MISSISSIPPI SOYBEAN PROMOTION BOARD PROJECT NO (YEAR 3) FINAL REPORT

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1 MISSISSIPPI SOYBEAN PROMOTION BOARD PROJECT NO (YEAR 3) FINAL REPORT Title: Identifying Irrigation Scheduling Tools that Maintain Soybean Yield and Improve Soybean Irrigation Water Use Efficiency in Clay Textured Soils PI: L. Jason Krutz, Associate Research/Extension Professor, MAFES-DREC Cooperators: Trent Irby, Bobby Golden, Lyle Pringle, Larry Falconer EXECUTIVE SUMMARY Adoption of a soybean irrigation scheduling tool that maintains yield while improving irrigation water use efficiency (WUE) relative to FAO56, a national standard for irrigation scheduling, can result in reduced agricultural water withdrawal from the Mississippi Alluvial River Valley Aquifer (MARVA). The objective of this study was to determine if two checkbook irrigation scheduling tools (Arkansas Irrigation Scheduler, atmometer) or a direct measurement of soil moisture with a watermark sensor could maintain soybean yield while improving WUE relative to FAO56. Field studies were conducted in on a Sharkey clay (very fine, smectitic, thermic, Chromic Epiaqert) with four replications of each treatment arranged in a randomized complete block design. A 5-cm soil water deficit was allowed for FAO56, Arkansas Irrigation Scheduler, and the atmometer method. Watermark irrigation thresholds were -50 cbar in 2012, -125 cbar in 2013, and -100 and -125 cbar in Relative to FAO56, the checkbook approaches maintained soybean yield and scheduled the same number of irrigation events, but had no effect on WUE regardless of year. Similarly, soybean yield, number of irrigation events, and WUE were not different between -50 cbar and FAO56. Conversely, when compared to FAO56, an irrigation threshold of -100 cbar maintained yield, reduced irrigation events by 50%, and improved WUE by 145%. Extending the irrigation threshold to -125 cbar also reduced irrigation events and improved WUE relative to FAO56, but soybean yield was reduced by at least 21%. Results from this study indicate that a soil moisture threshold of approximately -100 cbar in a clay-textured soil will maintain soybean yield, reduce withdrawal from the MARVA, and improve soybean WUE relative to FAO56.

2 INTRODUCTION Groundwater is the primary irrigation water source in the Mississippi Delta region, where over the past three decades the number of agricultural wells has increased exponentially (Mississippi Department of Environmental Quality, Personal Communication). Agricultural withdrawal has exceeded aquifer recharge rates, causing a decline in groundwater levels in the Mississippi Alluvial River Valley aquifer (MARVA) (Guzman et al. 2014). Currently, and for the foreseeable future, soybean is grown on the majority of the Mid-South s irrigated acres. Scheduling methods to reduce agricultural withdrawal from the MARVA for soybean irrigation are needed to assure sustainability of this water resource. The utilization of scientific irrigation scheduling tools can improve soybean yield and reduce aquifer withdrawal, but the adoption of scheduling tools by producers regionally and nationally is minimal. For example, survey data from southeast Missouri producers indicate that soybean managed by irrigation scheduling out-yielded non-scheduled soybean by 3.3 bu/ac (Henggeler 2003). In Mississippi, irrigation water applied to soybean when managed with a scheduling tool was reduced by 30% compared to soybean not managed with an irrigation scheduling tool (L.J. Krutz, personal observation). Unfortunately, the adoption of scientific irrigation scheduling tools, even in regions with severe water shortages occur, is less than 2% (Frisvold and Deva 2012). Moreover, there is a paucity of data regarding appropriate scientific irrigation scheduling tools from Mid-South soybean production areas. The objective of this study is to compare soybean yield, number of irrigations, and soybean WUE between FAO56, two checkbook approaches (Arkansas Irrigation Scheduler and atmometer method), and a direct soil moisture measurement (watermark soil moisture sensor) technique. We submit that there is potential to identify a scheduling tool that maintains or improves soybean yield while concurrently reducing irrigation events and improving soybean WUE relative to FAO56, a national standard with regard to irrigation scheduling. Experiment location and design MATERIALS AND METHODS Field studies were conducted in on a Sharkey clay (very fine, smectitic, thermic, Chromic Epiaqert) that had been tilled with a disk-harrow in the fall; i.e., stale seedbed. Treatments including non-irrigated, FAO56, Arkansas Irrigation Scheduler (AIS), atmometer, and Watermark soil moisture sensor (WM) were arranged in a randomized complete block with four replications of each treatment. Row spacing was 40 inches, seeding rate was 140,000 seed/acre, and experimental units were 100 ft long by 480 ft (12 rows) wide. Variety and planting date were HALO 494 on 5/15/2012, 494LL on 6/20/2013, and 95LO1 on 5/7/2014. Premergence and postmergence herbicides were broadcast-applied at labeled rates. Irrigation was applied to the middle four rows of each experimental unit by the furrow method via polytubing. From , irrigation was applied to checkbook approaches including FAO56, AIS, and atmometer when a two-inch soil moisture deficit occurred. Irrigation threshold for WM was -50 cbar in 2012, -125 cbar in 2013, and -100 and -125 cbar in Yield data

