外文摘要：Protein hydrolysates (PHs) derived from waste materials are promising for sustainable practices in agricultural production. This study evaluated the effects of PH enzymatically derived from anchovy by-products on the root system architecture (RSA) and aboveground development of potted primrose. The plants were treated with 0.5, 1.0, and 1.5 g/L concentrations of PH by drenching with 100 mL/pot at two-week intervals and irrigated once a week with 100 mL/pot during winter and twice weekly during spring. The results revealed that the 1.5 g/L treatment statistically significantly improved dry weight and leaf area, while the highest leaf chlorophyll content was observed with the 1.0 g/L treatment. The treatments did not influence leaf and flower numbers. Treatment with 1.0 g/L produced the most substantial improvement in root surface area, projected area, volume, length, tips, and forks. Additionally, the study employed machine learning (ML) algorithms, including GP, RF, XGBoost, and an ANN-based MLP. The input variables (root surface area, projected area, volume, length, tips, and forks) were assessed to model and predict the root traits. The ML and ANN algorithms' R-squared rates were noted in the following order: MLP > GP > RF > XGBoost. These outcomes hold significant implications for enhancing primrose growth.
外文关键词：machine learning;Sustainability;image analysis;amino acids;ornamental plant;root development;fish waste
作者：Tutuncu, Mehmet
作者单位：Ondokuz Mayis Univ
期刊名称：HORTICULTURAE
期刊影响因子：0.0
出版年份：2024
出版刊次：10（4）
原文传递申请：江苏省科技资源（工程技术文献）统筹服务平台