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

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.

Mapping the Depth-to-Soil pH Constraint, and the Relationship with Cotton and Grain Yield at the Within-Field Scale

“…In contrast, the wheat yield maps in 2016 and the cotton yield maps in 2017/2018 showed some differing spatial patterns, with some of the highest yielding areas for cotton being the lowest yielding for wheat. These inconsistently yielding or flip-flop patterns have been commonly observed in other studies [45][46][47], and often point to a temporary constraint, rather than a permanent soil constraint such as high soil pH levels. Despite the important role that soil pH plays on crop productivity, few studies have looked at the impact of within-field soil pH variability on crop yield, let alone how the depth-to-soil pH constraint relates to this.…”

Predicting within‐field cotton yields using publicly available datasets and machine learning

“…Within-field cotton yield can vary due to a multitude of factors, including soil properties, localized pests and diseases, and management (Chen et al, 2018;Li et al, 2008;Ping et al, 2007). Yield can also vary year-to-year within the same field due to differences in climate and management; such as fertilizer, irrigation, rotation, and cultivar Wenxuan, 2018). Current in-season yield estimations in cotton are based on boll counting within a small subsection of the field (Sun et al, 2019).…”