Yield Stability Research Articles

Adaptation and Grain Yield Stability Analysis of Winter Wheat Cultivars with and Without Fungicides Treatment from National Variety Trials in Sweden

Adaptation and Grain Yield Stability Analysis of Winter Wheat Cultivars with and Without Fungicides Treatment from National Variety Trials in Sweden

Harnessing Biostimulants to Mitigate Abiotic Stress in Soybean Production: An Overview

Abiotic stress factors, such as drought, temperature extremes, and soil salinity, significantly impact soybean (Glycine max) growth, yield, and quality. In recent years, biostimulants have emerged as a promising solution to improve crop resilience against these stresses. Biostimulants, derived from natural sources, enhance plant growth and tolerance by stimulating physiological and biochemical processes essential for stress adaptation. This study focuses on the application of biostimulants to mitigate abiotic stress in soybean, examining their effects on growth parameters, yield stability, and biochemical responses under stress conditions. Specifically, biostimulants based on seaweed extracts, amino acids, and microbial inoculants have shown considerable potential in promoting soybean resilience by enhancing water-use efficiency, modulating antioxidant systems, and improving nutrient absorption. The findings highlight the importance of biostimulants in sustainable agriculture, offering insights into optimizing their use to improve soybean production in challenging environmental conditions.

Stability of Early Maturing Soybean Genotypes in Poland

Poland is one of the northernmost countries in the world where soybean breeding is actively conducted. A large collection of soybean genotypes was analyzed in three locations in Poland during the 2022–2023 growing seasons. The objective of this research was to determine the stability of yield, as well as the protein and fat content in the seeds of 280 genotypes. The phenotypic correlations across genotypes and environments were assessed using the Spearman coefficient. The statistical analysis was provided using the additive main effects and multiplicative interaction model. The stability of genotypes was assessed using the weighted average of absolute scores. The main factor differentiating the results between locations was the variation in weather conditions. The variety Karok, which ranks among the top 10% in genotype selection indices for yield and thousand-seed weight, is recommended based on studies conducted within the Post-Registration Variety Testing System in three voivodeships in Poland. Among the most stable genotypes, in terms of the traits analyzed in this paper, are many registered and currently grown soybean varieties such as Obelix Pompei, Coraline, Kapral, ES Mentor, NS Mercury, Pepita, Pollux, Silesia, and Heihe 45. The yield stability of soybean genotypes during the development of new varieties should be one of the factors analyzed by breeders.

Leaf carbohydrate metabolic enzyme activities are associated with salt tolerance and yield stability in the climate-resilient crop Camelina sativa

Soil salinity is an increasingly severe problem affecting plant growth and development thus posing a threat to agricultural production worldwide. Many crops currently grown are susceptible to even moderate salt stress, and crop diversification is sought to cope with increasingly challenging environmental conditions. Camelina sativa is a versatile, underutilized, low-input Brassicaceae oilseed crop valued for its high-quality seeds and its resilience to a wide range of climate conditions. In this study, the effects of salt stress on the growth and productivity of two camelina cultivars and six landraces from different geographic regions were examined. The performance of these lines was related to adjustments in their carbohydrate metabolic enzyme activity profiles in leaves as a central physiological hub. Profiling enzyme activities and their regulation in response to salt stress revealed significant genotype × treatment (G × T) interactions and allowed the identification of specific activity signatures associated with differences in yield stability in the tested lines. Yield-stable landraces showed distinct regulation patterns contrasting those of less yield-stable lines. In particular, upregulation of specific enzyme activities was associated with yield stability under salt stress. Camelina landraces may be promising resources to improve tolerance to salinity, with plasticity in carbohydrate metabolism as a contributing mechanism. Overall, these results provide a valuable basis for enzyme activity signatures as new physiological markers for supporting breeding programmes.

