Legume Science最新文献

Cajanus cajan, commonly known as Arhar or tur in India, is a highly treasured plant species belonging to the Fabaceae family. Pigeonpea is a drought-tolerant legume crop produced in the world's tropics and subtropics areas, rich source of protein, carbohydrates, fiber, and minerals. It is considered as “meat for vegetarian people” and addresses malnutrition issues globally. Despite its nutritional and economic importance, the lack of comprehensive knowledge about its genomic resources prevents it from being used wisely through molecular breeding programs and biotechnological intervention. Several genomic repositories on pigeonpea are available; however, there is no cohesive integrated multi-omics database available for C. cajan. Here, we present a first report on comprehensive pigeonpea omics database, named as Ppomics database (db) available at https://ppomics.multiwebx.com/, which provides up-to-date various aspects of multi-omics information devoted to the catalogs phenomics (both qualitative and quantitative), genomics, transcriptomics, and proteomics data. Ppomics db is an integrated multi-omics platform for discovering important regulators of several qualitative and quantitative traits in pigeonpea, which can be utilized for superior breed development. Ppomics db has been made available to researchers to acquire the related omics information and perform multi-omics data analysis.

The study was based on primary data from 473 lentil farmers selected randomly to analyze productivity, profitability, efficiency, and sensitivity of lentil farms in Nepal. Methods like benefit–cost, break-even, margin safety, and sensitivity analysis, scaling technique, Cobb–Douglas type of production function, and stochastic frontier were adopted to derive farm economics, allocative, and cost efficiency levels. With average productivity of 672 kg/ha, lentil farmers in the study area were earning about 41% profit as of gross return with a profitability index of 0.78. About 45% margin of safety and estimates of benefit–cost ratio above one on all sensitivity measures is indicative of low risk and robust enterprise. Resources allocated in lentil production were found inefficient, and to achieve maximum return, expenses on land preparation, seed, nutrient, and plant protection cum irrigation should be increased by 27.6%, 80%, 33.1%, and 97%, respectively. Similarly, expenses on labor and harvesting activities need to be decreased by 30.1% and 23.6%. Labor cost and seed cost were the most important variables, and a 1% increase would surge the total production costs by 0.42% and 0.19%, respectively. The cost efficiency was estimated as 1.137 mean value, meaning that over 13.7% of the costs in lentil farms is wasted while comparing best-practiced farm. Only about 48% of farms is fairly efficient at efficiency levels 1.0 to 1.09, but the majority is inefficient, which needs to minimize the waste of resources. Although suffering from climatic risks and production-related problems, lentil enterprise is profitable, less risky, less sensitive, and fairly to inefficient in resource use. Wise attention is need on the part of farm management and resource utilization. Farmers are suggested to maintain farm size around 0.5 ha or below 1 ha, use only improved varietal seed, cut labor expenses with the use of machinery, and perform adequate tillage during sowing followed by effective disease management practices.

Common bean (Phaseolus vulgaris L.) is an important crop grown for household revenue, food, and nutrition security in many parts of the world, especially in Africa and Latin America. Anthracnose caused by Colletotrichum lindemuthianum is a major disease of common bean globally. The objective of this study was to determine the response of selected pinto bean genotypes to seven races of C. lindemuthianum the causative fungus for anthracnose. A total of 56 pinto bean genotypes and three checks were evaluated for resistance to C. lindemuthianum races 51, 65, 73, 247, 253, 263, and 1085. Significant differences were observed among the 56 pinto genotypes in their reaction to the seven races, which was generally skewed towards susceptibility except for races 51 and 73. There was no genotype that was resistant to all seven races. In general, the genotypes that showed resistance to most of the races were those that carried Co-4², which highlighted the importance of this locus to anthracnose resistance in pinto beans. Three genotypes—NDZ14006-4, NDZ14110-4, and NDZ14043—showed superior resistance (resistant to six of the seven races).

