Spatial and Temporal Trends of Irrigated Cotton Yield in the Southern High Plains

Wenxuan Guo

doi:10.3390/agronomy8120298

Abstract

Understanding spatial and temporal variability patterns of crop yield and their relationship with soil properties can provide decision support to optimize crop management. The objectives of this study were to (1) determine the spatial and temporal variability of cotton (Gossypium hirsutum L.) lint yield over different growing seasons; (2) evaluate the relationship between spatial and temporal yield patterns and apparent soil electrical conductivity (ECa). This study was conducted in eight production fields, six with 50 ha and two with 25 ha, on the Southern High Plains (SHP) from 2000 to 2003. Cotton yield and ECa data were collected using a yield monitor and an ECa mapping system, respectively. The amount and pattern of spatial and temporal yield variability varied with the field. Fields with high variability in ECa exhibited a stronger association between spatial and temporal yield patterns and ECa, indicating that soil properties related to ECa were major factors influencing yield variability. The application of ECa for site-specific management is limited to fields with high spatial variability and with a strong association between yield spatial and temporal patterns and ECa variation patterns. For fields with low variability in yield, spatial and temporal yield patterns might be more influenced by weather or other factors in different growing seasons. Fields with high spatial variability and a clear temporal stability pattern have great potential for long-term site-specific management of crop inputs. For unstable yield, however, long-term management practices are difficult to implement. For these fields with unstable yield patterns, within season site-specific management can be a better choice. Variable rate application of water, plant growth regulators, nitrogen, harvest aids may be implemented based on the spatial variability of crop growth conditions at specific times.

Highlights

For precision agriculture (PA) to be applicable, identifiable and measurable within-field variability in soil properties and plant growth and yield should exist [1]
The application of electrical conductivity (ECa) for site-specific management is limited to fields with high spatial variability and with a strong association between yield spatial and temporal patterns and ECa variation patterns
For fields with low variability in yield, spatial and temporal yield patterns might be more influenced by weather or other factors in different growing seasons

Summary

Introduction

For precision agriculture (PA) to be applicable, identifiable and measurable within-field variability in soil properties and plant growth and yield should exist [1]. Interpreting multiple years of yield maps may be challenging because yield variability may be caused by many factors, including spatial variability in soil type, landscape position, crop history, soil physical and chemical properties, and water and nutrient variability [4]. Interactions among biotic (plant genotype, soil fauna, pests, and diseases) and abiotic factors (soil physical, chemical, moisture characteristics, and climatic conditions) influence yield variability. Pests, and diseases are temporal factors that could explain up to 50% of yield variability across years and sites [5]. With multiple years of yield data, repeating patterns and their more stable natural causes may be separated from random variability within each year [3]. The relative productivity pattern that remains stable from year to year and crop-to-crop

Objectives

Results

Discussion

Conclusion