Accumulation of beneficial haplotypes in Huang-Huai-Hai wheat region and its application in molecular breeding

The Huang-Huai-Hai wheat region (HHHR) is characterized by the largest cultivation area and yield among all the major wheat-producing regions in China. Over the past 70 years, significant advances in wheat breeding have been achieved in this region, resulting in high and stable yields as well as improved disease resistance. However, there is a notable deficiency in the systematic molecular-level analyses of wheat breeding advantages in HHHR. To bridge this gap, we used a Wheat 55K SNP array to evaluate 384 accessions from a core collection of wheat germplasms across China to systematically analyze the distribution patterns of beneficial haplotypes associated with traits related to yield and powdery mildew resistance specific to HHHR. Our findings indicate that varieties from HHHR demonstrate significantly superior performance in terms of yield-related traits and powdery mildew resistance compared to those from other wheat regions. Using genome-wide association studies (GWAS) analysis, we identified the QTNs associated with both grain yield and powdery mildew resistance. Importantly, beneficial haplotypes were found at significantly higher frequencies in the HHHR than in other wheat-growing regions. Based on these haplotypes, the MFP-a gene was identified as potentially regulating jasmonic acid synthesis while also playing a role in grain development and conferring powdery mildew resistance. Furthermore, identity by descent (IBD) analysis revealed specific conserved genomic segments that have become fixed through selective breeding practices in HHHR, which may serve as invaluable resources for the targeted enhancement of yield and disease resistance traits in other wheat-growing areas. Finally, using the Aimengniu breeding lineage as a case study, we elucidated the genetic basis underlying the key founder parental formations utilized in breeding programs. This study not only provides essential references and guidance for future molecular breeding initiatives in China but also has implications for enhancing wheat production worldwide.

Light condition during grain-filling stage of main crop strongly influences ratooning ability of low-stubble ratoon rice

Compared with high-stubble ratoon rice (RR), low-stubble RR is superior in yield potential, grain quality, and economic benefit. However, the unstable ratooning ability limits the grain yield of low-stubble RR production. Light condition during the grain-filling stage of main crop (GFMC) may be important for rice ratooning. To elucidate the role of light condition during GFMC in affecting ratooning ability, the key response periods, and their underlying mechanisms, field experiments were conducted using two indica cultivars in 2021 and 2022. To create varied light conditions at the canopy base during GFMC, two planting density treatments combining three nitrogen (N) treatments were established in 2021, and three density treatments combining two N treatments and four shading treatments were established in 2022 for the main crop. Light intensity (LI), light quality as reflected by the ratio of red light/far red light (R/FR), and light transmission ratio (LTR) at the canopy base during GFMC and ratooning ability were dramatically altered by N fertilization but not by planting density. With increased N application, LTR, root bleeding rate, and maximum ratooning rate significantly decreased in 2021. In 2022, low N rate increased LI, R/FR, and maximum ratooning rate by 155.7-241.4%, 47.4-65.3%, and 15.6-27.5%, respectively, but reduced missing hill percentage (proportion of hills without regenerated tillers to the total number of hills) by 30.0-62.1% compared with high N rate. The missing hill percentage was negatively correlated with the indices of light condition, while the maximum ratooning rate was positively correlated with them for both cultivars. Root activity and the ratios of abscisic acid (ABA) to cytokinins (CTK), indole-3-acetic acid (IAA), and IAA+CTK could explain the effect of light condition during GFMC on ratooning ability. Shading experiment confirmed the effect of light condition on ratooning ability and further revealed that only shading during middle and late GFMC affected ratooning ability. These findings provide new insights into the regulation of ratooning ability, which are useful for developing management practices to increase the grain yield and yield stability of low-stubble RR.

Ранний сорт рапса озимого Актив

The early maturing variety Aktiv was developed as a result of the individual selection combined with selfpollination of plants from a hybrid population (No. 38787 х a variety Express), which was conducted during eight progenies with estimation in breeding nurseries of 1st and 2nd studying years. Then the best lines were included into a control nursery, nursery of preliminary and competitive trials. In a competitive trial, the variety Aktiv differed with stable high yield exceeding the early maturing standard variety Elvis by 0.44 t/ha in average for three years. A duration of a vegetative period of the new variety is significantly shorter comparing with early maturing standard varie-ty. The plants of the variety Aktiv are lower by 13 cm and more resistant to lodging than the plants of the variety Elvis. The early maturing variety Aktiv is similar to the standard variety Elvis by oil, glucosin-olate, and protein contents. Due to the results of ecological testing of 2022 in the Northern-Caucasus, Central and Central Black Soil zones of the Russian Federation, the new variety Aktiv exceeded the standard variety Elvis by yield in average by 0.24 t/hа. The variety Aktiv is recommended for cultivation in the North-Western. Central, Central Black Soil, and Northern-Caucasus regions of the Russian Federation. The variety is submitted in the State trial in 2023.

