Risk Assessment of Cold Damage to Maize Based on GIS and a Statistical Model

All published articles of this journal are available on ScienceDirect.

RETRACTED ARTICLE

Risk Assessment of Cold Damage to Maize Based on GIS and a Statistical Model

The Open Biotechnology Journal 02 Nov 2015 RETRACTED ARTICLE DOI: 10.2174/1874070701509010236

Abstract

Cold damage to maize is the primary meteorological disaster in northwest China. In order to establish a comprehensive risk assessment model for cold damage to maize, in this study, risk models and indices were developed from average daily temperature and maize yield and acreage data in 1991-2012. Three northwest provinces were used to calculate the temperature sum during the growth period, temperature departure over the years and relative meteorological yield in order to obtain the climate risk index, risk sensitivity index and damage assessment index. Using the geographic information system (GIS) and cold damage risk indices obtained from the statistical assessment model, the studied area was divided into four risk regions: low, medium, medium-high and high. Northeast and southwest Gansu were grouped to the high-risk region; west Shaanxi and north NHAR were grouped into to the low-risk region; all other areas fell into medium and medium-high risk regions. Our results can help growers avoid cold damage to maize using local climate data and optimize the structure and layout of maize planting. It is of significance in guiding the agricultural production in the three northwest provinces in China and also can serve as a reference in modeling risk assessment in other regions.

Keywords: Maize, climate, cold damage, risk assessment, geographic information system (GIS).