Agricultural Research Knowledge
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- Wide range of genetic variation lentil diversity panel for agronomic and yield component traits in multi-location trial.in lentil diversity panel under diverse environmentsAuthor(s): Balech, Rind; Maalouf, Fouad; Bouhlal, Outmane; Abou-Khater, Lynn; Agrawal, Shiv Kumar (International Center for Agricultural Research in the Dry Areas (ICARDA), 2025-09-10)Date: 2025-09-10Type: Conference PaperStatus: Open accessLentil (Lens culinaris) is a nutritionally and agronomically important legume crop, valued for its protein-rich seeds and its contribution to sustainable farming systems. To better exploit natural genetic variation, identify key agronomic and yield-related traits, accelerate genetic improvement, and address major challenges such as climate change, disease resistance, and yield stability, the development of a well-phenotyped diversity panel is essential. In this study, a total of 294 lentil accessions were evaluated at two ICARDA research stations: Terbol, Lebanon, and Marchouch, Morocco, during the 2023–24 growing season. The experiments were laid out in an alpha lattice design with two replications at each location. Several agronomic and yield component traits were recorded at both sites. Spatial row and column analysis of variance revealed highly significant differences among accessions for all measured traits in both environments (p < 0.001), indicating substantial phenotypic variability. Cluster analysis grouped the accessions into six clusters at Marchouch and four clusters at Terbol, reflecting differences in trait expression across environments. Principal component analysis (PCA) showed that the first three principal components (PC1, PC2, and PC3) explained 73.68% and 61.9% of the total variation at Marchouch and Terbol, respectively. Grain yield per plant (GYPO) and biomass per plant (BYPO) contributed the largest share of variation at both locations. At Terbol, PC1 (33.3%) was strongly associated with GYPO and BYPO, while at Marchouch, PC1 (26.48%) also showed strong associations with these traits. These results demonstrate considerable phenotypic diversity within the evaluated lentil panel and provide a valuable foundation for genome-wide association studies (GWAS) and marker-assisted selection in lentil breeding programs.
- Genetic analysis and marker assisted selection using KASP markers in a doubled haploid bread wheat populationAuthor(s): Djenadi, Chafika; Yahiaoui, Samia; Abdelguerfi-Laouar, Meriem; Zine el Abidine, Fellahi; Ouakkal, Meriem; Udupa, Sripada M. (Springer nature link, 2025-07-17)Date: 2025-07-17Type: Journal ArticleStatus: Timeless limited accessBread Wheat breeding can rely on different methods, the main objective of this study was to combine Marker Assisted Selection with haplodiploidisation to accelerate the breeding process, focusing on the introduction of high yield, rust resistance genes (Lr34 and Lr46) and dwarf gene Rht1. This approach was designed to be efficient and precise, significantly speeding up the development of wheat lines with desirable traits by reducing the time and effort typically required in conventional breeding methods. In this context, the concept of genetic gain which is the result of the interaction between heritability, phenotypic variation, selection intensity, and cycle length was rigorously applied. The selection was conducted using ANOVA, PCA, MGIDI analysis, and KASP markers. Analysis of variance revealed significant differences among the parental and the DH lines for all agronomic traits, indicating substantial genetic diversity within the DH lines. From the DH lines, 54 DH lines were selected for their optimal combination of agronomic performance, including early maturity and high yield potential. Additionally, KASP analysis enabled the selection of one DH ideotype carried Lr34, Lr46, and Rht1. 61 DH lines carrying pyramided resistance genes (Lr34, Lr46) and the dwarfing gene (Rht1) based on the presence of favourable marker alleles were identified. Among these selections, 13 DH lines were identified as having the ideal combination of rust resistance, dwarfing gene alleles, and high yield potential. These selections represent a significant advancement in terms of earliness and yield, and genes pyramiding for improving wheat productivity across diverse environments.