Developing drought and heat-resistant grapevine cultivars through marker-assisted breeding

Climate change poses significant challenges to viticulture, particularly through increased drought and heat stress. This study integrates physiological, biochemical, genomic, and field performance assessments to identify traits and genetic markers associated with stress tolerance in five grapevine cultivars: Cabernet Sauvignon, Chardonnay, Syrah, Merlot, and Riesling. Genomic analysis revealed specific SNP markers on chromosomes 4 and 8, linked to water-use efficiency (WUE) and proline accumulation, crucial for osmotic balance under drought conditions. Physiological assessments showed that Cabernet Sauvignon and Merlot maintained high relative water content and low stomatal conductance, reducing water loss. Biochemical analysis indicated that Chardonnay and Syrah had elevated heat shock protein (HSP) expression and low malondialdehyde (MDA) levels, supporting cellular stability under heat. Field trials further validated these traits, with Cabernet Sauvignon and Chardonnay demonstrating yield stability and high sugar content despite stress. This research underscores the potential of marker-assisted breeding to develop climate-resilient grapevine cultivars, offering practical insights for sustainable viticulture in the face of global climate shifts.

A decade of conservation agriculture in intensive cereal systems: Transitioning to soil resilience and stable yield trends in a climate crisis

Climate change jeopardizes the food security gains achieved in India since the Green Revolution, especially by impacting the productivity of the rice-wheat system in the Indo-Gangetic Plain, a region that serves as the ‘breadbasket’ of South Asia. In this study, we characterized the potential of long-term conservation agriculture (CA) based management practices (i.e., no-tillage, residue retention, and diversified rotations) to stabilize and enhance crop yields in Northwest India. The study consisted of six different production scenarios (Sc) namely Sc I: conventional rice-wheat system; Sc II: partial CA-puddled transplanted rice-zero till wheat-zero till mung bean (TPR-ZTWMb); Sc III: CA-based zero-till direct seeded rice-zero till wheat-zero till mung bean (ZTDSR-ZTWMb); Sc IV: CA-based zero till maize-zero till wheat-zero till mung bean (ZTM-ZTWMb); Sc V: Sc III + subsurface drip irrigation (SSDI); and Sc VI: Sc IV + SSDI. Long-term yield analysis indicated that the CA-based maize-wheat-mung bean system with SSDI (Sc VI) produced approximately 12%, 27% and 35% higher rice equivalent yield (REY), wheat yield and overall system yield, respectively, over to Sc I. Our study examines Wricke's ecovalence index (Wi2) and the sustainability yield index (SYI) to gauge long-term yield stability and sustainability. Consistently higher wheat yields with lower Wi2 and higher SYI were recorded in CA-based scenarios (Sc V: Wi2 = 0.82, SYI = 0.81; Sc VI: Wi2 = 0.85 and SYI = 0.82). CA-based scenarios also demonstrated stable REY over time. The soil physical properties were influenced by CA systems and compared to Sc I, bulk density was −5.89% in Sc V, followed by −3.62% in Sc III and −1.73% in Sc VI. Moreover, CA systems, Sc IV, Sc VI, and Sc V exhibited positive responses by +106%, +99 % and +72%, respectively for water infiltration rates. Overall, soil organic carbon was +83% and +69% with Sc VI and Sc V, respectively than in Sc I. By substantially enhancing soil health and crop productivity, as well as boosting resilience, CA emerges as a promising solution for meeting the increasing food demand in Northwest India and beyond.

Plant-level prediction of potato yield using machine learning and unmanned aerial vehicle (UAV) multispectral imagery

This study presents a new method for predicting the underground yield of potato at the plant level, using two key approaches: (1) identifying the critical variables for yield prediction based on plant height and vegetation index (VI) maps derived from unmanned aerial vehicle (UAV) imagery; (2) evaluating the accuracy of predictions for fresh tuber weight (FTW), number of tubers (NMT), and fresh weight per tuber (FWT), using various machine learning (ML) algorithms. During the growing season of 2022, high-resolution red, green, and blue light and multispectral images were collected weekly using a UAV. In total, 648 variables, including first- and second-order statistical parameters, were extracted from the images. Five feature-selection algorithms were used to identify the key variables influencing the predictions of FTW, NMT, and FWT. Furthermore, ML models, including random forest (RF), ridge regression, and support vector machines, were employed to refine the variable sets for ensuring stable yield component predictions. The results highlighted the importance of considering first- and second-order statistical parameters derived from plant height and VI. Second-order statistics were crucial for predicting the FTW and FWT. The RF model demonstrated high prediction accuracy, with R2 values of 0.57, 0.45, and 0.49 for FTW, NMT, and FWT, respectively, using the best feature selection method. Thus, leveraging RGB and multispectral imagery data recorded that 1.5–2 months before harvest can significantly enhance yield predictions conducted using ML models. The proposed methodology can help farmers growing potatoes or other crops optimize cultivation and predict the yield.

