Intensive agricultural practices lead to a deterioration in soil quality, causing a decline in farm productivity and quality, and disturbing the ecosystem balance in command areas. To achieve sustainable production and implement effective soil management strategies, understanding the state and spatial variability of soil quality is essential. The study aims to enhance the understanding of soil quality variability and provide actionable insights for sustainable soil management. In this regard, principal component analysis (PCA) and digital soil mapping were used to assess and map the spatial variability of the soil quality index (SQI) in the Cauvery command area, Mandya district, Karnataka, India. A total of 145 georeferenced soil samples were drawn at 0–15 cm depth and analyzed for physico-chemical properties. PCA was used to reduce the dataset into a minimum dataset as eight important soil indicators and to determine relative weightage factors, which were used for assessing SQI with linear and non-linear scoring methods. For spatial assessment of SQI, the random forest algorithm with environmental covariates was used to map eight soil indicators selected in the minimum dataset. The soil property maps were subjected to linear and non-linear scoring, followed by multiplying with corresponding weightage factors and summation to produce SQI maps. Results reveal that values of SQI calculated using linear scoring, range from 0.10 to 0.64, with a mean of 0.39, while non-linear scoring exhibits a wider range of 0.12 to 0.78 and a mean of 0.48. With a slight higher sensitivity index of 6.5, non-linear scoring proved to be the better scoring method compared to linear scoring. Spatial assessment shows that the R² and LCC between the calculated and predicted SQI were higher for non-linear scoring (0.66 and 0.66) compared to linear scoring (0.60 and 0.65). The SQI maps reveal high spatial variability with more than 40 percent of soils classified as moderate-to-low index. The soils with low SQI were distributed in eastern parts, whereas western parts exhibited high-to-very-high soil quality. To achieve production goals and improve soil quality in the eastern region, sustainable soil and crop management strategies must be developed, and their effects on soil quality should be assessed.

A field experiment was conducted during the rainy (kharif) and winter (rabi) seasons of 2010–11 and 2011–12 at Dharwad, Karnataka, to study the effect of sowing dates and cropping systems on growth and yield of maize (Zea mays L.) and pigeonpea [Cajanus cajan (L.) Millsp.] under rainfed condition. Pooled data over 2 years indicated that, maize and pigeonpea sown during the first fortnight of June revealed significantly higher grain/seed yield compared to subsequent sowing dates except sowing during the second fortnight of June (7.06 and 1.15 t/ha respectively). Among the cropping systems, sole maize and pigeonpea gave significantly higher grain/seed yield (7.48 and 1.42 t/ha respectively) than the intercropping systems. Among the intercropping systems, maize + piegonpea system in (4 : 2) row ratio recorded significantly higher maize grain-equivalent yield (9.04 t/ha) followed by maize + piegonpea in row (2 : 2) ratio (8.48 t/ha). The later treatment resulted in higher net returns and benefit: cost ratio (` 56,787/ha and 3.17, respectively) than rest of the cropping systems. Among the interaction effects, intercropping of maize + pigeonpea in 4 : 2 row ratio sown during the first fortnight of June recorded significantly higher maize-equivalent yield (10.23 t/ha), net returns (` 66,665/ha) and benefit: cost ratio (3.16) over other system.

Background: Maize followed by pulses is the predominant cropping system in many parts of India. After harvesting sweet corn, most farmers leave their land unplanted, even though it has significant potential for growing a second crop during the rabi season. Greengram is one of the best options for farmers, as it not only increases their income but also utilizes the soil¢s residual nutrients and moisture. Greengram, a short-duration crop, is one of the key pulse crops in India and serves as a protein-rich food. In light of the aforementioned considerations, an experiment was conducted to evaluate whether the foliar application of micronutrients mixture to the previous kharif sweet corn crop had any residual effects on the productivity and profitability of the subsequent greengram crop. Methods: The experiment, which included ten treatments was carried out in two consecutive rabi seasons during 2022 and 2023 at the College of Agriculture, V.C. Farm, Mandya, University of Agricultural Sciences, Bangalore, Karnataka, was designed using a randomized block design (RBD) with three replications. After sweet corn stubbles were incorporated into the soil, greengram was planted as a follow-up crop to preserve soil fertility. With the exception of absolute control, the recommended dosage of NPK fertilizers (20:50:50 kg ha-1) for greengram was common. Result: The pooled data showed that the foliar application of MM2 (0.2%) + Humic acid @ 0.5% greatly enhanced growth parameters and yield attributes over absolute control, resulting in the highest net return (Rs. 45,203 ha-1) and benefit:cost ratio of 2.47 among the residual effect of micronutrients mixture.