514 retained hybrids that had a significantly higher observed grain yield than the mean yield of 381 discarded hybrids. This tandem genomic selection scheme can advance the regional adaptation of individual fertility pools to support sorghum hybrid development for the eastern United States.

Abstract Forage legumes provide a wide range of ecosystem services to grasslands. Improving legume proportion and species diversity of meadow fescue [ Lolium pratense (Huds.) Darbysh] pasture‐based systems can increase the sustainability of a given farming system. This study compared no‐till or frost‐seeding methods to incorporate clovers ( Trifolium spp.) or chicory ( Cichorium intybus L.) into an established meadow fescue sward as pasture‐improvement strategies. No‐till planting occurred in the fall or spring of 2022 and 2023, and frost seeding occurred during the winter of each year. In addition, this study aimed to quantify biological N 2 fixation (BNF) from the interseeded clovers. Chicory failed to establish in both years of the study, comprising less than 2% of the botanical composition. While no‐till planting in the fall or spring, or frost seeding during the winter were successful at establishing clovers, frost seeding may be a more attractive method provided that it may be more economical, requiring less specialized equipment. No‐till interseeding in the fall or spring are also adequate strategies. Overall, red clover ( Trifolium pratense L.) was more productive than white clover ( Trifolium repens L.) in the first year after planting. Further evaluations into persistence after the first year of clover planting are warranted. As a whole, interseeding clovers into meadow fescue pastures is indeed valuable for improving pasture systems by increasing forage accumulation and fixing up to 20 kg N ha −1 year −1 .

Abstract Climate change caused by fossil fuels has driven the search for bioenergy sources. Elephantgrass [ Cenchrus purpureus (Schumach.) Morrone] biomass is a promising alternative for diversifying the energy matrix. One of the main steps of a genetic breeding program is the selection of parents who will form the crossing block, and the use of diallel analysis is critical in this step. Therefore, this study aimed to use mixed linear models to analyze diallel crosses and estimate the general combining ability (GCA) and specific combining ability (SCA) of elephantgrass clones to select superior parents and hybrids for bioenergetic applications. Eleven parents were crossed in a diallel scheme, totaling 55 hybrid combinations, and evaluated in a randomized complete block design with three replications. The measured traits were dry biomass production (DBP), in vitro dry matter digestibility (IVDMD), and cellulose‐lignin (C:L) ratio. There was a significant effect of SCA, SCA × cut interaction, and permanent effect on DBP, and a significant effect of GCA on IVDMD and C:L. There was a predominance of genes with additive effects controlling IVDMD and C:L traits, and dominance and epistasis for DBP. The parents selected for biochemical conversion processes were Embrapa's Active Germplasm Bank of Elephantgrass (BAGCE) 38 and CNPGL 92‐38‐2. The parents selected for direct combustion of biomass were BRS Canará, BRS Capiaçu, and CNPGL 96‐27‐3. The hybrids BAGCE 21 × BAGCE 38, BAGCE 30 × CNPGL‐92‐38‐2, and BAGCE 38 × BRS Kurumi show potential for the production of dry biomass.

Abstract Worldwide production of field peas ( Pisum sativum L.) with food‐quality grain has historically come primarily from spring‐adapted varieties, though novel winter‐adapted varieties have recently been released that exceed spring pea yield potential in many environments. Research analyzing yield, yield components, crop growth, and phenology of the novel germplasm in conjunction with environmental variables is lacking, which is needed to guide ongoing variety and management practice improvement. A comparison of the grain yield of the novel peas to wheat ( Triticum aestivum L.) is also needed to provide context for crop rotation management. The objectives of this research were to provide such analyses through a multi‐environment trial, comparing two food‐grade peas (MiCa and Klondike) to Austrian winter pea (AWP) and wheat. The food‐quality peas and AWP were similar overall in biomass production and most yield traits, with the most distinctive differences being the small seed size of AWP and greatly improved yield stability of the food peas. One food‐quality variety had reduced plant establishment with early onset of winter cold, likely attributable to low seedling vigor rather than cold sensitivity, per se. There was no evidence, in terms of divergence in plant population density or biomass, that the food‐grade pea varieties differed from AWP in cold hardiness following extreme cold events. Yield component analysis showed an especially close relationship between grains m −2 and yield, but there was relatively low broad‐sense heritability for all yield component traits. As indicated in other reports, grain yield in this pea germplasm may be most linked to plant biomass productivity and related traits. Among environmental–phenological variables analyzed, system water input was the strongest driver of yield. Over the core of the reproductive phase, increased growing degree day accumulation was associated with higher yield, while high temperatures were associated with lower yield. Wheat averaged 1.6 times more grain yield than peas, with a similar yield gap between the crops across environments differing in yield potential, though food‐grade peas typically bring higher grain prices than wheat. Thus, this new crop has great potential as a rotational crop in winter cereal‐based cropping systems, especially those in which alternative crop options have been limited.

