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Thirty-four red kernel rice genotypes along with two check varieties were evaluated across three different locations of Tamil Nadu viz., Coimbatore, Paiyur and Aduthurai during Kharif 2022 to assess the stability of the genotypes for single plant yield. The AMMI and GGE models were used to study the interaction between the genotypes and the environment in order to select the stable genotypes. Significant differences among the genotypes and the environment revealed the existence of variations among the genotypes and also environmental influence over the genotypes for single plant yield. Considering the overall average single plant yield performances, the genotype Rangoon samba recorded the highest single plant yield over the check varieties, while the genotype Karuthakar had the lowest single plant yield. The genotypes G24 (Thooyala), G25 (Kothamalli samba) and G34 (IG74 Check) recorded higher stable single plant yield across locations. Based on AMMI and GGE stability models, these three genotypes were identified to be highly stable over environments with less G x E interaction and these genotypes can be recommended for cultivation across the environments to obtain a higher single plant yield. [ABSTRACT FROM AUTHOR]

The soil test value is based on the soil test-based fertilizer prescription/recommendation equation. Each crop harvesting after the next crop is necessary to analyze the soil. Therefore, it is necessary to develop an alternative technique to predict postharvest soil tests after the harvest of every crop. For that a study was conducted in mixed black calcareous soils at Tamil Nadu agricultural University, Coimbatore to develop the post-harvest prediction equations for available nitrogen, phosphorus and potassium in barnyard millet cropping sequence based on a multiple regression model by considering post-harvest soil test value as the dependent variable and initial available nutrients, fertilizer doses and crop yield or crop nutrient uptake as an independent variables. The developed model was validated by computing R2 value, RMSE (root means square error), RE (relative error), and the ratio of performance to deviation (RPD) and the developed model was found to be valid. Using the validated model, post-harvest soil test values were predicted. A fertilizer recommendation was made for blackgram based on predicted postharvest soil test values in the barnyard millet-blackgram cropping sequence. The predicted soil test values were compared with actual soil test values and it revealed that the developed model is fairly accurate and best-fitted with more precision. The predicted post-harvest soil test values of barnyard millet could be used in order to prescribe fertilizer for desired yield targets for subsequent crops. [ABSTRACT FROM AUTHOR]