Yield environment changes the ranking of soybean genotypes

ContextCrossover interactions can hinder the identification of superior genotypes and the selection of evaluation sites. Identifying yield environments where frequent crossover interactions occur will help determine when narrowly or broadly adapted genotypes might excel or fail. This information can aid in targeted breeding and selection strategies. ObjectiveThis study aimed to characterize the genotypic variability in yield stability and its relation to yield, and to evaluate how changes in crossover interactions vary across yield environment among soybean maturity groups (MGs). MethodsWe studied 102 soybean genotypes spanning MGs 0.0–4.9 from 218 multi-environment trials during 2022 and 2023 in the United States (US). Genotypes were grouped in nine clusters based on MG adaptation zones for the US soybean production area. Yield stability was measured as the slope of regression in a reaction norm model. Genotype ranking consistency was estimated as the Spearman correlation between two consecutive yield environments. ResultsYield stability ranged between 0.793 and 1.181 across the dataset. The relationship between genotype stability and yield was not significant across MG clusters. All clusters showed higher ranking consistency in the highest and lowest yield environment that they explored. However, the magnitude of crossover interactions and the specific yield environments where these interactions frequently occur varied across the MG clusters. Finally, genotype choice in low- and high-yielding environments can result in yield penalties up to 516 and 710 kg ha⁻¹, respectively. Genotype choice in yield environments with frequent crossover interactions resulted in the lowest yield penalty. ConclusionThe absence of a trade-off between genotype stability and yield suggests that high-yielding soybean genotypes can be achieved through different breeding strategies. Crossover interactions were minimal in lower and higher-yielding environments among all MG clusters. The yield environment with frequent crossover and its magnitude varied among clusters. Genotype choice to minimize yield losses can vary across MG clusters and yield environments. ImplicationsIdentifying the yield environment with frequent crossovers can guide efficient resource allocation by selecting optimal test sites and prioritizing efforts in strategic breeding pipelines.

Synthesis and visible-light photocatalytic performance of Ce-BiVO4/SrTiO3Z-scheme heterojunction for H2 production and organic pollutant degradation

Ce-BiVO4/SrTiO3 (Ce-BVO/STO) Z-scheme heterojunction composites were synthesized through a hydrothermal method to address the dual challenges of the energy crisis and water pollution. The influences of Ce3+ doping in Ce-BVO and the composition ratio of Ce-BVO/STO on the photocatalytic degradation of methylene blue (MB) and water splitting for H2 production were systematically investigated. Notably, the Ce-BVO/STO-1/1 composite exhibited an H2 production capacity as high as 771.3 μmol/g under visible light irradiation for 5 h. Additionally, 96.65 % of MB (10 mg/L) was photodegraded under visible light within 150 min. Furthermore, after three cycles, the Ce-BVO/STO-1/1 composite maintained a stable H2 production yield and MB removal rate, demonstrating its high recyclability for practical application. The Z-scheme heterojunction structure effectively promoted the separation and redox reactions of photogenerated electrons (e-) and holes (h+), and the photoelectrochemical reaction mechanism responsible for the enhanced photocatalytic performance was verified. These findings indicate that the as-prepared Ce-BVO/STO-1/1 composite has significant potential for application in H2 production and pollutant degradation through visible-light-driven photocatalysis.

