Number Of Pods Research Articles

Importance of brassinosteroid in soybean yield

The aim of the present study was identify the effects of brassinolide plant regulator in soybean plants yield. The work was carried out at Olhos d’água farm located in Ipameri, Goiás, Brazil. It was used the Pioneer TEC 7022 IPRO with six brassinolide concentrations (0, 0.025, 0.050, 0.075, 0.1 and 0.125 ml L-1) of a pre-prepared solution and pulverized with a 100 L ha-1 flow rate. The applications were executed in R3 and R6 stages. The experiment was carried out following the completely randomized design with five replications. Each experimental plot was set up with 18x222 meters, with 0.5 meters between lines and 11 plants per linear meter. The brassinolide applications in R3 and R6 stages with 0.072 ml L-1 concentration increased the yield in 25.1%. Brassinolide increase the grains sink-source relationship and change the assimilates partition to reproductive development (pods number, grain number, grain weight per plant and yield) instead of vegetative growth, without compromising absorption of soil solution.

Agronomic Behavior of Peanut (Arachis hypogaea L.) Cultivars under Three Planting Densities in the Northeast of Peru

Factors such as the selection of cultivars and the planted density affect the development and yield of peanuts (Arachis hypogaea L.). This study’s objective was to evaluate peanut cultivars’ agronomic behavior under three planting densities in the northeast of Peru. The design used was randomized complete blocks (DBCAs) with a bifactorial arrangement 4A × 3B (factor A, peanut cultivars; factor B, planting densities), forming 12 treatments with three replications per block. The results revealed that T3 (Huayabamba cultivar + density of 30 × 50 cm) stood out, presenting the most favorable means in the number of pods (16 pods), number of seeds per pod (five seeds), height at 90 days (22.7 cm), and yield (1850 kg/ha). Empty pods did not show significant differences between treatments. T8 (Chivita cultivar + density of 20 × 50 cm) indicated the highest number of branches (six branches); in the weight of 100 seeds, the Rojo Tarapoto cultivar was the most encouraging, adapting optimally to the three densities. In addition, T7 (chivita cultivar + density of 10 × 50 cm) showed the shortest days at flowering and harvest, with 64 and 134 days. The study showed that T3 was the most efficient in pod and seed production, making it crucial to optimizing peanut yield.

Using Biochemical and Growth Parameters to Assess Soybean Yield Potential

This study, conducted in 2022 at the All India Coordinated Research Project on Soybean Dharwad, aimed to evaluate the yield potential of ten soybean genotypes, including three checks, using biochemical and growth parameters. Employing a randomized block design, the study assessed variations in chlorophyll content, which was highest in genotypes DLSb 3, DSb 34, and DSb 23. Significant differences among genotypes were observed in absolute growth rate (AGR), crop growth rate (CGR), relative growth rate (RGR), and net assimilation rate (NAR). Notably, DSb 34 and DLSb 5 exhibited the highest AGR and CGR at 60-90 days after sowing (DAS), while RGR was most pronounced in DSb 39 at 30-60 DAS. NAR peaked at 60-90 DAS, with DLSb 1 showing the highest values. Yield component analysis identified DLSb 5 and DSb 34 as the top-yielding genotypes, with significant variations in the number of pods per plant among the genotypes. These findings highlight key traits for breeding higher-yielding soybean varieties and offer valuable insights for future research and practical applications in crop improvement.”

Field-Based Soybean Flower and Pod Detection Using an Improved YOLOv8-VEW Method

Changes in soybean flower and pod numbers are important factors affecting soybean yields. Obtaining the number of flowers and pods, as well as fallen flowers and pods, quickly and accurately is crucial for soybean variety breeding and high-quality and high-yielding production. This is especially challenging in the natural field environment. Therefore, this study proposed a field soybean flower- and pod-detection method based on an improved network model (YOLOv8-VEW). VanillaNet is used as the backbone feature-extraction network for YOLOv8, and the EMA attention mechanism module is added to C2f, replacing the CioU function with the WIoU position loss function. The results showed that the F1, mAP, and FPS (frames per second) of the YOLOv8-VEW model were 0.95, 96.9%, and 90 FPS, respectively, which were 0.05, 2.4%, and 24 FPS better than those of the YOLOv8 model. The model was used to compare soybean flower and pod counts with manual counts, and its R2 for flowers and pods was 0.98311 and 0.98926, respectively, achieving rapid detection of soybean flower pods in the field. This study can provide reliable technical support for detecting soybean flowers and pod numbers in the field and selecting high-yielding varieties.