- Screening of lentil genotypes against stemphylium blight disease and molecular identification of causal organismAuthor(s): Zaman, Md Aktar Uz; Haque, Md. Ashraful; Sarker, Ashutosh; Rohman, Md. Motiar; Sarkar, Debashish; Muzahid-E-Rahman, Md.; Haque, Ruan Binte; Akhter, Md. Shamim; Agrawal, Shiv Kumar (nature portfolio, 2025-09-02)Date: 2025-09-02Type: Journal ArticleStatus: Open accessDuring the cropping seasons of 2019–20, 2020–21, and 2021–22, respectively, lentil genotypes were screened against Stemphylium blight using the Alpha-Lattice Design with three replications at Pulses Research Centre, BARI, Ishurdi, Pabna-6620 under natural and artificial epiphytotic conditions. In case of artificial inoculum condition, the artificial cultured inoculums were sprayed at 1.3 × 105 spores/mL concentration of spores for spore inoculation in the experimental plots. The disease severity data was recorded following 1–9 disease rating scale and Area under Disease Progress Curve (AUDPC) was also estimated. Considering the disease severity and Area under Disease Progress Curve (AUDPC) under natural epiphytotic condition none of the genotype was identified as Resistant, and Very Susceptible but seven genotypes namely BARI Masur-9, BARI Masur-8, PRECOZ, BLX-12004-5, RL-12-181, BLX 10001-1, and BLX 09015 were found as Moderately Resistance-Moderately Susceptible genotypes against Stemphylium blight disease with disease rating scale 4, 16 to 30% disease infection rate, and average estimated AUDPC 81–120 among the 60 lentil genotypes. But in case of artificial inoculation during cropping season 2021-22, only three genotypes BARI Masur-9, PRECOZ, and BLX 09015 were identified as Moderately Susceptible. Disease severity was recorded higher in artificial inoculation compared to natural epiphytotic condition. Considering the yield performance under natural and artificial inoculation the genotypes BARI Masur-9, PRECOZ, BARI Masur-8, LRIL-21-112-1-1-1-1-6, BLX-12004-5, BLX 10001-1, BLX 09015, and RL-12-181 were identified Moderately-Resistant to Moderately-Susceptible genotypes with better yield performance under disease infestation.
- DNA barcoding for species resolution in Egyptian lamiaceae: regional insights and conservation applications using rbcL, matK, and trnH-psbA markersAuthor(s): Hafez, Amr; Elwahy, Ahmed H.; Radwan, Khaled; Mahmoud, Nourhan Fouad; Mahdy, Ehab M.; Fouad, Ahmed S. (Springer Nature, 2025-12-01)Date: 2025-09-13Type: Journal ArticleStatus: Timeless limited accessThe Lamiaceae family includes numerous aromatic and medicinal species, but morphological similarities between taxa often make accurate identification difficult. This study evaluates the performance of three chloroplast DNA barcoding markers, rbcL, matK and trnH-psbA, in resolving species within Thymus, Mentha and Salvia collected from different ecological regions in Egypt. Amplification and sequencing were successful in all genera with rbcL, although resolution was limited to species level (e.g. genetic distance of 0.0154 between Thymus and Mentha). In contrast, matK and trnH-psbA showed better species discrimination but lower amplification efficiency, especially in Salvia (12.5%). Among all markers, trnH-psbA showed the highest interspecific variability with 172 parsimony-informative sites. Principal coordinate analysis and phylogenetic reconstructions using maximum likelihood, maximum parsimony and Bayesian inference models showed that matK and trnH-psbA better resolved interspecific relationships and geographic clustering patterns. A concatenated tree integrating all markers further improves phylogenetic resolution and supports the use of multi-locus barcoding. This study emphasizes that matK and trnH-psbA, when combined with rbcL, improve taxonomic precision within the Lamiaceae, especially in a poorly studied Mediterranean flora such as that of Egypt. Beyond taxonomy, these results have practical implications for the authentication of medicinal species, biodiversity conservation and quality control in the herbal industry. The barcode reference data generated also contributes to regional and global plant identification databases. Our results support the implementation of multi-locus barcoding strategies to resolve complex plant groups and preserve Egypt’s rich botanical heritage.
- Multi-Environment QTL Mapping of Rust Resistance in Faba Bean (Vicia faba L.) to Uromyces viciae-fabaeAuthor(s): Atienza, Sergio; Emeran, Amero A.; Arafa, Ramadan A.; Maalouf, Fouad; Sillero, Josefina; Avila, Carmen M. (MDPI, 2025-09-12)Date: 2025-09-12Type: Journal ArticleStatus: Open accessFaba bean rust is one of the major threats to the cultivation of faba beans worldwide. Three genes for rust resistance (Uvf-1, Uvf-2 and Uvf-3) and fifteen marker-trait associations have been identified so far. This study examines the genetic basis of rust resistance derived from BPL-261, an accessions that exhibits low infection frequency and a long latency period. We constructed a genetic map based on a RIL6 population derived from the BPL-261/Vf-274 cross, which consists of 91 individuals. Subsequent generations were used to evaluate rust resistance in Lattakia (Syria), Kafr El-Sheikh (Egypt) and Córdoba (Spain). A total of six QTLs for resistance were detected on chromosomes II, III, IV and V. Comparative analyses suggest that the QTL located on chromosome V is likely to be associated with Uvf-3. The QTL on chromosome III is close to Uvf-2 but it seems to be a different QTL since the confidence intervals do not overlap. Finally, the other QTLs constitute additional sources of rust resistance in faba beans. Functional analysis of the candidate genes within the confidence intervals suggests the hypothetical involvement of various resistance mechanisms, with salicylic acid playing a significant role but it should be confirmed with further studies. Our results advance understanding of rust resistance in faba bean. Markers identified in this study should be used to develop kompetitive allele-specific PCR (KASP) assays, after their utility has been confirmed in different genetic backgrounds. This will contribute to the development of durable rust-resistant faba bean cultivars.
