Key advances include CRISPR/Cas9 editing of GmFAD2/GmWRI1, genomic selection, genomic selection, AI phenotyping, and multi‐omics to overcome yield constraints and climate vulnerability in high‐oil soybean breeding are addressed.
Abstract
Soybean (
Glycine max
L.) is the world's most important oilseed crop, supplying 25% of world‘s edible oil and 66% of feed protein. This review address genomic innovations to overcome yield constraints and climate vulnerability (especially drought stress) in high‐oil soybean breeding. Global edible oil demand will rise 30% by 2025, but modern varieties lack sufficient stress tolerance and suffer from the oil‐protein trade‐off (1% oil gain = 1.5% protein loss), drought‐induced yield losses of 10%–20%, and restrictive GMO policies that reduce exports by 15%. We define clear breeding targets: oil concentration, seed yield, oil yield, and meal protein, with acceptable trade‐off thresholds (≤ 5% protein loss, no yield penalty). Key advances include CRISPR/Cas9 editing of
GmFAD2/GmWRI1
(75% higher oleic acid), genomic selection (79% accuracy), AI phenotyping (95% precision), and multi‐omics (20% oil profile improvement). The framework enhances climate‐smart production (a 30%–40% reduction in environmental impact) and addresses regulatory hurdles. Future directions focus on precision editing, multi‐environment trials, AI pipelines, and policy harmonization to increase farmer profitability by 15% and meet 25% of biodiesel demand by 2030.
Oilseed crops underpin edible-oil supply, livestock feeding, industrial feedstocks and rural incomes, yet recent production growth has depended heavily on harvested-area expansion and remains concentrated in a small number of crops and regions. This critical narrative review examines the status of major annual oilseeds, the biological and institutional causes of uneven genetic progress, and the extent to which conventional breeding, genomics, phenomics, genomic prediction and genome editing can improve yield, stability, product quality and sustainability. Literature published principally from 2000 to 20 May 2026 was identified through accessible scholarly indexes, DOI registries and authoritative institutional sources, with foundational earlier studies retained where necessary. The evidence indicates that breeding has delivered clear gains in adaptation, hybrid performance, oil composition and resistance to selected diseases, but progress is markedly less consistent for complex traits expressed across variable environments. Narrow breeding pools, polyploidy, structural variation, antagonism among seed yield, oil concentration and meal quality, weak phenotyping, and poorly connected seed systems constrain the conversion of gene discovery into cultivar-level impact. Pangenomes and high-density markers have improved variant discovery, while genomic selection can shorten cycles and raise selection intensity when training populations represent the target breeding population. Prediction often deteriorates across unrelated germplasm, environments and market classes, limiting claims of universal efficiency. Genome editing provides persuasive proof of concept for fatty-acid modification, flowering adaptation and shatter resistance, but transformation dependence, homoeologue redundancy, regulatory divergence and sparse multi-environment evidence impede routine deployment. The strongest path forward is therefore not technology substitution but integration: broad and strategically managed diversity, product-profile-led breeding, robust multi-environment phenotyping, dynamic genomic prediction, targeted editing, and delivery systems designed around farmers, processors and consumers. Future genetic improvement should be judged by realised, durable genetic gain per unit time and cost, together with nutritional, environmental and distributive outcomes.
