In the Southeast, winter wheat (Triticum aestivum L.) is typically planted from late October to early December. However, grain yield is reduced by an interaction of weather, soil, and plant factors. From 2009 to 2012 a study was conducted at three locations in Alabama to evaluate the seeding date effect on yield and yield components of three cultivars. The AGS 2060, AGS 2035, and Baldwin cultivars were evaluated within four seeding dates at approximately 15‐d intervals. Results showed that grain yield, spikes per m², and kernel weight declined linearly with seeding delay; however, the impact changed among years and locations within a year. The variability of kernels per spike was location specific, in the north delayed planting resulted in a greater number of kernels per spike while the opposite occurred at the central and southern locations. At most location–year combinations, seeding 2 to 4 wk later than the Extension’s best seeding date resulted in yield losses; especially if warm and dry conditions were prevalent during winter and spring months at locations with sandy loam soils. Under warm and dry growing conditions, the impact of delayed planting on yield and kernel weight was the greatest for Baldwin and AGS 2035 and least for the AGS 2060. In contrast, when cold and wet growing conditions were prevalent, there were not significant planting date differences on yield and yield components. Cultivar and seeding date should be selected on a location basis due to the plant interactions with soil and weather factors.

Adoption of water-conservation irrigation practices could potentially reduce water and energy use and increase profitability, as well as protect the environment. Precision irrigation consisting of soil sensors (SS) for irrigation scheduling and variable rate irrigation (VRI) was compared with conventional uniform irrigation (URI). The study was conducted in South Alabama during the 2018 and 2019 corn growing seasons. The SS-VRI and URI treatments spanned the length of the field and were compared across five different management zones (MZ) that exhibited soil and terrain differences. Soil water tension sensors were installed on each MZ-treatment area to monitor hourly soil water changes. Results showed that on the two zones covering 55% of the study field, MZ 1 and MZ 2, the SS-VRI treatment, on a two-year average, resulted in 26% less irrigation water applied compared to the URI treatment; however, there were no statistical differences between yields or yield variability among treatments. Even though in MZ 4, there was not a substantial difference in irrigation water applied among treatments, soil sensors increased the precision of irrigation rate determination during the peak of high crop water demand. Findings from this study showed that as rainfall amount and distribution change over a crop growing period, soil sensor-based irrigation scheduling could be used to prevent over- or under irrigation. With proper management, the combination of soil sensors and VRI provides farmers with the opportunity to reduce water use, while increasing or maintaining yields; however, farmers must consider the investment and operating costs relative to the benefits.

Highlights Corn response to irrigation was influenced by the precipitation distribution in 2018 and 2019, and that impacted the response of CWSI as an irrigation scheduling signaling method. CWSI was sensitive to changes in soil water storage, increasing due to crop evapotranspiration and decreasing after a precipitation or irrigation event. In 2018, both seasonal CWSI and yield were not different among the irrigation treatments, while in 2019, seasonal CWSI and yield were all statistically different among the treatments evaluated. Post analysis of canopy and air temperature indicated that the temperature-time threshold (TTT) method might not appropriately signal crop water stress in a humid environment. Abstract. Irrigation scheduling based on the crop water stress index (CWSI) and temperature-time threshold (TTT) methods is promising for semi-arid and arid climates. The objective of this study was to investigate if CWSI and TTT methods could be used as irrigation signaling tools for a humid environment in the southeastern U.S. Corn canopy temperature data were collected in Alabama in 2018 and 2019 using infrared leaf temperature sensors on a fully irrigated treatment and on two limited irrigation treatments. A set of three soil water sensors installed at 0.15, 0.3, and 0.6 m soil depth were used to prescribe irrigation time and amount. CWSI was sensitive to precipitation, irrigation, and plant water uptake. No statistical differences in CWSI or yield among the three irrigation levels were found in 2018 when precipitation was well distributed during the season. In contrast, during 2019 both CWSI and yield differed significantly among the three irrigation treatments. Precipitation events in 2019 were sparse compared to 2018; therefore, irrigation promoted greater differences in water availability between treatments. Inconsistencies observed in potential irrigation signaling using the TTT method with or without the inclusion of a limiting relative humidity algorithm indicate that the TTT method may not be a reliable irrigation signaling tool for humid environments. Keywords: Corn yield, Crop water stress index, Irrigation scheduling, Limiting relative humidity, Soil water depletion, Temperature-time threshold.