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Population structure and diversity of common bean (Phaseolus vulgaris L.) landraces in the Peruvian Amazon
No full textCommon bean (Phaseolus vulgaris L.) is a globally important legume with significant nutritional and agronomic value. Genetic diversity in Amazonian landraces remains undercharacterized, limiting their utilization in breeding programs. Here we analyzed 647 accessions from the Peruvian Amazon using 18 morphological traits and 23,050 high-quality DArTseq single nucleotide polymorphisms (SNPs). Our results revealed two major genetic groups corresponding to Andean and Mesoamerican gene pools, each subdivided into distinct subgroups, exhibiting high allelic richness and structured diversity. Despite abundant polymorphic loci, observed heterozygosity was low, consistent with the species’ self-pollinating nature. These findings highlight the Peruvian Amazon as a reservoir of unique genetic variation, underscoring the need for integrated in situ and ex situ conservation strategies. This germplasm offers valuable resources for breeding programs targeting tropical adaptation and resilience, contributing to sustainable agriculture and food security
Chapter 9. Using AquaCrop, DSSAT and the SIMPLE to estimate water use of underutilised cereal in South Africa
No full textThe study compares yield, biomass and water use (WU) for maize, sorghum and millet simulated using three crop models of varying complexity: AquaCrop, DSSAT and the SIMPLE model. A standard set of crop parameters was used to develop crop files for all three models. Similar soil, climate and management descriptions from the Ukulinga Research Farm were used across the models. The performance of the three models was observed to be statistically different. Based on the mean bias error, all models overestimated yield, but the lowest overestimation was with AquaCrop (0.22 t/ha), followed by DSSAT (0.24 t/ha) and the SIMPLE model (0.69 t/ha). Other statistical indicators, namely, RMSE and R2, illustrated that the simulation of yield and WP in AquaCrop was more satisfactory than DSSAT and the SIMPLE model. The study confirms that DSSAT requires relatively more input data but does not always perform more satisfactorily. Before their application, it is essential to calibrate crop growth parameters for local conditions or use parameters from local field studies when applying complex crop models such as DSSAT specifically for marginal environments, such as South Africa. On the other hand, AquaCrop performed reasonably well with minimal input requirements, confirming its application in data-limited and marginal environments. However, it is recommended that there must be calibration for all the models using inputs specific to locations.201-22
Proxydetection of the impact distance of trees on crops: An indicator of the Land Equivalent Ratio
No full textFaidherbia albida is known to affect the yield of various crops, typically in a pattern where the impact decreases with increasing distance from the tree. While several studies have investigated the spatial extent of this effect, limited research has explored how this distance varies across different crops or its relationship with crop yield and the Land Equivalent Ratio. In this study, we used a geostatistical approach combined with multispectral UAV (Unmanned Aerial Vehicle) imagery to address these gaps in understanding. The results showed that, in contrast to its tripling effect on millet yield, F. albida does not have a significant impact on groundnut pod yield, it only improves its haulm yield under its crown by about 50 %. The geostatistical analysis showed that F. albida affects the groundnut crop up to 9.8-m, compared to 18-m for millet. Yield upscaling from subplots to the whole plot was achieved with an error of 8 % for groundnut pod yield and 13 % for haulm yield. Groundnut’s partial Land Equivalent Ratio (LERcp) was 1.02 for pod yield and 1.05 for haulm yield, which was lower than the LERcp for millet. We concluded that the distance at which agroforestry trees influence crops is a reliable predictor of their effect on yield and Land Equivalent Ratio. This approach offers a promising tool for future agroforestry studies, potentially guiding crop management strategies in agroforestry systems
International training on wheat diseases and resistance breeding empowers global efforts for food security and safety
No full text9 page
Genome wide linkage mapping for black point resistance in a recombinant inbred line population of Zhongmai 578 and Jimai 22