Unravelling Yield and Yield-Related Traits in Soybean Using GGE Biplot and Path Analysis

Soybean (Glycine max) is a vital crop for food, animal feed, and industrial products. However, its yield performance is significantly affected by genotype-by-environment interaction (GEI), which complicates the selection of high-yielding, stable varieties. This study aimed to evaluate the yield performance and stability of 12 elite soybean varieties across five major production areas in Uganda using GGE biplot and path analysis. The varieties were planted in a randomized complete block design with three replications over two consecutive seasons. Results revealed significant differences in grain yield among the varieties, locations, and their interactions (p < 0.001). The highest-yielding varieties were Maksoy 5N (979 kg ha−1), Maksoy 4N (978 kg ha−1), Maksoy 3N (930 kg ha−1), and Signal (930 kg ha−1). GGE biplot analysis grouped the locations into two mega-environments, with the Maksoy varieties exhibiting greater yield stability compared to Seed Co. varieties. Path analysis showed that traits such as the number of lower internodes, central internode length, and filled pods had the highest positive direct effects on grain yield. This study provides insights into soybean breeding in tropical environments, highlighting traits that can be targeted to improve yield and stability. The findings offer a framework for breeding programs in Uganda and similar agro-ecological regions, promoting more resilient and productive soybean varieties. This study also illustrated the potential advantages of employing more complex mathematical techniques like path analysis to uncover yield and yield-related traits in soybean breeding programs.

Genetic Variability Studies in a Biparental RIL Population for Blast Disease in Pearl Millet

Aim: This study aimed to estimate genetic parameters within a pearl millet population comprising 288 recombinant inbred lines (RILs) of the F7 generation along with two parental lines. The investigation focused on exploring the relationships among 13 quantitative traits and Blast disease score across two environments (ENV-I, ENV-II) as well as in pooled environments. Study Design: Alpha Lattice Design. Place and Duration of Study: Patancheru, Telangana and Vizianagaram, Andhra Pradesh during Kharif, 2023. Methodology: The RILs used for this current study developed through the single seed descent method at ICRISAT, Patancheru. The genotypes were assessed at ICRISAT, Patancheru, Hyderabad (ENV-I), and Agricultural Research Station, Vizianagaram, Andhra Pradesh (ENV-II). Combined Analysis of Variance, Heritability, Phenotypic Coefficient of Variation (PCV), Genotypic Coefficient of Variation (GCV), Genetic Advance as percent of Mean (GAM), and Correlation studies were performed in R 4.4.0. Results: The analysis identified significant variation in both the quantitative traits and Blast disease scores among the RILs, highlighting the potential for genetic improvement and selection. High heritability coupled with substantial genetic advance was observed for traits such as Plant Height, Number of Tillers, Panicle Length, Thousand Seed Weight, Seed Yield, Harvest Index, and Blast Score across ENV-I, ENV-II and Pooled environments. PCV and GCV were notably high for the Number of Tillers, Number of Productive Tillers, Thousand Seed Weight, Seed Yield, and Blast Score across ENV-I, ENV-II, and Pooled Environments. Seed Yield showed positive and significant correlations with the Number of Productive Tillers, Harvest Index, Plant Height, and Number of Tillers in all environments. Conversely, Blast Score exhibited negative associations with all studied traits across the environments. Conclusion: High heritability coupled with high GAM, along with medium to high PCV and GCV for traits such as plant height, panicle length, seed yield, harvest index, and thousand seed weight, indicates that these traits are predominantly genetically controlled and can be improved significantly through selection, making them valuable for breeding. Blast disease was negatively correlated with seed yield, thousand seed weight, days to maturity, harvest index, number of leaves, number of productive tillers, plant height, and number of tillers, suggesting that increased susceptibility to blast disease negatively affects key agronomic traits. This implies that genotypes with higher blast disease scores tend to exhibit lower productivity, delayed maturity, and reduced overall plant vigor, making resistance to blast disease a critical factor for achieving optimal crop performance and yield stability.

Effects of different tillage methods on soil properties and maize seedling growth in alternating wide and narrow rows rotation mode in the Songliao Plain of China