- Phenolic Content, Antioxidant Capacity and In Vitro Glycemic Index of Traditional Noodle (EriSte) High in Plant-Based Protein and β-Glucan ContentAuthor(s): Arer, Damla; Acar, Oguz; Ozkan, Kubra; Sagdic, Osman; Visioni, Andrea; Sestili, Francesco; Koksel, Hamit (Wiley, 2025-06-20)Date: 2025-06-20Type: Journal ArticleStatus: Open accessTraditional noodle samples (erişte) were supplemented with hull-less barley and lentil flours as the source of β-glucan and protein at different ratios and their cooking quality, phenolic content, antioxidant capacity and estimated GI values were evaluated. The estimated GI of control erişte produced from wheat flour was the highest (74.7), while GI of those supplemented with 15%, 30%, 45% barley or lentil flour were 68.7%, 66.0%, 61.2% and 67.5%, 63.8%, 60.6%, respectively. GI values of mixtures of barley and lentils flours (Mix-1–4 samples) were lower (58.9–61.0). All noodles supplemented with barley and/or lentil flours had medium GI values. The erişte samples supplemented with 45% hull-less barley flour and Mix erişte samples meet the requirements of FDA health claim (0.75 g β-glucan per serving). Protein content of control sample was 16.30%, while those supplemented with lentil flour had higher protein contents (18.15%–22.36%). Hence, noodle samples supplemented with 30% and 45% lentil flour can be labeled as “high protein” and all other noodle samples can be labeled as “source of protein” according to EC Regulation because calories which can be received from proteins per serving are > 20% and > 12%, respectively. Significant increases were also observed in phenolic contents and antioxidant capacities of erişte samples supplemented with barley/lentil flours.
- Machine learning-integrated hydrogeochemical and spatial modeling of groundwater quality indices for seawater intrusion and irrigation sustainability in coastal agroecosystems of Skhirat Region, MoroccoAuthor(s): Sanad, Hatim; Moussadek, Rachid; Zouahri, Abdelmjid; Lhaj, Majda Oueld; Mouhir, Latifa; Dakak, Houria (Elsevier (12 months), 2025-12-11)Date: 2025-10-11Type: Journal ArticleStatus: Open accessStudy region Skhirat coastal aquifer, Morocco. Study focus This study aimed to evaluate groundwater quality for drinking and irrigation, quantify seawater intrusion (SWI), and explore the added value of machine learning (ML) models for predicting groundwater indices. A total of 30 groundwater samples were collected and analyzed for physicochemical parameters. Hydrogeochemical characteristics were assessed using Piper, Gibbs, and Chadha diagrams. Water Quality Index (WQI), Irrigation Water Quality Index (IWQI), and Saltwater Mixing Index (SMI) were computed. Statistical tools (correlation matrix, PCA, K-means clustering) and GIS-based spatial interpolation were applied. Additionally, Random Forest (RF) and Artificial Neural Networks (ANN) models were tested to estimate groundwater indices and assess predictive performance. Key findings and implications Results showed WQI values ranging from 31.58 to 139.28, with 40 % of samples falling into the “poor” to “very poor” categories for drinking. IWQI revealed that 43.3 % of samples were “good,” while 6.7 % were “very poor” for irrigation suitability. SMI values exceeded 1 in 30 % of samples, confirming SWI in northwestern zones. ANN achieved higher accuracy for IWQI prediction (R² = 0.81), while RF performed best for SMI (R² = 0.74). Spatial analysis confirmed that salinization intensified toward the coast. These findings highlight the importance of integrating hydrogeochemical analysis, geospatial mapping, and ML modeling for sustainable groundwater management in Morocco’s coastal agroecosystems.
