CONICET | Buscador de Institutos y Recursos Humanos

Introduction: Chickpea cropping in Argentina experienced, since 2000, a high increase due to new crop-specific technologies (varieties, field management and farm equipment). The high level of acceptance of grains cultivates in Argentina makes the country a leading exporter, which drives the need to expand the local genetic base developing Kabuli and Desi types of new cultivars with high performance regarding nutritional quality. Objectives: 1) to evaluate selected chickpea genotypes regarding nutritional quality, and 2) the relative contribution of genotype (G), environment (E), and GxE interaction effects on quantitative traits related to nutritional quality.Materials and methods: A total of 10 selected chickpea genotypes including advanced lines, commercial and pre-commercial cultivars from the germplasm collection of the Agricultural College at National University of Córdoba (FCA-UNC), were evaluated for chemical grain quality across 15 environments of the Argentinean crop area during 2017 to 2019 crop years. The Kabuli genotypes were Norteño, Felipe UNC-INTA, Kiara UNC-INTA, Pre-commercial line 1, Pre-commercial line 2, J22, J77 and J95. The Desi genotypes: J75 and Chañarito Negro UNC (Ch M-6). Multienvironmental trials were conducted in 5 locations (Cañada de Luque, Capital, Tuclame, Chañaritos, Candelaria) with a randomized block experimental design at each location and year, 3 replications, and 3 rows per plot. Soil samples were taken for subsequent analysis. The daily climatic record was obtained for each environment during different chickpea phenological stages. Phenotypic variables were measured after harvest. Chemical analyses were carried out at the Grain Laboratory of INTA-Manfredi, using two field replicates (200 g/sample) per G from each E. There were determined the contents of oil, protein, carbohydrates, ashes. fatty acids and tocopherols. A random effect model was fitted to obtain REML estimates of G, E and GxE variance components for each quantitative trait. The AMMI1 model was used to rank genotypes according to nutritional mean performance and stability of chemical composition across environments, and a PLS regression to correlate GxE and environmental determined variances with site covariates. Results: Significant differences for chemical composition between genotypes was found. The grain quality traits with higher contribution of G effects were oil content, gamma and delta tocopherols, and fatty acid composition mainly in content of saturate acids. Protein, ashes, carbohydrates, iodine value had lower genetic components and varied significantly among environments. Ashes ranged from 2.9 to 4.9%, indicating the environmental impact on the mineral content of the grain. Variability in environmental determined traits were correlated to soil and climate site data. The GxE interaction was significant for all traits but it was not the main source of variability, except for alpha+beta tocopherols. The average trait contents of the selected chickpea genotypes were (expressed in percentage): oil 5.96±0.76, protein 22 ± 2.2, carbohydrates 56.4± 2.2 %, total tocopherols 297.49± 39.4mg/100g, being gamma tocopherol the most abundant (221.9 mg/100g), followed by alpha+beta (64.9 mg/100g). In the fatty acid profile C18:2 had the highest content (56.9g/100g) followed by C18:1 (27.1g/100g) and C18:3 (2.86g/100g).Conclusions: Genotype-environment interaction was verified for the nutritional composition of kabuli and desi genotypes. The results provide valuable information to identify new genotypes that meet the needs of local and global demand for human consumption, complementing the action with biotechnological techniques under the concept of sustainability. They also provide information for research and the community in general through the knowledge of the nutritional quality of this pulse. Acknowledgements: Secretaría de Ciencia y Tecnología UNC, INTA Project (2019-PE-E6-1132-001) and Granaria SA through Cooperative coworking with FCA-UNC. Proyectos Especiales de Innovación CientíficoTecnológica integrados en Red Red Garbanzo de I+D+i. MINCyT-Pcia Córdoba RES. 166/2017-2019.PIODO res 134-2017