Studying the impact of climate and technology variables on maize productivity in Punjab using GIS
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Date
2019
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Punjab Agricultural University, Ludhiana
Abstract
Climate change has resulted in the variation of temperature and precipitation, affecting the crop production and productivity. A study therefore has been planned to examine the impact of climate and technology variables on maize productivity in Punjab using GIS. Long-term data (1971-2017) on maize yield, fertilizer consumption and maize gross irrigated area was collected from statistical abstracts of Punjab and long-term climatic data on maximum temperature, minimum temperature and rainfall during the maize growing period was collected from Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana, different research stations of PAU, India Meteorological Department, New Delhi and different websites. The maize yield increased in all the districts and the rate of increase was highest at Patiala (74.3 kg year-1). Significant increase has been observed in minimum temperature during maize growing period in all the maize growing districts, whereas no significant trend has been observed in maximum temperature and rainfall, although large year to year variations have been observed. Significant increase in fertilizer consumption in all the districts of the state was observed except Amritsar, where no trend was observed. Significant decrease has been observed in maize gross irrigated area in all the maize growing districts except Hoshiarpur and Roopnagar where the trend increased. The Mann-Kendall test results revealed that long term (1971-2017) seasonal variability showed the increase in minimum temperature in Gurdaspur, Hoshiarpur, Kapurthala and Roopnagar @ 0.04°C year-1 and increase in maximum temperature in Hoshiarpur, Kapurthala, Patiala and Roopnagar @0.03°C year-1. Temporal seasonal variability showed the decrease in maximum temperature in Jalandhar @ -0.14°C year-1 and increased in Patiala @ 0.10°C year-1 during 2001-2010. Increase in minimum temperature in Gurdaspur @ 0.37°C year-1 was observed during 2001-2010. Stepwise regression showed that 95.3 per cent of the variance in maize yield was explained by minimum temperature and 2.8 per cent by fertilizers. Inverse distance weighted method in Arc GIS 10.4 was used to show the spatial variability in maize productivity, technology variables and weather parameters during its growing period.
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