No full textBlack point is a black discoloration of the grain embryo that reduces the grain quality and commodity grade. Identifying the underlying genetic loci can facilitate the improvement of black point resistance in wheat. Here, 262 recombinant inbred lines (RILs) from the cross of Zhongmai 578/Jimai 22 were evaluated for their black point reactions in five environments. A high-density genetic linkage map of the RIL population was constructed with the wheat 50K single nucleotide polymorphism (SNP) array. Six stable QTLs for black point resistance were detected, QBp.caas-2A, QBp.caas-2B1, QBp.caas-2B2, QBp.caas-2D, QBp.caas-3A, and QBp.caas-5B, which explained 2.1-28.8% of the phenotypic variances. The resistance alleles of QBp.caas-2B1 and QBp.caas-2B2 were contributed by Zhongmai 578 while the others were from Jimai 22. QBp.caas-2B2, QBp.caas-2D and QBp.caas-3A overlapped with previously reported loci, whereas QBp.caas-2A, QBp.caas-2B1 and QBp.caas-5B are likely to be new. Five kompetitive allele-specific PCR (KASP) markers, Kasp_2A_BP, Kasp_2B1_BP, Kasp_2B2_BP, Kasp_3A_BP, and Kasp_5B_BP, were validated in a natural population of 165 cultivars. The findings of this study provide useful QTLs and molecular markers for the improvement of black point resistance in wheat through marker-assisted breeding.3311-332
Understanding farmers' trust in stakeholders of carbon credit projects: A perception-based analysis
No full textCarbon credit projects (CCPs) are promoted to finance the adoption of carbon farming practices, yet their success depends on farmers' confidence in the organizations that recruit, train, and pay them. We investigated how farmers perceive the main actors in CCPs and which of those actors are most likely to motivate uptake of sustainable technologies. We used a perception matrix survey with 500 rice- and livestock-based farmers (the two most significant sources of agricultural emissions) in southern India to identify which actors they trust most across eight functions – participation, information, training, inclusiveness, payment transparency, understanding of farmer realities, and overall trust. State Departments of Agriculture, Horticulture, and Animal Husbandry received the highest composite score (>3.9/5), reflecting strong confidence in their technical advice, inclusive training, and fair handling of carbon credit payments. Progressive farmers and agricultural universities, including Krishi Vigyan Kendras (KVK - agricultural extension centers), formed the next tier, valued for peer demonstration and science-based support. Private companies, input dealers, and farmer-producer organizations were considered moderately reliable, while international organizations and non-governmental organizations ranked lowest due to limited village-level engagement and unclear benefits. Financial transparency emerged as the weakest function across all actors. The study underscores that public extension agencies, KVKs, and progressive farmers together constitute the trust infrastructure for credible and transparent carbon credit implementation. These findings indicate where credibility already exists and where it must be built. Embedding State Departments as nodal agencies and mandating transparent, Direct Benefit Transfer payments would institutionalize trust and accountability in future carbon projects. Project proponents can use the perception matrix framework at the design stage – and later as a diagnostic – to decide whether to deliver services through trusted public agencies and farmer networks or invest in correcting misperceptions when they stem from information gaps. Aligning CCP implementation with high-trust actors locally and publishing auditable payment schedules could accelerate the adoption of carbon farming practices, reduce disadoption, and enhance the effectiveness of India's forthcoming voluntary carbon market
Entomopathogenic nematodes and bioactive compounds of their bacterial endosymbionts act synergistically in combination with spinosad to kill Phthorimaea operculella (Zeller, 1873) (Lepidoptera: Gelechiidae), a serious threat to food security
No full textAs a staple food, potato (Solanum tuberosum L.) (Solanaceae) is one of the most produced food crops to ensure food security. The potato tuber moth (PTM), Phthorimaea operculella (Zeller, 1873) (Lepidoptera: Gelechiidae), is a major pest of potato, damaging both the growing and storage processes. In recent years, green pest control strategies have been gaining importance to reduce the adverse effects of chemicals and protect the environment. Entomopathogenic nematodes (EPNs) and their bacterial endosymbionts (Xenorhabdus and Photorhabdus spp.) have been one of the top topics studied in sustainable pest control approaches. In the present study, the two most common EPN species, Steinernema feltiae and Heterorhabditis bacteriophora, and their bacterial associates, Xenorhabdus bovienii and Photorhabdus luminescens subsp. kayaii were evaluated against PTM larvae separately and in combination with spinosad. The survival rates of infective juveniles (IJs) of EPNs were over 92% after 72 h of direct exposure to spinosad. Co-application of EPNs and bioactive compounds (BACs) of endosymbiotic bacteria with spinosad induced synergistic interactions and achieved the maximum mortality (100%) in PTM larvae 48 h post-treatment. Spinosad and BAC combinations were highly efficient in controlling the PTM larvae and provided LT50 values below 23.0 h. Gas chromatography mass spectrometry (GC-MS) analysis identified 29 compounds in total, 20 of which belonged to P. luminescens subsp. kayaii. The results indicate that the integration of EPNs and BACs of endosymbiotic bacteria with spinosad presents a synergistic interaction and enhances pest control efficacy
