In:
Agriculture, MDPI AG, Vol. 10, No. 11 ( 2020-11-09), p. 538-
Abstract:
Recent developments in the controlled-release fertilizer (CRF) have led to the new modern agriculture industry, also known as precision farming. Biopolymers as encapsulating agents for the production of controlled-release fertilizers have helped to overcome many challenging problems such as nutrients’ leaching, soil degradation, soil debris, and hefty production cost. Mechanistic modeling of biopolymers coated CRF makes it challenging due to the complicated phenomenon of biodegradation. In this study, a machine learning model is developed utilizing Gaussian process regression to predict the nutrient release time from biopolymer coated CRF with the input parameters consisting of diffusion coefficient, coefficient of-variance of coating thickness, coating mass thickness, coefficient of variance of size distribution and surface hardness from biopolymer coated controlled-release fertilizer. The developed model has shown greater prediction capabilities measured with R2 equalling 1 and a Root Mean Square Error (RMSE) equalling 0.003. The developed model can be utilized to study the nutrient release profile of different biopolymers’-coated controlled-release fertilizers.
Type of Medium:
Online Resource
ISSN:
2077-0472
DOI:
10.3390/agriculture10110538
Language:
English
Publisher:
MDPI AG
Publication Date:
2020
detail.hit.zdb_id:
2651678-0
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