Phosphorus use efficiency in common bean genotypes

Phosphorus absorption in plants can vary depending on the genotypes, mineral levels, and environmental conditions. Thus, this study aimed to evaluate phosphorus use efficiency and the response capacity of five common bean genotypes in two cultivation cycles. A 2x5 factorial scheme was used with three replicates. Factor A consisted of using and not phosphorus fertilization, and factor B consisted of five common bean genotypes (BRS Expedito, Iraí, Pérola, Maronze, and Vermelho). The evaluated yield components were the number of pods per plant (NPP), the number of grains per plant (NGP), and the mass of 1000 grains (M1000G). The yield was calculated and extrapolated to kg ha-1. We also evaluated the phosphorus levels accumulated in the leaves and grains (mg and %) and estimated the use efficiency of using phosphorus in the grains. The data obtained were subjected to analysis of variance and compared using the Scott-Knott test at a 5% significance level. There was a significant interaction for all studied variables, indicating the interference of phosphorus fertilization in the behavior of the genotypes. The growing season influenced the genotypes' responses regarding phosphorus use. Yields increased with phosphorus fertilization and changed according to genotype. The phosphorus accumulated in the leaves and grains showed little divergence. The Iraí, Pérola, and Maronze genotypes stand out for their efficient use of phosphorus, presenting an increase above 50% when grown in soil with phosphorus fertilization. When fertilized, the Vermelho variety most accumulated phosphorus in the grains in the first season. In the second season, it showed a significant change in its response when using the phosphate fertilizer, indicating a change in behavior due to the environmental component.

Effect of Various Biochar Materials and Levels of Chicken Manure Fertilizer on Soil Chemical, Growth and Yield of Soybean (Glycine max L Merrill)

This study aims to determine the effect of various biochar materials and doses of chicken manure fertilizer on soil chemical properties, growth and yield of soybean. The research method used a 2 factorial Randomised Group Design. The first factor was the treatment of various biochar materials consisting of 4 levels, namely: B0 without treatment, B1 (corn cob biochar 1.5 kg/m2, B2 (jengkol bark biochar 1.5 kg/m2), B3 (rice husk biochar 1.5 kg/m2). Factor II was chicken manure (P) consisting of P0 (0 kg/m2), P1 (0.5 kg/m2), P2 (1 kg/m2 and P3 (1.5 kg/m2). The application of various biochar materials and chicken cohe fertilizer gave a real response to soil pH, organic C, total N, available P and K available. The results showed that the application of biochar to the growth and yield of soybean plants gave a significant effect on the parameters of stem diameter, number of productive branches, number of pods, dry weight of seeds/m2, seed production/ha. The application of jengkol skin biochar gave the highest effect on stem diameter (1.750 cm), number of productive branches (5.06 branches), number of pods (181.60 pods), dry weight of seeds/m2 (442.98 grams). The application of chicken manure fertilizer on the growth and yield of soybean plants gives a significant effect on stem diameter, number of productive branches, number of pods, dry weight of seeds/plot. The dose of chicken manure fertilizer 1.5 kg/m2 showed the highest effect on stem diameter (1.79 cm), number of productive branches (5.19 branches), number of pods (184.22 pods), dry weight of seeds/m2 (398.50 g). The interaction of biochar and chicken manure fertilizer did not give significant effect on all treatments. Keywords: Biomass, Biochar, Chicken Manure, Soybean

Genetic Studies of Diverse Genotypes of Blackgram in Kymore Plateau District of Madhya Pradesh, India

