Design and Implementation of Crop Recommendation Fertilization Decision System Based on WEBGIS at Village Scale - Computer and Computing Technologies in Agriculture IV - Part II Access content directly
Conference Papers Year : 2011

Design and Implementation of Crop Recommendation Fertilization Decision System Based on WEBGIS at Village Scale

Abstract

To study crop recommendation fertilization of the rural farmers as the main in our country, the paper took towns and villages of Hua County as the study area, took recommendation fertilization of wheat, maize and peanut as the study object, designed model components of crop balance fertilization by using Object-Oriented technique, and developed the decision-making system about crop recommendation fertilization based on ArcGIS Server at village scale. The decision-making system realized farmland nutrient management and fertilization recommendations decision-making according to soil output capacity, agricultural production level and crop target yield. It was successfully applied in crop production in Hua County. The research results show that the system has the characteristic of better expansibility than before, and it is significantly simple and practical to reduce crop production cost and increase agricultural production efficiency, which provides technical support for crop fertilization decision-making and is significant to improve agricultural ecological environment and increase the comprehensive production capacity of farmland.
Fichier principal
Vignette du fichier
978-3-642-18336-2_44_Chapter.pdf (371.88 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01562771 , version 1 (17-07-2017)

Licence

Attribution

Identifiers

Cite

Hao Zhang, Li Zhang, Yanna Ren, Juan Zhang, Xin Xu, et al.. Design and Implementation of Crop Recommendation Fertilization Decision System Based on WEBGIS at Village Scale. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.357-364, ⟨10.1007/978-3-642-18336-2_44⟩. ⟨hal-01562771⟩
41 View
172 Download

Altmetric

Share

Gmail Facebook X LinkedIn More