P. Kumari, Deep Shikha, A. Jha et al.· Journal of Advances in Biolo...· 0 citations
Maize is the most staple food crop produced in sub-Saharan Africa which its cultivation has been expanding with time however, the productivity remains low. Low productivity of maize in Africa is contributed by different challenges such as pests and diseases, drought, floodings which are associated with the effects of climate change. Drought is among the critical constraints in maize production causing yield loss up to 100% under extreme conditions. With these challenges researchers have come with some of the promising technologies that help to reduce the effect of climate changes for instance breeding new climate resilience maize varieties which using modern breeding tools like marker assisted backcrossing, quantitative trait loci, genomewide association studies, double haploid, gene editing, genomic selection and high throughput phenotyping. These tools map traits of target for introgression to recipient varieties thus reducing time of breeding cycles. Some of the climate of improvement for climate resilience include drought and heat tolerance, high stay green with low less leaf rolling, stemborer and fall armyworm tolerance, water-use efficiency and high grain yield. Effort have been done by CIMMYT in collaboration with National Agricultural Research Institutes have developed climate resilient crop varieties, however, with pace of climate change there is more effort to diversify varieties for sustainable climate resilience that will strengthen food security in sub-Saharan Africa which is the most vulnerable to climate change. There is a need to integrate approaches to cope with climate change such as use of next-generation genomic technologies, digital agriculture and data-driven approaches, strengthening seed systems, integration of farmer preferences and socioeconomic factors into the breeding process, and adaptive breeding programs based on climate scenarios. These will shorten breeding cycles and come up with new technologies that cope with variation of climate at certain intervals.
A. Mwamahonje, Anifa Mtanda, Julius S. Missanga et al.· Frontiers in Plant Science· 0 citations
Soybean is one of the most important crops for global food security, and understanding the impacts of plant diseases on its productivity is essential, particularly under climate change. Among these diseases, soybean target spot (
Corynespora cassiicola
) has re-emerged as a significant constraint in Brazilian production systems. Current management strategies focus exclusively on yield preservation without accounting for the fossil energy consumed by intensive fungicide use, highlighting the need for an energy-based threshold. Because climate change alters the environmental conditions essential for pathogen development, it is critical to determine whether future scenarios will exacerbate or constrain disease severity, as this directly dictates the frequency of energetically justifiable interventions. This study assessed the future energetic feasibility of chemical control by integrating an epidemiological model with the CROPGRO-Soybean crop model (DSSAT) across 24 Brazilian locations, using five CMIP6 models under three emission scenarios (SSP1-RCP2.6, SSP3-RCP7.0, and SSP5-RCP8.5). Yield losses were converted into energy losses and compared with the energy required for fungicide manufacture and application, establishing the Energy Injury Level (EnIL). The EnIL acts as an energy-based decision threshold, justifying chemical control only when the energy preserved in crop yield surpasses the total energy invested in fungicide interventions. Results indicate that median energy losses decrease across most scenarios toward the end of the century, suggesting a gradual reduction in average disease pressure. However, maximum potential damage increases in the Central and South regions, indicating that severe epidemics may still occur. Consequently, the frequency of energetically justified fungicide applications declines over time. In practice, the EnIL framework provides a tactical tool to help stakeholders optimize fungicide programs, reducing fossil energy waste while ensuring interventions are sustainable under variable future climates.
G. D. Luca, T. L. Romanelli, F. R. Marin· Frontiers in Agronomy· 0 citations
India faces large, persistent yield gaps across eight major crops—wheat, rice, maize, soybean, pulses, mustard, cotton, and sugarcane—that collectively limit food security and rural income. This review synthesises evidence from over 100 peer-reviewed studies (1990–2024) to provide the first comprehensive, multi-crop, agro-climatically resolved yield gap analysis for India. Applying the three-tier framework of potential yield (Yp), attainable yield (Ya), and farmer yield (Yf), exploitable yield gaps are quantified at national and agro-climatic zone level, ranked limiting factors are identified, and projected climate change impacts are assessed. Yield gaps range from 20 to 35% in irrigated rice of the north-western Indo-Gangetic Plain to 60–75% in rainfed cotton and pulses of the semi-arid tropics. Yield gaps of blackgram across 20 major districts average 515 kg ha−1, driven by moisture stress, biotic pressure, and management constraints. Nitrogen management, irrigation access, variety adoption, and sowing-date optimisation collectively explain 80–85% of exploitable gaps, while nitrogen and irrigation alone account for 40–58%. Closing 50% of exploitable yield gaps could add approximately 100 million tonnes of food grain annually without expanding cultivated area, directly supporting Sustainable Development Goal (SDG 2). However, climate change is projected to widen yield gaps of rainfed rice by 15–30% by the 2040s under Representative Concentration Pathway (RCP) 8.5. Beyond this crop-by-crop synthesis, the review proposes a constraint-transition framework in which the dominant type of limiting factor shifts predictably from biophysical (water, climate) in the largest-gap rainfed systems to agronomic management (nitrogen, sowing date, variety) at intermediate gap levels and to institutional and socioeconomic constraints (credit, extension, land tenure, gender) as gaps narrow in the best-resourced irrigated systems, thus offering a conceptual lens for prioritising interventions by development stage rather than by crop alone.
