[Spatial variability and quantitative analysis of field factors based on GIS]

Area of Science:

• Agricultural Science
• Soil Science
• Agronomy

Background:

• Understanding spatial variability in soil nutrients is crucial for optimizing crop production.
• Crop growth status indicators like SPAD and Leaf Area Index (LAI) are vital for yield prediction.

Purpose of the Study:

• To investigate spatial variability and quantitative relationships among soil nutrients, crop growth status, and rice yield.
• To evaluate the efficacy of geostatistics and GIS in analyzing these relationships.

Main Methods:

• Classical statistics and geostatistics based on GIS were employed for data analysis.
• Soil properties (pH, total N, organic matter, available P, available K) and crop growth indicators (SPAD, LAI, SPAD x LAI) were measured.
• Kriged interpolation maps were generated to visualize spatial patterns.

Main Results:

• Most soil parameters (except pH) and crop growth indicators exhibited significant spatial correlation.
• Soil total N, organic matter, SPAD, LAI, and SPAD x LAI were all correlated with rice yield.
• Kriged maps effectively illustrated spatial variability in yield and crop growth.

Conclusions:

• The combined metric SPAD x LAI is a more sensitive indicator of crop growth status than individual measurements.
• Spatial analysis using GIS and geostatistics aids in understanding yield-determining factors.
• These findings support precision agriculture practices, enabling timely interventions like topdressing.