Hybrid Modeling and Management of Lodging in Subtropical Fiber Flax: Optimizing Plant Nutrition for Sustainable Cultivation
| Autor: | Suhita Pyne, M.S. Negi, B.S. Mahapatra, Ajay Kumar, Prithwiraj Dey, Pramit Pandit |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Journal of Natural Fibers, Vol 21, Iss 1 (2024) |
| Druh dokumentu: | article |
| ISSN: | 15440478 1544-046X 1544-0478 05858240 |
| DOI: | 10.1080/15440478.2024.2394139 |
| Popis: | Subtropical fiber flax faces significant challenges due to crop lodging, exacerbated by the high N regimes needed for increased fiber production. This study examines impact of balanced P and K applications under varied N regimes on lodging resistance, fiber yield, and quality of flax. Field experiments with 12 NPK treatments revealed that while 120:19:38 kg N, P, K ha−1 achieved highest plant height, stem-diameter, and fresh-weight while increased lodging percentage and reduced fiber quality when P and K were not balanced. Conversely, balanced P and K applications mitigated negative effects of high N, significantly reducing lodging and enhancing fiber yield, quality. Optimal fiber quality, including fiber length and bundle tenacity, was observed with 90:19:38 kg N, P, K ha−1. The novelty of this study lies in integration of stochastic and ML approaches to develop hybrid models for lodging. By combining LASSO with ANN, NLSVR, and RF techniques, hybrid models outperformed individual models in lodging prediction. Specifically, LASSO-NLSVR provided most accurate predictions due to its nonlinear mapping capabilities. Key predictive factors included fiber content, linear density, and tensile strength at 60 days post-sowing, offering valuable insights for breeders and agronomists to improve flax lodging resistance and fiber quality in subtropical climates. |
| Databáze: | Directory of Open Access Journals |
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