3 were collected from the middle two rows each year. Data on rainfall, relative humidity, and maximum and minimum temperatures were obtained from the Stoneville weather station. Data analysis Data were subjected to analysis of variance using SAS PROC MIXED and means separated via PDMIX8000. Rainfall data RESULTS AND DISCUSSION Cumulative rainfall from April through October during was at least 17% higher than long-term rainfall averages for Stoneville MS; however, soybean drought stress did occur at some point during each growing season from , where irrigation was required to achieve maximum yield potential (Figure 1). In 2012, May and September rainfall was at least 13% lower than long-term averages, while rainfall during all other months within the growing season was at least 30% higher than the long-term average. During 2013, July and August rainfall was at least 14% lower than historic rainfall averages, while rainfall for all other months was equivalent to or at least 100% higher than long-term averages. In 2014, with the exception of September, rainfall during all months was at least 12% higher than long-term averages site year Irrigation, independent of scheduling tool, improved soybean yield by at least 34% (Table 1). Compared to FAO56, the number of irrigation events, soybean yield, and WUE were not different from that of AIS and atmometer. Similarly, there were no differences in number of irrigation events, soybean yield, and WUE between FAO56 and WM at the -50 cbar threshold site year Irrigation, independent of scheduling tool, improved soybean yield by at least 68%. Number of irrigation events, yield, and WUE differences among scheduling tools were evident, however (Table 2). The number of irrigations for checkbook approaches were not different from that of FAO56. Conversely, WM at -125 cbar had two less irrigation events than FAO56. With exception of a 10% yield increase for soybean managed with AIS, soybean yield among checkbook approaches was not different from that of FAO56. Soybean yield for WM at the -125 cbar threshold was 28% lower than that of FAO56. Soybean WUE values for all checkbook approaches were not different from that of FAO56; conversely, WUE values for WM at the -125 cbar threshold were 60% greater than that of FAO site year With the exception of WM at the -125 cbar threshold, irrigation improved soybean yield by at least 8.4%. Similar to 2013, differences in number of irrigation events, yield, and WUE among

4 scheduling tools were measured. Number of irrigation events for the checkbook approaches were not different from that of FAO56. Conversely, WM at the -100 cbar and the -125 cbar thresholds received 2 and 3 less irrigations than FAO56, respectively. Soybean yield for checkbook and WM measurement approaches were not different from that of FAO56. Soybean WUE for all checkbook approaches was not different from that of FAO56; conversely, WUE values for WM at the -100 cbar and -125 cbar thresholds were 145 and 210% higher than that of FAO56, respectively. CONCLUSIONS The objective of this study was to identify an irrigation scheduling tool that would maintain soybean yield while improving WUE in clay textured soils compared to FAO56. Irrigation, regardless of scheduling tool, improved soybean yield by at least 8%. From , evaluated checkbook approaches had similar number of irrigation events, soybean yield, and soybean WUE values compared to FAO56. Conversely, only WM -100 cbar reduced irrigation events, maintained soybean yield, and improved soybean WUE relative to FAO56. Our data indicate that irrigation scheduling tools based on direct soil measurement may be able to maximize soybean yield while improving soybean WUE relative to FAO56. Literature Cited Frisvold, G.B. and S. Deva Farm Size, irrigation practices, and conservation program participations in the US Southwest. Irrig. Drain. 61: Guzman, S.M., J.O. Paz, M.L.M. Tagert, and R. Wu A neural network framework to estimate groundwater levels in the Mississippi River Valley shallow alluvial aquifer. Am. Soc. Ag. Bio. Eng. Annual Int. Meeting 3: Henggeler, J.C Bootheel Irrigation Surveys from as found at:

5 Total Rainfall (mm) Apr May June July Aug Sep Oct Months in the growing season Figure 1. Total rainfall in mm for Stoneville, MS from April through October during 2012, 2013, and 2014 growing seasons.

6 Table 1. Irrigation water added, yield (kg/ha), and irrigation water use efficiency (WUE) for non-irrigated, FAO56, Arkansas Irrigation Scheduler, atmometer, and watermark -50 cbar threshold during 2012 growing season. A 5-cm soil water deficit was allowed for FAO56, Arkansas Irrigation Scheduler, and atmometer methods. Scheduling tool Irrigation water Yield WUE a ----mm---- kg/ha kg yield/mm Non-irrigated b b FAO a 3.1 a Arkansas Irrigation Scheduler a 3.1 a Atmometer a 3.1 a WM a 3.1 a a = Water use efficiency = yield (kg/ha) / irrigation water applied (mm) b = numbers followed by same letter are not significantly different at p=0.05. Table 2. Irrigation water added, yield (kg/ha), and irrigation water use efficiency (WUE) for non-irrigated, FAO56, Arkansas Irrigation Scheduler, atmometer, and watermark -125 cbar threshold during 2013 growing season. A 5-cm soil water deficit was allowed for FAO56, Arkansas Irrigation Scheduler, and atmometer methods. Scheduling tool Irrigation water Yield WUI a ----mm---- kg/ha kg yield/mm Non-irrigated d b FAO b 2.5 b Arkansas Irrigation Scheduler a 2.8 b Atmometer b 2.5 b Watermark -125 cbar c 3.8 a a = Water use efficiency = yield (kg/ha) / irrigation water applied (mm) b = numbers followed by same letter are not significantly different at p=0.05. Table 3. Irrigation water applied, yield (kg/ha) and irrigation water use efficiency (WUE) for non-irrigated, FAO56, Arkansas Irrigation Scheduler, atmometer, and watermark -100 cbar threshold, and watermark -125 cbar threshold for 2014 growing season. A 5-cm soil water deficit was allowed for FAO56, Arkansas Irrigation Scheduler, and atmometer methods. Scheduling tool Irrigation water Yield WUE a ----mm---- kg/ha kg yield/mm Non-irrigated c b FAO ab 4.1 c Arkansas Irrigation Scheduler a 4.1 c Atmometer a 4.2 c Watermark -100 cbar ab 7.9 b Watermark -125 cbar bc 15.4 a a = Water use efficiency = yield (kg/ha) / irrigation water applied (mm). b = numbers followed by same letter are not significantly different at p=0.05.