- Monte carlo simulation for evaluating spatial dynamics of toxic metals and potential health hazards in sebou basin surface waterAuthor(s): Sanad, Hatim; Moussadek, Rachid; Mouhir, Latifa; Lhaj, Majda Oueld; Dakak, Houria; Manhou, Khadija; Zouahri, Abdelmjid (nature portfolio, 2025-08-12)Date: 2025-08-12Type: Journal ArticleStatus: Open accessSurface water is vital for environmental sustainability and agricultural productivity but is highly vulnerable to heavy metals (HMs) pollution from human activities. The focus of this research is to provide an analysis of ecological and human exposure to HMs in the Sebou Basin, an agriculturally significant region within Morocco’s Gharb Plain. Using a multi-index integration approach, encompassing HM pollution indices, Human Health Risk Assessment (HHRA), Monte Carlo Simulation (MCS), multivariate statistical analysis (MSA), and Geographic Information Systems (GIS), twenty samples of surface water were taken and subjected to analysis. The results demonstrated notable spatial variability, with the northwestern, southwestern, and western parts of the Sebou Basin showing higher contamination levels. Cu exhibited the highest hazard quotient for ingestion, while Cr exceeded the hazard index (HI) threshold in both age categories. Statistical analysis uncovered strong associations, particularly between As and Cr, while principal component analysis (PCA) detected two key factors explaining 74.44% of the overall variability. Pollution indices classified all samples as highly contaminated (HPI > 30), with 65% categorized as “seriously affected” (MI > 6). The HHRA results indicated a heightened non-carcinogenic risk for children and carcinogenic risks exceeding acceptable thresholds (TCR > 10–4), with Ni presenting the highest risk (TCR = 2.32 × 10–3 for children). MCS results revealed that Cu and Cr pose potential risks, with Cu exceeding the safety threshold for ingestion in both adults and children. These results emphasize the urgent necessity for tailored strategies to reduce contamination and foster sustainable agricultural and environmental management practices.
- Preprint: Metabolite-based genome-wide association studies enable the dissection of the genetic bases of bioactive compounds in Chickpea seedsAuthor(s): Ruan, Siyue; Rocchetti, Lorenzo; Bitocchi, Elena; Wendenburg, Regina; Santamarina, Chiara; Di Vittori, Valerio; Istanbuli, Tawffiq; Hamwieh, Aladdin; Fernie, Alisdair; Papa, Roberto; Alseekh, Saleh (Cold Spring Harbor Laboratory)Date: 2025-06-12Type: Journal ArticleStatus: Open accessChickpea, is the second most consumed food legume, and significantly contributes to the human diet. Chickpea seeds are rich in a wide range of metabolites including bioactive specialized metabolites influencing nutritional qualities and human health. However, the genetic basis underlying the metabolite-based nutrient quality in chickpea remains poorly understood. Here we dissected the genetic architecture of seed metabolic diversity and explored how domestication shaped the chickpea metabolome. Through UPLC-MS we quantify over 3400 metabolic features in 509 chickpea seeds accessions from three independent multi-location field trials. The metabolite genome-wide association study (mGWAS) detected around 130,000 leading SNPs corresponding to 1890 metabolites across different environments. We further found and functionally validated a gene cluster of three CabHLH transcription factors that regulate soyasaponin biosynthesis in chickpea seeds. Our results reveal new insights on the effects of domestication process on chickpea metabolome. and provide valuable resources for the genetic improvement of the bioactive compounds in chickpea seeds.
- Mesoporous biochar reshapes soil water dynamics under shallow groundwater: interactions with nitrogen managementAuthor(s): Elbana, Maha Abdelhameed; Mostafa, Rania; El-Shirbeny, Mohammed Ahmed; Rashad, Mohamed; Brouziyne, Youssef; Abou Hadid, Ayman (Frontiers Media, 2025-12-03)Date: 2025-12-04Type: Journal ArticleStatus: Open accessShallow groundwater tables influence nearly one-quarter of global croplands, yet the role of biochar in such hydropedological settings remains poorly understood. This study investigated how mesoporous biochar interacts with nitrogen fertilization to modify soil properties, water dynamics, and irrigation requirements in a clay loam soil of the Nile Delta, Egypt. A two-season field experiment using randomized complete block design tested biochar (35 t ha-1) combined with three nitrogen levels (100, 80, and 50% of the common farmer practice). Biochar significantly increased available N, Ca, and Mg and altered soil moisture profile: Instead of monotonic moisture increase typical of shallow groundwater conditions, an S-shaped distribution developed within the 0–30 cm layer. Drainage losses consistently declined when biochar was combined with moderate nitrogen input. Although crop yield and fruit quality responses were not statistically significant, the biochar-nitrogen combination reduced irrigation demand by ~82 m3 ha-1 yr-1 compared to conventional management. When scaled regionally under same environmental conditions, this strategy could save >80 million m3 of irrigation water annually in Egypt, assuming 100% irrigation efficiency. These findings show that mesoporous biochar can reshape root-zone water dynamics under shallow groundwater, offering a promising strategy to enhance water-use efficiency in water-scarce regions.