The experiment was conducted involving 96 genotypes of black gram for genetic variability of 13 quantitative traits at Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur. The analysis of variance (ANOVA) revealed existence of significant differences among the genotypes for all the characters studied. Among the genetic parameters phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV) for all the traits indicates the role of environment in expression of the characters. High GCV and PCV were maximum in case of biological yield followed by number of pods per plant, number of pod clusters per plant, harvest index, seed yield per plant and plant height. Characters like plant height, number of pod clusters per plant, number of pods per plant, biological yield, seed yield per plant and harvest index shows high heritability coupled with high genetic advance. Correlation and Path analysis studies revealed that the important yield attributing traits like biological yield, harvest index, number of pods per plant, pod length, 100 seed weight exhibited a highly significant correlation values both at phenotypic and genotypic levels. Further, the same traits also exhibited a higher value of direct effects on seed yield per plant. Hence, these traits should be given the top priority while developing the superior hybrids in blackgram.

Impacts of Varying Sowing Dates on the Profitability and Production of Cultivars of Pigeonpea (Cajanus cajan L. Mill sp.)

At the experimental farm of the College of Agriculture, Badnapur, VNMKV, Parbhani, a suitable range of field experiments were done during the kharif season, with an optimal time of sowing. The experiment was carried out using five varieties in the sub plot, V1-BSMR-736, V2-BSMR-853, V3-BDN-711, V4-BDN-708, and V5-Vipula, and four sowing dates in the main plot, D1: (15 th June), D2: (30 th June), D3: (15 th July), and D4: (30th July). The soil had a medium-black color, a clayey texture, a high base saturation level, an alkaline reaction, and a higher concentration of total soluble salts. It also had low levels of nitrogen and phosphorus and high levels of potassium and lime. The dibbling method of sowing was used. According to the experiment's results, sowing of pigeonpea on June 15 th was the best date to achieve greater yield metrics, specifically number of pods per plant, pod weight plant-1 (g), grain weight plant-1 (g), and test weight (g). in addition to economic indicators including GMR (119080 Rs ha-1), NMR (96573 Rs ha-1), and B:C (5.29), in addition to harvest index (HI), biological yield (kg ha-1) and seed yield (kg ha-1). Comparatively speaking to the other kinds, the pigeonpea variety BSMR-736 was shown to be very prolific.

ANALISIS LINTAS KARAKTER AGRONOMI TERHADAP KOMPONEN PRODUKSI KACANG TANAH (Arachis hypogaea L.)

The peanut has been one of the most important commercial crops in Indonesia and its yield still needs to be improved. Peanut yield can be increased genetically through plant breeding programs. Indirect selection in peanut plant breeding programs requires information related to the relationship between its characters, especially the relationship between growth and yield characters through correlation and path analysis. This study aims to determine the relationship between growth and yield characteristics of peanuts based on correlation values, direct effects, and indirect effects using path analysis, so that selection criteria for high-yielding peanuts are obtained. This study was conducted using a survey method. 50 peanut plant samples were taken randomly as observation units, then path analysis was carried out. The results showed that the 12 DAP canopy width was positively and significantly correlated with peanut yield characters, such as fresh pod weight and number of pods. The 12 DAP canopy width also had the highest direct and indirect influence on the character of fresh and dry pod weight, and the number of pods. Indirect selection to increase peanut yield can be done using the 12 DAP canopy width character as selection criteria.

Genetic Variability and Cluster Analysis of Faba Bean (<i>Vicia faba</i> L.) Genotypes in Debre Tabor, Northwestern Ethiopia