The Songliao Plain is the main maize (Zea mays L.) producing region in Northeast China. The no-tillage22NT: no-tillage. (NT) method in alternating wide and narrow rows rotation mode is widely used for maize planting in this region. However, in spring, the NT method in this mode suffer from low soil temperature and high soil water content33SWC: soil water content. (SWC), which severely restrict maize seed germination and seedling growth. We pioneered the research and practice of the ridge tillage44RT: ridge tillage. (RT) method and strip tillage55ST: strip tillage. (ST) method in this mode. We developed a new tillage machine to enable the implementation of RT and ST methods in alternating wide and narrow rows rotation mode, which has not been previously reported in this region. In this mode, the relative research of the RT method and ST method has not been conducted, and the effects of the RT method and ST method on the soil properties and maize seedling growth have not been clarified. Therefore, a 3-year field experiment was conducted at 7 randomly selected experimental sites in this region to research the effects of RT, ST, and NT methods on soil properties and maize seedling growth. During the spring sowing period, for soil pH, organic matter66OM: organic matter. (OM), available nitrogen, available phosphorus, and available potassium, both the RT method and ST method resulted in greater values than the NT method, and there was no significant difference between the RT method and ST method. This indicated that prolonged NT was not conducive to even distribution of OM, resulting in slightly lower available nitrogen, phosphorus, and potassium compared to the RT and ST methods. Within 30 days after spring sowing, for soil temperature, RT method value > ST method value > NT method value; for SWC, NT method value > RT method value > ST method value. For mean seedling emergence time77MET: mean seedling emergence time. (MET), RT method value < ST method value < NT method value; for seedling emergence rate88ER: seedling emergence rate. (ER), plant height, stem thickness, and plant dry weight, RT method value > ST method value > NT method value. Higher soil temperature, more suitable SWC, and better nutrient availability were beneficial in shortening MET, promoting dry matter accumulation, which ultimately increased plant height, stem thickness, and plant dry weight of maize seedlings. In RT, ST, and NT methods, soil temperature and plant dry weight were positively and linearly correlated in the 10–22 °C soil temperature interval. In the RT method and ST method, SWC and plant dry weight were positively and linearly correlated in the 15–24 % SWC interval. In the NT method, SWC and plant dry weight were negatively and linearly correlated in the 27–35 % SWC interval. Moreover, maize yield responses were positive for the RT method and ST method compared with the NT method. The RT method and ST method well solved the problems of low soil temperature and high SWC that existed in NT fields, which affected the early growth of maize seedlings, and ensured the stability and improvement of maize yields. The results suggest that both the RT method and ST method may provide significant improvements over the existing NT method.

Deciphering Rice Genotypes Under Submergence Stress and Optimum Condition for Yield Stability Analysis

Deciphering Rice Genotypes Under Submergence Stress and Optimum Condition for Yield Stability Analysis

Stability of anthocyanin, carotenoid and root yield of 10 sweet potato genotypes

ABSTRACT Sweet potato roots are rich in phytochemicals. The objective of this study was to evaluate the stability of number of storage roots, storage root dry weight, harvest index and anthocyanin and carotenoid contents of 10 sweet potato genotypes. Ten sweet potato genotypes were evaluated in a randomised complete block design with three replications at three locations in Surin province, including Rajamangala University of Technology Isan (RMUTI), Chomphra district and Sanom district during November 2022 to March 2023. Results indicated that the environment significantly influenced most traits, except for carotenoid content. Genotypes and genotype–environment interactions were significant for all traits. Number of storage roots was highest in genotypes found in RMUTI. Storage root yield and anthocyanin content was highest in genotypes found in Chomphra district, while harvest index and carotenoid content were highest in genotypes found in Sanom district. SR 2022/03 had the highest storage root yield across locations and in Chomphra district. KS 2022/07 had the highest harvest index and anthocyanin content across locations. SR 2022/10 had the highest anthocyanin content at RMUTI and also had the highest carotenoid content across locations. KS 2022/07 had the most stable storage root yield. SR 2022/01 had the most stable anthocyanin and carotenoid contents. Information on the levels and variability of phytochemicals in sweet potato enables breeders to select sweet potato genotypes with high and stable phytochemicals for sweet potato breeding.

Cultivating sustainable futures: multi-environment evaluation and seed yield stability of faba bean (Vicia faba L.) genotypes by using different stability parameters in Ethiopia

Faba bean is an important legume crop with significant potential to contribute to sustainable agricultural systems and food security in Ethiopia. Despite its importance, the crop is prone to various biotic and abiotic constraints that can reduce seed yield and affect its stability and adaptability. To identify stable and adaptable genotypes, 10 faba bean genotypes were evaluated at three locations over two growing seasons using different stability parameters. Genotype-by-environment interaction (GGE biplot) and additive main effect and multiplicative interaction (AMMI) analyses are the statistical methods used to evaluate crop genotype performance across different environments to identify high-performing, stable, and adaptable genotypes and to highlight preferable environments for genotype differentiation. This study utilized cultivar superiority, regression coefficients, and deviations from regression parameters that provide valuable insights into genotype performance under varying environmental conditions. This approach helps to identify robust cultivars that can thrive across different agricultural settings and challenges, ultimately contributing to improved crop production and food security. The results revealed that G9, G8, and G7 are the three most stable and adaptable genotypes. These faba bean genotypes showed greater resilience to environmental changes and improved suitability for sustainable production, making them better options for local farmers. They also bolster resilience against climate variability and ultimately ensure agricultural sustainability. The AMMI model indicated that the genotype-environment interaction (GEI) significantly influences seed yield. These findings provide crucial insights into the genetic potential of faba bean genotypes that can help breeding programs to develop high-yielding, adaptable, and stable varieties for the region and other areas with similar agro-ecological conditions.