P. Dodewar, R. Bana, Y. Bajgai et al.· Land· 0 citations
Drought constitutes one of the most pervasive abiotic constraints limiting global crop productivity, with its frequency and intensity projected to increase substantially under ongoing climate change. This narrative review synthesises contemporary evidence on the genetic, physiological, and agronomic dimensions of drought resilience in major food crops, drawing on peer-reviewed literature published primarily between 2000 and 2026. Physiologically, drought impairs stomatal conductance, suppresses photosynthetic carbon assimilation, disturbs osmotic equilibrium, and restricts root-mediated water acquisition, with reproductive stages being disproportionately vulnerable. At the genetic level, the deployment of quantitative trait loci (QTL) mapping, transcription-factor engineering, CRISPR-Cas9 genome editing, and the overexpression of stress-responsive functional genes has opened novel avenues for enhancing tolerance without compromising yield potential. Breeding programmes have increasingly integrated marker-assisted selection (MAS) and genomic selection to accelerate genetic gain, whilst high-throughput phenotyping platforms now enable rapid assessment of drought-adaptive traits at a population scale. Agronomic strategies, including deficit irrigation, conservation tillage, intercropping, and application of plant growth-promoting rhizobacteria (PGPR), provide complementary levers for sustaining productivity under water-limited conditions. Emerging integrative approaches that combine multi-omics, digital precision agriculture, and policy-enabled climate-smart frameworks are highlighted as critical pathways for translating laboratory and field insights into scalable solutions. The review identifies persistent knowledge gaps—including the limited translation of genomic advances to smallholder contexts and the underexplored potential of microbiome engineering—and calls for a convergence of disciplinary expertise, equitable technology transfer, and coherent policy support to achieve drought-resilient food systems globally.
B. Santhosh, V. Sanjivkumar, H. B. Gowda et al.· Journal of Advances in Biolo...· 0 citations
Sustainable crop development aims to maintain or increase yields while reducing environmental impact and managing the challenges imposed by climate change. As the global population grows and arable land becomes scarcer, the integration of molecular breeding with bioinformatics has emerged as an effective strategy for long-term crop improvement. Bioinformatics enables researchers to analyze and interpret the vast quantities of genetic data generated by high-throughput sequencing, making it possible to identify molecular markers, candidate genes, and regulatory networks linked to specific agronomic traits, which breeders then translate into focused, ecologically sustainable breeding programs. This approach has enabled major progress across several fronts: the identification of genes conferring resistance to biotic stressors (pests, pathogens) and abiotic stressors (drought, salinity, heat); the development of nutrient-efficient, low-input crop varieties; the improvement of agronomic performance and nutritional quality through identification of yield- and quality-related genes; and the conservation and deployment of genetic diversity to safeguard long-term breeding sustainability. By combining genomic data with precision breeding techniques, researchers are developing crops that are better adapted to a growing population and a changing climate, positioning the integration of molecular breeding and bioinformatics as a central pillar of future global food security.
Muhammad Shahid Iqbal, Z. Sarfraz, Muhammad Mujahid et al.· Frontiers in Plant Science· 0 citations