Faba bean, a globally important pulse, offers genetic variation for plant breeders, although information on this variability is scarce in Ethiopia. Therefore, the study was conducted to assess the genetic variability of genotypes using 49 genotypes with 7 × 7 simple lattice designs. The experiment was conducted at in Fogera National Rice Research and Training Center at Debre Tabor research site in north western Ethiopia. Analysis of variance revealed that there were highly significant differences among forty-nine genotypes for all studied traits (days to flowering, days to maturity, grain filling period, number of branch, plant height, pod per plant, biomass yield, harvest index, hundred seed weight, chocolate spot and seed yield). High GCV and PCV was observed in pod per plant and chocolate spot both at genotypic and phenotypic level including number of branch at phenotypic level. Moderate to high heritability estimates were observed in all studied traits. A high genetic advance in percent of mean was observed in the number of branches per plant, the number of pods per plant, grain yield, seed weight, and chocolate spot. In conclusion, the study found that the ET 07013-1 and ET 07005-1 genotypes are potential for future breeding programs, but further experimentation across locations and seasons is needed. It is recommended to give much attention to traits with high heritability and GAM, which include the number of branches per plant, the number of pods per plant, grain yield, hundred seed weight, and chocolate spot. The best genotypes should be included in future breeding programs to maximize yield even further. It is recommended to closely monitor traits with high heritability and high GAM.

Influence of Plant Spacing and Bio-fertilizers on Yield and Yield Attributing Characters of Rain-fed Soybean at Damazin in Blue Nile State, Sudan

This study had the objective of evaluating the effect of biofertilizers on the performance of soybean plants under different planting spacing. It was conducted during the summer seasons of 2018 and 2019at one site at Demonstration Farm of Damazin Agricultural Research Station, Sudan. The different plant spacing designated as D1, D2, and D3 (5, 10, and 15 cm between plants) under three types of bio-fertilizers as Rhizobacteria (B1), Azotobacter (B2), Bacillus (B3) and control (B0). The experiment was laid out in Randomized Complete Block design (RCBD) with three replications as split-plots trail. The result revealed that the improvement due to the application of fertilizers with wider, spacing D3 stimulated plant growth and caused an increase in dry matter accumulation and high leaf area and gave the higher number of pods and seeds/pod, particularly at inoculation with B1 and B2 bacteria. While sowing seeds inoculated with B1or B2 under closer spacing resulted in higher seed yield per unit area. To achieve optimum results in soybean variety Sudan 1, the crop may be sown in plant spacing of 10cm with inoculation seeds with B1or B2 to achieve a high plant population per unit area to obtain higher seed yield.

Principal Component and Cluster Analysis in Mungbean [Vigna radiata (L.) Wilczek

Background: Mungbean is a warm-season crop and its ability to grow quickly, allowing adaptation to multiple cropping systems and crop rotations. Principal component analysis (PCA) and cluster analysis are the useful tool to explain the diversity among the genotypes, identification of superior genotypes and characters forfuture breeding programs. Methods: The experiment was conducted at the Agricultural Experimental Farm, (AEM), Division of Genetics and Plant Breeding, RKMVERI, Narendrapur, West Bengal, for summer, 2021 and 2022 in a randomized block design. Result: Principal components i.e. PC1 to PC3 which eigen value more than one extracted from the data contributed 67.45% from the total variation. Cluster analysis revealed that the maximum contribution for the total divergence was recorded for number of branches per plant (25.7%), seed yield per plant (14.5%), plant height (13.8%) and number of pods per plant (12%). Genotypes had classified into six clusters and their intra and inter cluster distance showed the genetic diversity between them. The highest genotypes i.e. nine had in the cluster 1 followed by cluster 5 contributed six genotypes, cluster 2, 4 and 6 represented four genotypes each and the cluster 3 had three genotypes. The identified diverse genotypes like AKM 96-2, IPDI-539, PRATIKSHA NEPAL, SUKETI-1, TMB 96-2, SAMRAT, SIKHA and VIRAT showed high contribution to total diversity for number of branches per plant, plant height, number of pods per plant and number of primary branches per plant could be used in future breeding program.