Evaluating Drought Tolerance and Yield Stability of Sorghum Genotypes for Sustainable Agriculture in Sohag, Egypt

ABSTRACTThe major problem in the cultivation of sorghum in the Egyptian agricultural system includes arid climate and water shortage. Thus, the present study was undertaken to investigate the effect of drought conditions on the productivity of 21 different sorghum (Sorghum bicolor L.) genotypes at Sohag, Egypt. A set of drought tolerance metrics employed in the present study were Tolerance Index (TOL); Mean Production (MP); Sensitivity to Drought Index (SSI); Stress Tolerance Index (STI); Geometric mean performance (GMP) and Harmonic mean of yield (HARM). A field‐controlled experiment was conducted on the two growth seasons (2021 and 2022) concerning the impact of different drought levels on (ET0 = 0.8, 0.6 and 0.4) Grain Yields (GY) and Water Use Efficiency (WUE) for the various studied sorghum genotypes. Principal Component Analysis (PCA) was also conducted on the obtained data of the different yield parameters with the aim of identifying the most effective tolerance indices related to the different genotypes of sorghum under both conditions, optimal and stressed. Drought tolerance varies among different sorghum varieties, which, by their genetic and physiological nature, possess efficient stomatal regulation and deep‐rooted systems, enhancing water conservation and physiological functions and hence higher WUE. These are mainly influenced by environmental conditions, such as soil type and moisture levels in the region of Sohag, where such genotypes may exhibit different performances regarding drought stress. It was observed that Giza‐15 and Hybrid Sh1 were among the high performers under well‐irrigated conditions, and L38 was outstanding during a severe drought in terms of WUE. Therefore, proper genotype selection depends on the irrigation strategy. Hence, the Sohag region presents a good opportunity for further improvement of drought tolerance through designed selection and hybridization activities in sorghum breeders, and this contributes to climate‐resilient cultivars by addressing the present agricultural challenges and food security for the present world. Emphasis will be placed by breeders on the development of arid‐condition‐adapted genotypes and the development of models that can be applied within comparable climates to boost productivity and sustainability for those farmers dependent on this vital crop.

Effects of Time Based Integrated Organic and Mineral Fertilizer Rate Application on Improved Coffee Cultivar Yield at Awada South Ethiopia

Coffee Production plays a significant role in Ethiopian economy, even though the productivity at farm level is among the lowest as compared to other coffee producing country. Soil degradation is one of the most challenging problems in coffee growing areas of Ethiopia. Declining soil fertility is a fundamental problem to agricultural growth and a major reason for slow growth of food production. Therefore, this activity was designed to determine optimum application time of integrated organic and inorganic fertilizers under coffee growing areas and to assess the effects of temporal application effects of integrated organic and inorganic fertilizers on coffee yield and yield stability performance of coffee cultivar. The experiment was conducted with RCBD design with four replications and ten treatments settled from integrated organic and inorganic inputs at Awada Agricultural research sub-center starting from 2013-2023 for the last 10 consecutive years. The result demonstrated that, application of 200kgha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;N, 77kgha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;P and 12.5ton ha&amp;lt;sup&amp;gt;-1 &amp;lt;/sup&amp;gt;integrated nutrient application at each cropping season resulted statically significant higher yield result as compared to the other nutrient applications. The plot treated with the recommended NP + recommended decomposed coffee husk application per year (200kgha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;N, 77kgha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;P and 12.5ton ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;) indicated over all yield advantage over the other plots by 22.07% or 345kg/ha of clean coffee yield over the recommended (200kgha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;N, 77kgha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;P) applied alone per year and 33.39% or 522kg/ha of clean coffee yield over the plots treated with recommended decomposed coffee husk (12.5ton ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;) alone application per each cropping season.