Abstract Spring pruning of hops ( Humulus lupulus L.) is a critical practice to reduce foliar disease inoculum and control weeds, thereby supporting more profitable hop production. Although paraquat and carfentrazone have been used for spring pruning, the increasing regulatory restrictions on paraquat and the limited weed control efficacy of carfentrazone highlight the need for alternative solutions. This study evaluated glufosinate, a nonselective postemergence herbicide, during spring pruning of hop plants. Four field studies were conducted between 2022 and 2024 in experimental and commercial hop yards located in Washington and Oregon. Treatments included glufosinate applied at 1150 and 2295 g ai ha − 1 , either as a single or two sequential applications, compared to carfentrazone (35 g ai ha − 1 ) and a nontreated control. Sequential applications were made 14 days apart. Across all site‐years, glufosinate consistently provided superior hop basal shoot control, with 14 and 28 days after initial treatment (DAIT) control ranging from 50% to 96% and 34% to 96%, respectively. In contrast, carfentrazone resulted in lower control levels (36%–50% at 14 DAIT; 8%–34% at 28 DAIT). Glufosinate effectively controlled kochia (84%–93% at 28 DAIT), outperforming carfentrazone (<25%). In addition to improved weed and hop shoot control, no negative effects were observed in hop plant height or bine fresh weight at harvest, except in 1‐year‐old hops. These findings support that glufosinate is safe and effective for spring pruning in mature hops, though crop age should be considered to ensure crop safety.

Abstract Intercropping a grain legume with a grain nonlegume is of increased interest by producers in the Canadian Prairies, especially under organic production where intercropping is an alternative to the lack of economic returns of green manure or summer fallow. Information on the impacts of intercropping on root rot, a significant challenge for legume crops, is needed. The objective of this organic study, conducted over 2 years (2017–2018) in the semiarid Canadian Prairies, was to determine how intercrops of lentil ( Lens culinaris Medik.)–yellow mustard ( Sinapis alba L.) and field pea ( Pisum sativum L.)–oat ( Avena sativa L.), at different seeding ratios, might affect in‐season root rot development and associated fungal communities. This 2‐year study showed that the impacts of intercropping varied between crop combinations and among fungal species. Multiple pathogens, as well as saprophytes, were associated with the intercrops and respective monocultures, with most being Fusarium species. For intercropped lentil, there was a >50% reduction in the mean root rot severity, and an 11% reduction in the isolation of total Fusarium species, compared to its monoculture. These results suggest disease suppression in the intercropped lentil, which might be attributed to allelopathy from mustard leading to an increase in fungi with biocontrol potential (antagonists). These antagonist fungi were 84% higher in lentil intercropped with a full mustard ratio than in its monoculture. In contrast, root rot in pea intercropped with oat was mostly higher than in the pea monoculture, attributed to the prevalence of similar species, including Fusarium pathogens, common to both crop species.

Abstract Intercropping is a sustainable practice becoming increasingly popular in the Canadian Prairies. However, its long‐term impact on diseases in subsequent sole crops is not well understood. We examined root rot and associated fungal communities in durum wheat [ Triticum turgidum L. ssp. durum (Desf.) Husn.], following different ratios of lentil ( Lens culinaris Medik.)–yellow mustard ( Sinapis alba L.), and field pea ( Pisum sativum L.)–oat ( Avena sativa L.) intercrops, and respective monocultures, in a semiarid region of the Canadian Prairies (2018–2019). The previous crop(s) impacted disease severity in durum wheat and had a significant impact on the composition of fungal communities. Durum grown after the mustard monoculture and its high‐ratio intercrop had 15% less severe root rot than after the lentil monoculture and its high‐ratio intercrop, while durum following the oat monoculture and its intercrops had 16% more severe root rot than after mustard and its intercrops. Fusarium species were the most frequent fungal isolates, accounting for 70% of total isolations. The main Fusarium cereal pathogens were >1.7x–25.5x higher following the oat than the mustard monoculture and 2x–3x higher after the pea–oat than the lentil–mustard intercrops. In turn, isolation of the main fungi with biocontrol potential (antagonists) was 4.3x–5x higher after the mustard than oat monoculture, and 2x higher after lentil–mustard than pea–oat. The prevalence of antagonists in mustard‐containing treatments, and their negative correlation with disease levels, suggest a dual mechanism of disease suppression: a direct pathogen inhibition through the mustard's allelopathy and enhanced populations of indigenous microbial antagonists.