Integrated nutrient management for okra in an inceptisol of eastern India and yield modeling through artificial neural network

Phonglosa, Amit; Bhattacharyya, Kallol; Ray, Krishnendu; Mandal, Jajati; Pari, Arnab; Banerjee, Hirak; Chattopadhyay, Arup

Abstract

Present investigation has been conducted to assess the efficiency of few selected and simulated options of integrated nutrient management and plant growth regulator in improving okra growth and increasing okra yield (Abelmoschus esculentus L. Moench) in an inceptisol at Gayeshpur, West Bengal, India (23° N 89° E at 9.75 m above MSL). The experimental soils were neutral, non-saline, sandy loam, low in organic carbon, available N, DTPA extractable micronutrients, moderate in available P and medium in available K contents. The experiment was laid out in an asymmetric factorial design with seven different treatments of integrated nutrient management (INM) and two levels of gibberellic acid (GA). Okra yield, macro and micronutrients uptake by okra pod, available nutrient status in post-harvest soil were observed to increase significantly when chemical N and P were supplemented by organic manures and/or bacterial fertilizers along with application of GA. Application of 75% of NP + total K through chemical fertilizers along with Azospirillum, PSB, VAM and FYM restored highest soil nutrient availability and okra pod nutrient accumulation. Highest okra yield and best economic return could be achieved when PSB and FYM were used to supplement 75% of N, P + total K. Okra yield models, developed through artificial neural network (ANN), clearly indicated the manifest role of soil and okra pod N, P, Zn, Fe and Mn in increasing productivity under interventions of bacterial fertilizers (PSB and VAM).

Citation

Phonglosa, A., Bhattacharyya, K., Ray, K., Mandal, J., Pari, A., Banerjee, H., & Chattopadhyay, A. (2015). Integrated nutrient management for okra in an inceptisol of eastern India and yield modeling through artificial neural network. Scientia Horticulturae, 187, 1-9. https://doi.org/10.1016/j.scienta.2015.02.037

• Journal Article Type: Article
• Acceptance Date: Feb 16, 2015
• Publication Date: 2015-05
• Deposit Date: Sep 2, 2023
• Journal: Scientia Horticulturae
• Print ISSN: 0304-4238
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 187
• Pages: 1-9
• DOI: https://doi.org/10.1016/j.scienta.2015.02.037
• Keywords: Horticulture