Knowledge about spatial distribution patterns of soil attributes is very much needed for site-specific soil nutrient management (SSSNM) under precision agriculture. High spatial heterogeneity exists in the agricultural soils of India due to various reasons. The present practice of assessing the spatial variability of the vast cultivated landscape of India by using traditional soil sampling and analysis is costly and time consuming. Hence, proximal soil sensing (PSS) is an attractive option to assess the plot-scale spatial variability pattern (SVP) of soil attributes for SSSNM. A PSS system, either in a fixed position or mounted on a vehicle (on-the-go), can be used to obtain measurements by having direct contact with soil. PSS measurements provide low-cost and high-density data pertaining to the SVPs of soil attributes. These data can be used to generate digital elevation and soil attribute variability maps at the field scale in a crop production environment. Based on the generated variability maps, locally available and economically feasible agricultural inputs can be applied using variable rate application strategies for sustainable cropping and enhanced farm profit. This overview presents the potential of adopting PSS in India and other developing countries. The scope, challenges, and probable solutions are also proposed. There is ample scope for adoption of PSS in India in view of diverse soil types, climatic conditions, cropping patterns, crop management practices, and ultimately, the ever-increasing demand for higher agricultural production. However, the successful adoption of the PSS technique in India will be dependent on the proper design and adoption of strategies which require adequate planning and analysis. There are several studies that have highlighted the usefulness of soil sensing technologies in Indian soils. There are also certain challenges and limitations associated with PSS in India, which could be addressed. The available proximal soil sensing technologies will be of great help in improving the understanding of soil heterogeneity for adopting SSSNM in order to optimize crop production in India and other developing countries.

Among the micronutrients, Zinc (Zn) is one of the essential nutrient due to its involvement in many metabolic processes in plant. The research was conducted to optimize Zn seed priming treatments for improving the yield attributing traits and crop yield of pea and maize crops. Different priming levels of Zn (water soaking- without zinc, 1%, 2% and 3% ZnSO₄), were applied with three priming durations (4, 8 and 12 hours). The priming treatments were compared with basal dose of recommended NPK + ZnSO₄ @ 25 kg ha⁻¹ and farmers’ practice (40% N of RDF + unprimed seed- control). The results showed that seed priming with 1% ZnSO₄ for 12 hours solution increased yield attributing traits (length of pea pods, number of pods/plant, number of grains/pod and shelling in pea pods) and yield of green peas, however in maize crop yield attributing traits (length of maize cobs, number of cobs/plant, number of grains/cob, shelling in maize cobs, girth of maize cobs and 1000-grain weight of maize) and yield were found maximum due to priming with 2% for 12 hours duration.

The quantification of soil properties and their spatial distribution is imperative for increasing crop productivity and suggesting the appropriate management strategies. The present study is based upon the hypothesis that the geologically complex landscape of the Indian Himalayan Region may lead to the varied distribution of the soil properties. This study appraises the influence of complex geological environment on some of the selected soil properties, viz., soil pH, electrical conductivity, organic carbon, nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg) and diethylene triamine penta acetic acid-extractable micronutrients, viz., zinc (Zn), iron (Fe), manganese (Mn) and copper (Cu) by delineating their spatial dependency using the geostatistical approach. The surface maps were prepared using the ordinary kriging technique along with semivariogram modelling. The value of the coefficient of variation for the calculated soil properties ranged from low to high (10.99% to 62.83%), indicating the heterogeneous application of fertilisers, management practices and land-use pattern. The principal component analysis aggregates the variability into four principal components. The nugget-to-sill ratio of soil properties, ranging from 25% to 75%, indicates the moderate dependency. The surface maps represent the influence of the complex geological environment on the spatial distribution of soil physico-chemical properties. The results also reveal that the variations in the soil properties were mainly due to the combined effect of intrinsic as well as extrinsic factors. The spatial distribution maps can be used for site-specific nutrient intervention for better resource management and environmental protection.

International Journal of Current Microbiology and Applied Sciences ISSN:2319-7692(Print), ISSN:2319-7706(Online) is a multidisciplinary peer-reviewed journal with reputable academics and experts as members of its Editorial Board. The Current Microbiology aims to publish all the latest and outstanding research articles. Review and letters in all areas of major importance to techniques of microbiology and applied research with publishes high quality of review and research articles on novel aspects of Microbiology including Environmental, Food, Agricultural, Medical, Pharmaceutical, Veterinary, Soil, Water and Biodeterioration.