A combination of the two methods of stability analysis, the additive main effect and multiplicative interaction (AMMI) and the best linear unbiased prediction (BLUP), based on weighted average of stability (WAASB) estimated by the linear mixed models (LMM) index identified the improved genotypes. In this study, 17 advanced genotypes of lentil were studied at two locations, Zanjan and Maragheh, during the two seasons. To examine the genotype × environment interaction, the AMMI and BLUP methods using the WAASB and weighted average of mean performance (WAASBY) index were combined to evaluate the performance stability of genotypes according to different experimental plots. Considering the significant genotype × environment interaction based on likelihood ratio test (LRT), data were analyzed by the BLUP method. The highest grain yield was detected for genotype 13, followed by genotypes 7, 11, 20, 5, 12, and 19 with higher productivity than the grand mean. To select genotypes according to yield and stability, the WAASBY index was defined by combining mean grain yield and stability. Considering 50:50 contributions for the two components, the grain yield and stability of the 13 genotypes were higher than the grand mean. The highest WAASBY was observed for genotypes 7, 20, and 12, which were determined as the best genotypes of lentil under agroecological conditions encountered in the current study regions.

Cowpea (Vigna unguiculata L. (Walp)) is a multipurpose legume, which has good nutritional properties. Nutritional parameters assessed conventionally can be labour intensive, costly and time taking for germplasm screening. Near-infrared reflectance spectroscopy (NIRS) is a rapid and nondestructive method, which can facilitate high-throughput germplasm screening. In our study, estimation of amylose and sugars has been done using NIRS. Two preprocessing methods, that is, SNV-DT (standard normal variate with detrending) and MSC (multiplicative scatter correction), were performed for optimization of the original spectra. Subsequently, MPLS (modified partial least square) regression method was employed to construct the prediction models. In amylose, the best RSQ_external (coefficient of determination) (0.962) was found in SNV-DT with mathematical treatment 3,8,8,2. The same result was shown in sugar where the best RSQ_external (0.914) was found in SNV-DT with mathematical treatment 3,4,4,1. Overall, in the case of amylose and sugars, SNV-DT was found to be a good preprocessing treatment than MSC. Paired t-test values in all the treatments for both the preprocessing methods were > 0.05 indicating their reliability. High RSQ_external values for both the traits imply the applicability of the prediction models. Thus, these models can facilitate high-throughput germplasm screening in different national and international crop improvement programmes focusing on quality traits.

Common bean (Phaseolus vulgaris L.) is a grain legume rich in proteins and micronutrients, particularly iron and zinc. In this study, 30 small-seeded genotypes were planted in five locations in Ethiopia, following an alpha lattice design with three replications, to determine environmental and genotypic influence on the Fe and Zn concentration. Based on their Fe and Zn contents, bean cultivars were evaluated for adaptability and stability using AMMI analysis. The Fe concentrations of raw bean seed varied from 44.4 to 84.4 μg/g within the panel of small-seeded genotypes, with an average range of variance of 18 μg/g across environments, and its seed Zn concentrations varied from 19.7 to 32.3 μg/g, with an average range of variance of 12.6 μg/g across environments. The averages bean Fe concentration among the small-seeded genotypes across sites in Ethiopia was 62.2 and 26.1 μg/g for Zn concentrations. Results from the analysis of variance using the AMMI model indicated that genotypes accounted for 20.53% and 9.49% of the total variance in seed Fe and Zn concentrations, respectively. The environment had a greater impact, affecting 60.92% and 81.52% of total sum of squares for Fe and Zn concentrations, respectively. According to the broad-sense heritability, there appears to be some genetic control over Fe and Zn concentrations. However, the substantial effects of the environment and genotype-by-environment interaction on Fe and Zn concentrations in small-seeded genotypes indicates breeding for higher amounts of trace minerals in new bean varieties could be a challenging task. This means the notion that beans can be biofortified to have higher concentrations of Fe and Zn might not be achievable in Ethiopia. A shift in breeding strategies that focuses on traits to enhance the bioavailability of Fe and Zn from bean is warranted and could be a solution to enhance the delivery of iron from small-seeded beans produced in Ethiopia.