The gibberellic acid responsive GmbHLHm1 transcription factor influences nodule development, nitrogen fixation activity and shoot nitrogen content in soybean (Glycine max)
No full textGmbHLHm1 is a basic Helix-Loop-Helix membrane (bHLHm1) DNA binding transcription factor localized to the symbiosome membrane and nucleus in soybean (Glycine max) nodules. Overexpression of GmbHLHm1 significantly increased nodule number and size, nitrogen fixation activity, and nitrogen delivery to the shoots. This contrasts with reduced nodule numbers per plant, nitrogen fixation activity and poor plant growth when silenced using RNAi. The promoter of GmbHLHm1 was found to be sensitive to exogenous GA supply, decreasing the level of GUS expression in transformed hairy roots in both nodules and roots and reducing native GmbHLHm1 expression in wild-type nodules. In summary, our study suggests that GmbHLHm1 positively regulates soybean nodulation and nitrogen fixation, and that GA can negatively regulate GmbHLHm1 expression in soybean nodules
Use of multi-trait principal component selection index to identify fall armyworm (Spodoptera frugiperda) resistant maize genotypes
No full textThe Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith) invaded sub-Saharan Africa (SSA) in 2016 and has since become prevalent in many countries, causing significant maize grain yield losses and reduced grain quality. Breeding for host plant resistance to FAW requires improving multiple traits, complicating selection. This study evaluated the use of principal component (PC)-based multi-trait selection indices to identify FAW resistant maize genotypes. A total of 192 maize hybrids alongside four commercial hybrids, were evaluated over four seasons under artificial FAW infestation. Data on FAW leaf feeding damage (LD) at 7, 14, and 21 days after infestation, and ear damage (ED), ear rot (ER), and grain yield (GY) were recorded. The data were subjected to analysis of variance and PC analysis, and results used to construct two economic weight-free selection indices: PC1-based index (PC1BI) and PC2-based index (PC2BI). Broad-sense heritability estimates were 0.59 to 0.73 for LD, and 0.69 for GY. The two PCs explained 97.1% of the variation among the hybrids. PC1BI, with higher loadings for the leaf feeding damage traits, showed the larger desired gains for these traits (-2.92 to -3.84%) and GY (19.9%), making it a superior index to PC2BI. PC1BI identified six promising hybrids with GY above the cutoff of 7.0 t ha-1 for selection under FAW infestation. PC2BI exhibited larger gains for ED (-11.1%) and ER (-45.4%). The index-based selected hybrids consistently outperformed the commercial hybrid checks. The PC-based indices have the potential to serve as valuable tools for breeders to maximize selection gains; however, modifications are necessary to incorporate other desirable agronomic and adaptive traits
Membrane-permeable trehalose 6-phosphate precursor spray increases wheat yields in field trials
No full textTrehalose 6-phosphate (T6P) is an endogenous sugar signal in plants that promotes growth, yet it cannot be introduced directly into crops or fully genetically controlled. Here we show that wheat yields were improved using a timed microdose of a plant-permeable, sunlight-activated T6P signaling precursor, DMNB-T6P, under a variety of agricultural conditions. Under both well-watered and water-stressed conditions over 4 years, DMNB-T6P stimulated yield of three elite varieties. Yield increases were an order of magnitude larger than average annual genetic gains of breeding programs and occurred without additional water or fertilizer. Mechanistic analyses reveal that these benefits arise from increased CO2 fixation and linear electron flow ('source') as well as from increased starchy endosperm volume, enhanced grain sieve tube development and upregulation of genes for starch, amino acid and protein synthesis ('sink'). These data demonstrate a step-change, scalable technology with net benefit to the environment that could provide sustainable yield improvements of diverse staple cereal crops