- Correlating the 1H NMR fingerprinting of a collection of red lentil varieties with seed colour and morphology using advanced statistical analysesAuthor(s): Palombi, Lorenzo; Romano, Giuseppe; Tufariello, Maria; Mancarella, Sara; Visioni, Andrea; Angilè, Federica; Laddomada, Barbara; Fanizzi, Francesco Paolo (Elsevier, 2025-10-01)Date: 2025-08-21Type: Journal ArticleStatus: Open accessThis study aimed to investigate the biochemical basis of seed morphological traits in red lentils that are important for lentil producers in relation to quality, consumers’ preferences and commercial value. To achieve this objective, proton Nuclear Magnetic Resonance (1H NMR) spectroscopy combined with multivariate statistical analyses was employed. A collection of 64 red lentil varieties exhibiting diversity in seed colour, size, weight, and cotyledon pigmentation was analysed. Aqueous extracts of the seeds were profiled using 1H NMR, and spectra were processed into bucketed variables. Partial Least Squares Regression and Multiple Linear Regression were applied to assess relationships between spectral data and continuous morphological traits: lightness (L∗), chromatic indexes (a∗, b∗), Hundred Kernel Weight, and seed size. For categorical traits like cotyledon colour, Partial Least Squares Discriminant Analysis (PLS-DA) and binomial logistic regression were used. Variable Importance in Projection scores helped to identify key metabolite buckets significantly contributing to trait prediction. Metabolites such as leucine, fructose, and phenolic compounds were positively associated with seed size and weight, while NAD+ and short-chain fatty acids showed negative associations. Cotyledon colour classification achieved high accuracy (up to 100 %) using both PLS-DA and logistic models, with amino acids like leucine and alanine linked to yellow pigmentation and tryptophan and citrate linked to orange. Overall, the study demonstrates that 1H NMR fingerprinting, combined with rigorous statistical modelling, effectively elucidates the multivariate relationships between metabolomic profiles and key agronomic traits, providing a valuable tool for phenotypic prediction and lentil breeding.
- DeltaBreed: A BrAPI-centric breeding data information systemAuthor(s): Yarnes, Shawn; Palladino, Nick; Meidlinger, Dave; Philips, David; Sweeney, Heather; Mustafa, Shahana; Mandych, Matthew; Bouabane, Sam; Parsons, Tim; Slonecki, Tyler; Zhao, Dongyan; Rife, Trevor; Ellerbrock, Bryan; Courtney, Chaney; Selby, Peter; Mueller, Lukas; Flores-Gonzalez, Mirella; Aparicio, johan; Al-Shamaa, Khaled; Raubach, Sebastian; Jannink, Jean-Luc; Buckler, Edward S.; Beil, Craig; Sheehan, Moira (PUBLIC LIBRARY SCIENCE, 2025-12-12)Date: 2025-12-12Type: Journal ArticleStatus: Open accessDeltaBreed is a unified breeding data management system designed by Breeding Insight (BI, Cornell University) to serve the wide diversity of USDA-ARS specialty crop and livestock breeding programs. DeltaBreed has a RESTful microservice architecture that utilizes the BrAPI v2.1 Java Test Server as its primary database. The system is interoperable with many BrAPI-compliant applications (BrApps), including Field Book v6.1.0, and is continually aligned with the most recent BrAPI specifications (BrAPI v2.1). Here we describe the features of DeltaBreed v1.0, a minimum viable product, and how we aligned data capture and validation with community standards. We highlight the modules for management of germplasm, observation variables, experiments and observations, genotypic sample submission, and a prototype genomic database that supports polyploid and multiallelic genomic data, as well as SNP data. Several test cases are illustrated to demonstrate the successes and challenges of interoperability with other open-source BrAPI-enabled software packages. We also discuss expansion and enhancement plans for future DeltaBreed versions, as well as outline possible solutions to known limitations. To our knowledge, DeltaBreed is the first species-agnostic, fully BrAPI-compliant breeding data management system built for transactional use.
