Mutation Breeding as a Tool for Sustainable Crop Production and Climate Resilience: Experiences from the South-Eastern Europe (SEE) and Central Asia (CA)
Aug 2026· Agronomy· Vol 16, pp. 1488· 0 citations· 58 references
Abstract
The review summarizes practical experiences in using mutation breeding for crop improvement in South-Eastern Europe (SEE) and Central Asia (CA), demonstrating that mutation breeding can be a field-validated, effective approach for developing climate-resilient crops. Drawing on coordinated research conducted within national breeding programs and international initiatives supported by FAO/IAEA, applied methodologies, trait-evaluation strategies, and concrete breeding outputs in cereals, legumes, and industrial crops are presented. The use of gamma irradiation, fast neutrons, and chemical mutagens has successfully generated stable mutant lines stable mutant lines with enhanced traits, such as increased thousand-grain weight in wheat, altered oil quality in sunflower, and improved drought tolerance in common bean and sesame. The integration of classical pedigree selection with modern breeding tools such as high-throughput phenotyping, molecular and biochemical markers, and doubled-haploid technology has enabled earlier and more efficient identification of superior genotypes in mutation breeding programs. The review underscores the practical relevance of mutation breeding in contemporary pipelines to maintain yield stability and quality under adverse environmental conditions.
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
Overall, transcription factors from the DREB, NAC, MYB, and WRKY families are still considered the primary regulatory targets, but CRISPR/Cas-based gene editing is now able to provide precise, multiplex gene modifications in polyploid wheat.
Amit Kumar, Shivani, R. Chaudhary et al.· Progressive Agriculture· 0 citations
Plant breeding has progressed from phenotype-based selection to increasingly precise genetic and agronomic interventions. Advances in molecular breeding, genome engineering, and crop management have improved productivity, but have also promoted the widespread use of genetically uniform cultivars optimized for controlled production systems. While uniformity facilitates predictability and mechanization, it may constrain adaptive capacity under increasingly variable environmental conditions. In parallel, recent developments in digital agriculture, including high-resolution phenotyping, remote-sensing, molecular diagnostics, and AI-assisted decision support, are transforming the ability to monitor and manage biological variation across spatial and temporal scales. In this review, we examine how these technological advances intersect with emerging concepts in crop diversity and reproductive biology. We discuss how digital agriculture enables improved characterization of genotype-environment interactions and consider reproductive mechanisms that expand the accessible breeding space beyond conventional biparental crossing schemes, including haploid induction and multi-parental breeding. These approaches provide opportunities to accelerate trait introgression, generate novel genetic combinations, and overcome reproductive barriers. We argue that digital and diagnostic agriculture provide an informational framework for the deployment and evaluation of genetically heterogeneous plant populations. Together, recent advances suggest that technological precision and biological diversity can be integrated into breeding strategies that improve productivity and resilience.
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
Controlled-environment protocols that shorten the interval between successive generations, collectively described as speed breeding, have been presented as a decisive intervention in crop improvement. Protocols based on extended photoperiods, controlled temperature, modified light spectra, managed water and nutrient supply, high planting density and early harvest of immature seed now report four to seven generations per year in several annual species, and comparable acceleration has been demonstrated in clonally propagated and perennial species through flower induction rather than generation turnover. This review examines whether the accumulated evidence supports the claim that the technology is transformative for genetic gain, rather than merely for generation turnover. Literature was identified through Crossref Metadata Search, Europe PMC, the Directory of Open Access Journals and targeted citation searching, and was appraised for methodological adequacy, transferability and the alignment between reported outcomes and the components of the breeder’s equation. Three findings emerge. First, the evidence base is dominated by protocol development in a small number of long-day, self-pollinating annual species, and the physiological levers that accelerate development in those species are not neutral across germplasm, as allelic variation at photoperiod and circadian-clock loci determines both the magnitude of acceleration and its uniformity. Second, cycle-time reduction is supported by direct experimental evidence, whereas gains in selection accuracy, selection intensity and useful genetic variance under accelerated regimes are supported mainly by simulation and by a small number of correlation studies, so that projected gains in genetic gain per unit time remain partly extrapolated. Third, the technology interacts with resource constraints, energy demand, seed multiplication requirements and statutory variety registration in ways that are rarely quantified, and these interactions determine whether accelerated generation turnover reaches farmers. Priorities for future work include prospective comparisons of realised gain in operating programmes, systematic quantification of correlated response between accelerated and target environments, transparent reporting of energy and cost per fixed line, and extension to outcrossing, tropical and clonal species.
Kadam Abhishek Deepak, Bangar Vaibhav Dhanaji, Pranshi Dubey· Asian Journal of Biotechnolo...· 0 citations
Wheat is one of the world’s main crops. Its improvement is pivotal given the threat of climate change and the growing population. However, enhancing breeding efficiency and improving wheat are challenging due to strong genotype-by-environment (G×E) interactions and the biological complexity underlying the wheat genome and key agronomic traits. In this context, predictive frameworks and data-driven approaches can offer new strategies to address these challenges. This article provides a comprehensive review of the latest developments in wheat breeding, highlighting emerging predictive frameworks and their contributions to modern breeding pipelines. First, we report on genomic selection (GS) applications, emphasizing GS’s ability to improve complex traits by shortening the breeding cycle and increasing selection accuracy. We then describe the applications of phenomics in wheat breeding, including both ground- and unmanned aerial vehicle (UAVs)-based systems. We also discuss the potential for implementing multi-omics strategies to improve complex wheat traits. We debate how predictive breeding frameworks can assist in identifying the best parents and crosses in wheat breeding. Finally, we presented the latest panorama of software for predictive breeding and its integration with other technologies. This review reports recent advances demonstrating how predictive frameworks are reshaping wheat breeding methods, highlighting current progress and outlining future opportunities to accelerate genetic gain in wheat improvement.
P. Vitale, Karim Ammar, Flávio Breseghello et al.· WheatOmics· 0 citations
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