Phytic acid, proteins, and oils are seed storage compounds that play a role in germination and seedling growth and may determine seed quality. The pattern of accumulation of these compounds and the relationship of their contents with the seed quality of the Bambara nut (BN) are poorly understood. Seeds of three BN landraces, AbiBam001 (black/cream), LocalBam (brown speckled), and TVSU544 (cream), were harvested from two field experiments at different maturation stages and tested for final germination percentage (FGP), germination velocity index (GVI), and seedling dry weight (SDW). Seed samples from the same experiments were analyzed for phytic acid and proximate composition. Kendall's ranked correlation was used to describe relationships between phytic acid, protein, and oil contents and the seed quality of the landraces. Results showed no differences in the phytate, protein, and oil contents of landraces during seed maturation (p > 0.05), except for the phytate content of AbiBam001 (p < 0.05), which increased in the first experiment. At mass maturity, AbiBam001 and LocalBam had higher phytate and less protein and oil contents than TVSU544, implying that seed coat color may influence the phytate, protein, and oil contents of BN landraces. Higher phytate content in landraces appeared to relate positively with FGP, GVI, and SDW and vice versa. Phytic acid may positively affect seed germinability in BN landraces with high phytate content but may affect it negatively in low-phytate landraces. The oil content of all landraces had negative correlations with most seed quality characteristics, suggesting that BN oils either are not priority reserves or play a minimal role in germination and seedling growth.

The common bean weevil (Acanthoscellides obtectus [Say]) is a major post-harvest pest of common bean (Phaseolus vulgaris L.) in tropical regions. Developing and using weevil-resistant varieties is the most environmentally and cost-effective means of mitigating the losses caused by the common bean weevil. The arcelin–phytohemagglutinin–alpha-amylase (APA) locus, originally from tepary bean (Phaseolus acutifolius A. Gray), provides effective resistance against the common bean weevil. The APA locus is currently deployed in very limited market classes, and knowledge of the stability of its resistance across different market classes of common bean is limited. The objectives of this study were to (i) introgress the APA locus into selected market classes of Andean gene pool of common bean and (ii) determine the stability of APA-based resistance to A. obtectus (AO) in multiple market classes of common bean. A total of 571 F_5:7 breeding lines derived from crossing the weevil-resistant breeding line AO-1012-29-3-3A (AO-3A) possessing the APA locus with seven Andean genotypes belonging to five market classes were evaluated for resistance to AO. Of the 571 breeding lines screened, 16 were resistant, representing a low weevil resistance recovery rate of 2.8%. These lines are across diverse market classes, including those preferred in African countries. Of the 16 newly developed resistant breeding lines, six were more resistant to AO (scores ranging from 1–1.3) than AO-3A (score of 2), and these can be used for further genetic enhancement of common bean resistance to AO.

Chickpea (Cicer arietinum L.) cultivation practices underwent significant transformation in recent decades due to advancements in scientific knowledge and the need for sustainable, productive farming systems. In this study, a bibliometric analysis of scientific publications from 1977 to 2023 on chickpea agronomic practices was conducted, revealing critical insights. India, as the world's leading chickpea producer, plays a pivotal role, not only in production but also as a significant contributor to scholarly research and international collaborations. The choice of journals for publication is found to influence research impact.

Analysis of research trends using co-occurrence networks of keywords reveals evolving focuses, with a recent shift towards qualitative aspects, such as protein content and nutritional quality, as well as sustainable agricultural practices. The study also emphasizes the necessity for further research on chickpea quality characteristics, strategies to mitigate antinutritional factors, yield optimization, and the impact of climate change on chickpea cultivation. Ultimately, chickpea cultivation research holds great promise in contributing to global food security and environmental sustainability. This bibliometric analysis provides a comprehensive overview of chickpea cultivation research and offers valuable insights for researchers, policymakers, and stakeholders as they navigate the future of sustainable agriculture and the quest for protein-rich food production while minimizing the environmental footprint.

Chickpea production is threatened by severe epidemics of Ascochyta blight occurring in main chickpea growing lands under appropriate weather conditions worldwide. In this 4-year research, occurrence of Ascochyta blight was monitored across nine main chickpea growing areas of Kermanshah province, western part of Iran. Each year, commercial chickpea fields were studied on a weekly basis from March to June. Disease data were collected as disease incidence (percentage of infected plants) and severity (percentage of infected tissues) and occurrence of epidemics. Weather data were collected as air temperature, rainfall, and relative humidity (RH) on a daily basis. According to a factor analysis, which explained 83% of data variance, 13 weather predictors were selected to estimate disease epidemics developed across different areas. Before modeling, a principal component analysis determined predictive values for these selected weather variables. Then, eight predictors of rainy days in March and April, mean RH in February, mean minimum temperature in January–March–April, and rainfalls in May and June were involved in model based on their predictive values. Current findings advanced our knowledge on the best weather predictors of severe epidemics of Ascochyta blight in chickpea crops at large scale.