- Evaluation of Genetic Diversity of Rice (Oryza Sativa L.) Genotypes Under Salinity Stress Using Multivariate Statistical MethodsDate: 2025-12-01Type: Journal ArticleStatus: Timeless limited accessSalinity stress poses a significant challenge to rice production, particularly in regions where rice is a staple food. Breeding programs aimed at developing salt-tolerant rice varieties are crucial for enhancing food security and agricultural sustainability. In this experiment, 11 rice genotypes were evaluated as split-plot based on a randomized complete block design with three replications in summer 2012, at the Yasouj University. The main plots included 4 levels (0, 44, 88, and 132 mM) of salinity, and 11 rice genotypes considered as the subplots. According to the analysis of variance, sufficient genetic diversity was observed among genotypes for all studied traits. Breeding programs may therefore take into account the association of various component traits with yield and among themselves. According analysis of correlation coefficients under salt stress conditions revealed that traits such as flag leaf length (0.53), flag leaf area (0.61), hundred-grain weight (0.64), sterility percentage (0.67), and number of grains per panicle (0.80) had a moderate to high impact on the number of filled grains per panicle. The first two principal components (PC1, PC2) explained 64% of the data variation under non-stress conditions (PC1 = 33.50%, PC2 = 30.50%) and 64.6% under salt stress (PC1 = 37.20%, PC2 = 27.40%). This revealed that genotypes 2 and 6 were located near vectors associated with traits such as the number of grains per panicle, number of filled grains per panicle, and hundred-grain weight, indicating their superior yield under salt stress conditions. Using Ward’s method, genotypes were grouped into three clusters under both non-stress and salinity stress conditions. Under non-stress conditions, Group 2 (genotypes 2, 6, 7, 8) showed the highest filled grains and grain weight, while Group 1 (9, 10, 11) had the lowest. Under salinity stress, Group 1 (2, 4, 6) exhibited superior performance, suggesting genetic potential for salt tolerance, making them valuable for breeding programs aimed at improving yield under stress. Genotypes with high variability and desirable traits can be used in further breeding programs.
- Modeling land use change impacts and identifying erosion hotspots using RUSLE in a northwestern Ethiopian highland watershedAuthor(s): Gebremariam, Lemlem; Adem, Anwar; Fares, Ali; Tarkegn, Temesgen; Taddele Dile, Yihun; Abeyou, Abeyou; Addis, Hailu Kendie (Springer, 2025-11-26)Date: 2025-11-26Type: Journal ArticleStatus: Open accessThis study aimed to assess the impact of land use land cover (LULC) changes on soil loss (SL) and sediment yield (SY) using the Revised Universal Soil Loss Equation (RUSLE) model in the Angereb watershed. The 1991, 2001, 2011, and 2021 Landsat TM and OLI images were used for classification. Cover management (C) and conservation practice (P) factors of the RUSLE model were prepared for each LULC map. The other three RUSLE factors, such as slope length and steepness (LS), erosivity (R), and erodibility (K) factors, were prepared from digital elevation model (DEM), rainfall, and soil data, respectively. The sediment delivery ratio (SDR) and the SL maps were used to calculate the mean annual SY of the watershed. Results indicated that cultivated land expanded from 29.6% in 1991 to 42.6% in 2021 at the expense of forest and bush/shrubland. The change in LULC from 1991 to 2021 increased the mean annual SL and SY by 57% and 39%, respectively. The erosion rate increased from 107 t ha⁻¹ yr⁻¹to 134.3 t ha⁻¹ yr⁻¹ on cultivated land between 1991 and 2021. In the Angereb watershed, areas classified under very severe erosion (> 50 t ha⁻¹ yr⁻¹) cover 23.1% of the total area but contribute approximately 99.4% of the overall soil loss, predominantly occurring on steep slopes. These steeply sloped regions represent critical erosion risk zones and should be prioritized for targeted soil and water conservation interventions. The study’s findings offer valuable insights for evidence-based policymaking and the development of effective watershed management strategies.
- Integrating machine learning and the GGE biplot for identification of climate-suitable grasspea genotypesAuthor(s): Barpete, Surendra; Das, Arpita; Parikh, Mangla; Yumnam, Sonika; Aasim, Muhammad; Ali, Seyid; Singh, Akanksha; Yadav, Ashutosh; Devate, Narayana; Kaul, Smita; Bhattacharya, Sudip; Roy, Soumyayan; Gupta, Sanjeev; Agrawal, Shiv Kumar (Frontiers Media SA, 2025-11-21)Date: 2025-11-21Type: Journal ArticleStatus: Open accessGrasspea is a nutrient-rich food legume crop known for its resilience in the challenging agro-ecosystems. However, information is scanty regarding the recommendation of grasspea genotypes with respect to their suitability for both general and specific adaptations. The primary goal of the study was to delineate stable grasspea genotypes by nullifying the influence of intricate interactions among multiple traits with the environment. Additionally, the study aimed to identify suitable locations within diverse agro-climatic zones in India for future evaluation while also validating and predicting results using machine learning algorithms. From several hundred genotypes developed and tested in station trials at Amlaha, India, a panel of 64 diverse promising grasspea genotypes was identified, and their performance was subsequently assessed through multilocation testing at four diverse locations in India during 2021–2022 using the GGE biplot approach. Mean selection index of each genotype was enumerated considering multi-trait performance for better elucidation of genotype and environment ranking as well as selection of the mega-environment. The findings revealed that the environment was the primary contributor to variation across all studied traits, followed by genotype × environment interactions as the second most influential factor. Genotypes such as FLRP-B54-1-S2, Prateek, 31-GP-F3-S7, 31-GP-F3-S4, FLRP-B38-S5, 48-GP-F3-S3, and BANG-288-S2 were identified as good performers with promising multi-trait performance. Experimental results were validated using multiple performance metrics, with the Random Forest (RF) model of machine learning demonstrating superior predictive accuracy compared to the multilayer perceptron (MLP) model. Regression coefficient (R2) values ranged between 0.558 and 0.947, depending on the output variables. In conclusion, “Prateek,” “31-GP-F3-S7,” and “48-GP-F3-S3” emerged as the most stable genotypes when considering their combined yield-trait performance. These genotypes can be recommended for widespread commercial cultivation in regions where grasspea cultivation faces challenges of weather extremities.