Optimization of Genotyping‐by‐Sequencing (GBS) for Germplasm Fingerprinting and Trait Mapping in Faba Bean

ABSTRACTFaba bean (Vicia faba L.) is an important pulse crop with a wide range of agroecological adaptations. The development of genomic tools and a comprehensive catalog of extant genetic diversity are crucial for developing improved faba bean cultivars. The lack of a cost‐effective genotyping platform limits the characterization of large germplasm collections, understanding of genetic diversity across populations, and implementing breeder's tools like genomic selection. Genotyping‐by‐sequencing (GBS) offers high‐resolution genotyping for both model and crop plant species, even without a reference genome sequence. The genome fragments targeted by GBS depend substantially on the restriction enzyme (RE) used for the complexity reduction step. Species with complex genomic architecture require optimization of GBS with proper RE to realize the full potential of GBS. Here, we evaluated various REs in the GBS method and identified that the combination of ApeKI/MseI proved to be the most appropriate for faba bean based on the best library quality, a high number of genomic loci spread across chromosomes, and high enrichment loci associated with the gene space. With the new optimized protocol, we constructed a genetic map using a recombinant inbred line (RIL) population and identified a QTL for seed hilum color on Chromosome 1. In addition, we also genotyped a diversity panel and performed a genome‐wide association studies (GWAS) for important agronomic traits, including plant height (PH), flowering time (FT), and number of pods per plant (PPP). We identified six SNP markers significantly associated with these traits and listed potential candidate genes. The optimized faba bean‐specific GBS procedure will facilitate access to the untapped genetic diversity for genetic research and breeding and may facilitate functional genomics.

Effect of phosphorus and micronutrients on growth and yield of groundnut (Arachis hypogaea L.)

An experiment was conducted at the Crop Research Farm (CRF), Department of Agronomy, SHUATS, Prayagraj, U.P, India, during the Kharif season of 2023. The experiment was replicated three times according to a Randomized Block Design (RBD) with ten treatments. Three different concentrations of phosphorus (40, 50, and 60 kg/ha) and micronutrients (0.5% FeSO4, 0.5% ZnSO4, and 0.2% Borax) were administered as a topical spray to the leaves. A control group was treated with a mixture of 20:60:40 kg N:P:K/ha. Phosphorus application at a rate of 60 kg/ha and foliar spray of ZnSO₄ at 0.5% (treatment 8) resulted in the highest plant dry weight of 35.54 g, crop growth rate of 25.14 g/m²/day, number of pods per plant of 21.50, number of kernels per pod of 2.13, highest test weight of 365.33 g, seed yield of 3552.10 kg/ha, and B:C ratio of 2.43. The effect of applying a higher quantity of phosphorus, specifically 60 kg/ha, together with a foliar spray of ZnSO₄ at 0.5%, on the growth and yield of groundnut was found to be superior compared to the control treatment.

Soybean crop yield estimation using artificial intelligence techniques

It is common to observe conventional methods for estimating soybean crop yields, making the process slow and susceptible to human error. Therefore, the objective was to develop a model based on deep learning to estimate soybean yield using digital images obtained through a smartphone. To do this, the ability of the proposed model to correctly classify pods that have different numbers of grains, count the number of pods and grains, and then estimate the soybean crop yield was analyzed. As part of the study, two types of image acquisition were performed for the same plant. Image acquisition 1 (IA1) included capturing the images of the entire plant, pods, leaves, and branches. Image acquisition 2 (IA2) included capturing the images of the pods removed from the plant and deposited in a white container. In both acquisition methods, two soybean cultivars, TMG 7063 Ipro and TMG 7363 RR, were used. In total, combining samples from both cultivars, 495 images were captured, with each image corresponding to a sample (plant) obtained through methods AI1 and AI2. With these images, the total number of pods in the entire dataset was 46,385 pods. For the training and validation of the model, the data was divided into subsets of training, validation, and testing, representing, respectively, 80, 10, and 10% of the total dataset. In general, when using the data from IA2, the model presented errors of 7.50 and 5.32% for pods and grains, respectively. These values are considerably lower than when the model used the IA1 data, where it presented errors of 34.69 and 35.25% for pod and grain counts, respectively. Therefore, the data used from IA2 provide better results to the model.

Sustainable management of peanut damping-off and root rot diseases caused by Rhizoctonia solani using environmentally friendly bio-formulations prepared from batch fermentation broth of chitinase-producing Streptomyces cellulosae.

