Nutrient Expert for High Yield and Use Efficiency in Rainfed Bt Cotton Hybrids

Autor: D. Blaise, T. Satyanarayana, Sudarshan Dutta, A. Manikandan, Bhargavi Bussa
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Frontiers in Agronomy, Vol 3 (2021)
ISSN: 2673-3218
Popis: Low cotton productivity in the rainfed cotton grown in central India is attributed to abiotic (water and nutrients) and biotic (insect pests and diseases) stress. Nutrient stress can be overcome by providing nutrients in right amounts and at the right time when the plant needs the most. Field studies in cereal crops have demonstrated fertilizer recommendations by using the Nutrient Expert® (NE) decision support system to improve crop yields. However, such information in the case of the commercial crop, cotton, is scarce. Therefore, on-farm trials were conducted in three districts of Maharashtra, India during 2018–2020 with the hypothesis that the NE-based fertilizer recommendation would lead to higher cotton productivity and savings in fertilizer. Averaged over two seasons and locations, lint yield was significantly greater in the NE based than the recommended dose of fertilizer (RDF), soil test crop response (STCR), and farmers' practice (FP). Internal utilization efficiency (IE) did not differ among treatments for N (4.8 to 5.9 kg lint kg−1 nutrient uptake) and K (6.7 to 7.2 kg lint kg−1 nutrient uptake). With regard to the fertilizer P applied, the FP treatment had the least IE (17.0 kg lint kg−1 nutrient uptake) and was significantly lower than the other treatments. Partial nutrient balance (PNB) did not vary among treatments for applied fertilizer N. The FP treatment had PNB < 1 in case of fertilizer P and ~20 in the case of fertilizer K. This indicates farmers applied excess of P fertilizers. On the other hand, farmers in the region applied very small amount of K. Although the NE treatment had the highest cost of cultivation, net returns were the greatest followed by the STCR and RDF treatments. Our studies demonstrate that the NE-based fertilizer recommendation is not only productive, but also profitable.
Databáze: OpenAIRE