- A tool for the estimation of the magnitudes and monetary values of ESS losses and returns on investment to combat agricultural resources degradationAuthor(s): Yigezu, YigezuDate: 2025-12-31Type: Internal ReportStatus: Timeless limited accessReversing the effects of agricultural resource degradation – and its implications for ecosystem services (ESS) – require targeted policy action. Comprehensive and consistent estimates of the magnitudes and monetary values of the loss of ESS due to inaction and avoided losses due to action to prevent and reverse agricultural resource degradation (ARD) can provide strong evidence that motivate investment and unlock financing mechanisms. In this paper, we present a decision support tool called “Analysis Pack for Economics of Agricultural Resource Degradation and Ecosystem Service Losses (APEARD)” which we developed not only to provide estimates of losses for different ESS, but also to evaluate the returns on investment and sustainability of co-benefits of actions. A national-scale application of APEARD, presented here only as proof of its versatility, shows that inaction on ARD is costing Uzbekistan potential production of at least 2 million tons of food, 63.8 thousand tons of woody biomass, and 477 thousand tons of forage, and 18.2 billion cubic meters of irrigation water, and 194 million tons of soil annually. ARD is also causing the emission of 1.6 million tons of carbon annually, among other hazards. These impacts on ESS are valued at more than US$11.1 billion per year (17.94% of GDP) - too high a cost to ignore. Were Uzbekistan and its development partners to invest $2.9 billion over 10 years to implement recommended packages of policy, institutional, and technological innovations to combat ARD, the country would reap returns worth $47.9 billion at a benefit-cost ratio of 16.5.
- Costs of Inaction, Benefits of Action, and Returns on Investment to Combat Agricultural Resource Degradation in TunisiaDate: 2025-11-01Type: Internal ReportStatus: Timeless limited accessThis study aimed at estimating the total economic costs of inaction, the benefits of action, and the returns on investment to combat agricultural resource degradation in Tunisia. The study’s scope covers all four biomes in agriculture, namely crop lands, pasturelands, forests, and irrigation water at both provincial and national levels. Using the Analysis Pack for Economics of Agricultural Resource Degradation (APEARD) tool and applying extremely conservative assumptions, we estimated that Tunisia is annually losing at least 1.9 million tons of potential production of different crops (cereals, legumes, vegetables, fruits, and cultivated forages), which represents 22% of current production and the associated crop residues in one season. Degradation also causes the loss of 431 thousand tons of forest and shrub biomass (1.09% of total stock), and 2.3 million tons (25.4%) of forage from natural pastures. Moreover, due to inaction or inadequate action to conserve water and reduce losses, the country is losing at least 884 million cubic meters of water including surface runoff (23.33% of total supply). Tunisia is also losing at least 142 million tons of soil (i.e., 8.68 ton/ha or 0.62% of total soil stock assuming an average 1,400 tons per ha of land) every year due to erosion, which is also associated with the release of at least 882 thousand tons of carbon into the atmosphere. The study estimated that if Tunisia implements recommended package of policy, institutional, and technological changes at a cost of US$611 million on 1.5 million ha of land that are prioritized for investment, it can reap time-discounted benefits valued at US$3.5 billion in ten years - leading to an average benefit:cost ratio of 5.97. The policy implication of our findings is that the government of Tunisia, its national and international development partners, civil society, and all citizens should join forces in raising awareness on the gravity of the problem and exert concerted efforts to prevent further degradation and loss of ecosystem services. Such efforts can be justified not only on social, biophysical, and environmental grounds, but also on economic rationale.