Soil-borne plant diseases represent a severe problem that negatively impacts the production of food crops. Actinobacteria play a vital role in biocontrolling soil-borne fungi. The target of the present study is to test the antagonistic activity of chitinase-producing Streptomyces cellulosae Actino 48 (accession number, MT573878) against Rhizoctonia solani. Subsequently, maximization of Actino 48 production using different fermentation processes in a stirred tank bioreactor. Finally, preparation of bio-friendly formulations prepared from the culture broth of Actino 48 using talc powder (TP) and bentonite in a natural as well as nano forms as carriers. Meanwhile, investigating their activities in reducing the damping-off and root rot diseases of peanut plants, infected by R. solani under greenhouse conditions. Actino 48 was found to be the most significant antagonistic isolate strain at p ≤ 0.05 and showed the highest inhibition percentage of fungal mycelium growth, which reached 97%. The results of scanning electron microscope (SEM) images analysis showed a large reduction in R. solani mycelia mass. Additionally, many aberrations changes and fungal hypha damages were found. Batch fermentation No. 2, which was performed using agitation speed of 200rpm, achieved high chitinase activity of 0.1163 U mL- 1 min- 1 with a yield coefficient of 0.004 U mL- 1 min- 1 chitinase activity/g chitin. Nano-talc formulation of Actino 48 had more a significant effect compared to the other formulations in reducing percentages of damping-off and root rot diseases that equal to 19.05% and 4.76% with reduction percentages of 60% and 80%, respectively. The healthy survival percentage of peanut plants recorded 76.19%. Furthermore, the nano-talc formulation of Actino 48 was sufficient in increasing the dry weight of the peanut plants shoot, root systems, and the total number of peanut pods with increasing percentages of 47.62%, 55.62%, and 38.07%, respectively. The bio-friendly formulations of actinobacteria resulting from this investigation may play an active role in managing soil-borne diseases.

Nitrogen sources and defoliation levels in cowpea bean

This study was aimed at evaluating the effect of artificial defoliation and different nitrogen sources on production traits of cowpea using mixed generalized linear models. The experiment was developed in a 3x5x2 factorial arrangement, being: three Nitrogen sources; five levels of artificial defoliation; and two defoliation seasons, with four repetitions. The plots were distributed in the Randomized Block Design, developed in a greenhouse and in the field. The following characteristics were evaluated: number of pods produced per plant; number of grains produced per pod; number of grains produced per plant; average length of pods; average weight of 100 grains; and estimated production. The GLIMMIX procedure was used because it allows the probability distribution of the response variable to take the appropriate distribution model. Production per Hectare (PHA) of plants subjected to leaf loss area can be increased up to 50% defoliation level, the variety Tumucumaque overcompensates in productivity, with maximum yields at 27.03% of defoliation and significant decrease above 75%, regardless of phenological stage. Even with losses above these levels, this cultivar had high indexes of productivity, revealing its high resistance to leaf loss injury. The use of chemical nitrogen fertilization and inoculation of cowpea seeds, variety Tumucumaque with Bradyrhizobium is unnecessary in the edaphoclimatic conditions of Bom Jesus – PI; The use of nitrogen fertilization with ammonium sulfate and inoculation of cowpea seeds with Bradyrhizobium does not influence the resistance of the Tumucumaque variety to defoliation levels; Defoliation levels above 75% impair the performance of production traits of cowpea, Tumucumaque.

Application of combined GA3 and NAA treatments to improve yield and quality of Okra (Abelmoschus esculentus L.)