- Progress report - Protecting Ethiopian lentil cropsAuthor(s): Kemal, Seid AhmedDate: 2025-06-30Type: Donor ReportStatus: Timeless limited accessSix Fusarium oxysporum f. sp. lentis (Fol) isolates were collected between 2018 and 2021 from the ICARDA breeding station in Morocco and multiplied using autoclaved sorghum seeds. Sterilized peat moss was infested with the inoculum of each isolate five days before sowing (5 g of inoculum per 100 g of sterilized peat moss, treated with 1% solution, per cone). Nineteen elite lentil genotypes from the lentil breeding program, including released varieties in Morocco, were tested under glasshouse conditions. Prior to sowing, lentil seeds were surface sterilized using a sodium hypochlorite solution for 2 minutes, then dried at room temperature and planted. The genotypes were evaluated in three replications (five seedlings per cone), and plant mortality was recorded 40 days after planting.
- Genome wide association mapping reveals genetic loci and candidate genes for seedling stage drought tolerance in lentil (Lens culinaris)Author(s): Kumar, Neteti Siddartha; Pandey, Renu; Anand, Anjali; Singh, Amit; Aski, Muraleedhar; Mishra, Gyan Prakash; Dikshit, Harsh; Rao, Mahesh; Agrawal, Shiv Kumar; Bana, R.S.; Chinnusamy, Viswanathan; Bansal, Ruchi (Elsevier, 2025-09-01)Date: 2025-08-19Type: Journal ArticleStatus: Open accessLentil (Lens culinaris) is a very important cold-season nutritious legume crop. The crop faces intermittent drought in South Asian countries and terminal drought in West Asian and North African Mediterranean regions causing adverse impact on lentil productivity. The present study aimed to evaluate a diverse lentil panel (243 genotypes) under irrigated and drought conditions at seedling stage and to identify significant marker trait associations for drought tolerance traits. Drought stress was imposed by restricting the pre-sowing irrigation. A total of 18 different morpho-physiological traits including root (length, surface area, volume, tips and forks), physiological (germination percentage, NDVI, canopy temperature) and growth (seedling vigor, plant biomass) traits were recorded among the lentil genotypes in both control and stress conditions. All the traits except canopy temperature were found to be significantly reduced under stress. Principal component analysis explained 56.3 % variation in control and 60.7 % variation in drought condition. Shoot dry weight had significant correlation to NDVI, shoot branching, primary and total root length, and root length density. Genotypes IC560032, IC560246, P3227, IC560051, and IG134349 were identified as drought-tolerant using SSI (<0.5). Association mapping analysis identified 65 and 71 non-overlapping distinct SNPs significantly associated with all traits under control and drought conditions, respectively. Putative candidate genes encoding legumain-like cysteine endopeptidase, L-ascorbate oxidase, and auxin-responsive proteins were involved in the regulation of key drought tolerance associated traits like germination percentage, root length, seedling vigor respectively. These findings highlight the potential of lentil germplasm for drought resilience and provide a valuable genetic resource for breeding high-yielding, stress-tolerant varieties.
- Predictions of Genes Conferring Resistance to Puccinia hordei in an International Barley Panel Using Gene-for-Gene-Based Postulations and Linked Molecular MarkersAuthor(s): Singh, Davinder; A. Ziems, Laura; Sandhu, Karanjeet S.; Chhetri, Mumta; Sanchez-Garcia, Miguel; Amri, Ahmed; J. Dieters, Mark; Park, Robert (MDPI, 2025-10-12)Date: 2025-10-12Type: Journal ArticleStatus: Open accessDeployment of resistant barley cultivars is the most cost-effective and environmentally responsible strategy to manage barley leaf rust caused by Puccinia hordei. Gene predictions based on screening of germplasm with an array of well-characterised pathotypes and application of molecular markers serve as a pivotal step for identification, characterisation, and deploying resistance in breeding programmes. We evaluated 77 barley genotypes from 17 countries using an array of diverse P. hordei pathotypes and molecular markers to predict resistance gene identities. Evaluation and resistance analysis of the panel determined four known all-stage resistance (ASR) genes—Rph2, Rph3, Rph9.am, and Rph25 present individually or in combination, with Rph3 being the most common (33% of entries) and Rph2 the second most frequent (9%). Three entries, CG55, CG56, and CG57, exhibited low infection to all tested pathotypes and were negative for markers associated with Rph7, Rph15, and Rph28, potentially carrying novel uncharacterised resistance. In addition to ASR, our studies demonstrated that the core panel had a high prevalence of adult plant resistance (APR) to P. hordei, occurring in ~83% of entries. By employing markers linked to APR, we were able to partition known APR with Rph24 found in the most lines (60%), followed by Rph23 (17%), Rph20 (14%), and uncharacterised (9%) either individually or in combination. The resistance sources identified in this study can be effectively utilised and combined by breeding programmes to diversify their resistance gene pool. Our study also revealed the virulence and avirulence profiles of 12 Australian P. hordei pts to catalogued Rph genes, providing pathologists and breeders with insights into combining genes relevant to their breeding regions and pathogen shifts.