In Bangladesh, okra is an important popular summer vegetable. However, traditional farming practices often lead to suboptimal yields. Thus, the study was designed to determine the ideal GA3 and NAA doses for accelerating okra growth, yield, and quality characteristics. A three-replication, randomized complete block design was adopted. Foliar sprays with three concentrations of GA3 (0 ppm, 150 ppm, and 250 ppm) and NAA (0 ppm, 150 ppm, and 250 ppm) were applied in 2022 and 2023. In comparison to the control, the combined application of GA3 @ 150 ppm and NAA @ 150 ppm improved plant height, leaf number, leaf area, branch number, internode length, bud number, pod number, pod length, pod diameter, and 1000 seed weight average over the two years. Furthermore, GA3 @ 150 ppm with NAA 150 ppm increased yield by 35.08% and 27.01% in 2022 and 2023 respectively, above the control. Combining NAA @ 150 ppm with GA3 resulted in higher levels of vitamin C, TSS, magnesium, and zinc by 19.31%, 81.2%, 22.73% and 21.43% in 2022 and 22.83%, 50.57%, 18.07%, 33.33% in 2023 respectively, compared to the control. In contrast, GA3 and NAA decreased potassium and calcium in both year when compared to the control. Overall, the results of this experiment indicated that using GA3 @ 150 ppm with NAA @ 150 ppm could enhance okra growth, yield, and quality. These findings provide insightful information for improving okra cultivation techniques and improving Bangladesh’s productivity in agriculture and food security.

Correlation and Path Coefficient Analysis of Yield and Yield Components in Faba Bean (<i>Vicia faba </i>L.) Genotypes

Through the use of path coefficient analysis and correlation, crop breeders can improve complex traits like grain yield through indirect selection. The current study set out to quantify the relationship between yield and traits related to yield as well as pinpoint critical features for indirect selection aimed at enhancing the grain yield of faba bean. The objective of the current study was to identify key characteristics for indirect selection targeted at increasing the grain yield of faba beans as well as quantify the relationship between yield and variables related to yield. The study was conducted at Fogera National Rice Research and Training Center at the Debre Tabor research site used a 7x7 simple lattice design with two replications to evaluate 49 faba bean genotypes during the rainy cropping season of 2022. The study found a significant positive correlation between grain yield, plant height, pod number, biomass yield, 100-seed mass, and harvest index. The study found that biomass yield and harvest index significantly impact grain yield, suggesting they can be used as indirect selection criteria to enhance faba bean grain yield.

Study of Genetic Variability and Character Association for Yield and Components Traits in Chickpea (Cicer arietinum L.) Germplasm in Bundelkhand Region

Chickpea (Cicer arietinum L.) is a very important crop among the grain legume crops in India. It is grown in north India in the winter season on marginal and semi-marginal land as a commonly non-irrigated crop. Bundelkhand, a region in Uttar Pradesh, India, is notorious for its harsh climate, characterized by extreme heat and drought stress. Temperature fluctuate with highs reaching 50°C in summer and lows of 5°C in winter, exert substantial adverse effects on chickpea cultivation, impairing crop growth and yield and demand to have genetic resources used in breeding programs. The experiment aimed to characterize and evaluate 204 chickpea lines, including commercial varieties, to understand the magnitude of variability and the association of various yield parameters on the yield of chickpea based on 12 agro-morphological characters under Bundelkhand region. ANOVA shows that significant variation exists for most of the characteristics of chickpeas. Higher GCV and PCV were observed for plant population (GCV 24.92, PCV 31.22) followed by the number of secondary branches (GCV 21.61, PCV 26.55), number of pods per plant (GCV 12.92, PCV 18.47), seed yield per plant (GCV 11.39, PCV 21.98) and biological yield per plant (GCV 11.68, PCV 20.37), revealing that the environment plays a positive role in the expression of these characters. High heritability was found by 100 seed weight (96.41) followed by seed yield per plant (84.11) and number of pods per plant (66.26) and a high degree of genetic advance was found in the number of pods per plant (26.24) followed by biological and seed yield per plant (15.25 and 6.92). High heritability coupled with high genetic advance was found in seed yield per plant, followed by biological yield per plant, indicating selection could be rewarding in proper breeding programs. Correlation and path studies showed that biological yield per plant (r-0.91), number of pods per plant (r- 0.680), number of secondary branches per plant (r-0.46), number of seeds per pod (r-0.32) and 100 seed weight (0.29) turned out to be the main components for seed yield per plant in chickpea, stipulating that these characters could be desirable selection parameter.