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Water scarcity is increasing in the world, which is limiting crop production, especially in water-limited areas such as Southern High Plains of the United States. There is a need to adopt the irrigation management practices that can help to conserve water and sustain crop production in such water-limited areas. A 2-year field study was conducted during the summers of 2019 and 2020 to evaluate the effect of deficit irrigation levels and cultivars on root distribution pattern, soil water depletion, and water use efficiency (WUE) of cucumber (Cucumis sativus). The experiment was conducted in a split-plot design with four irrigation levels [100%, 80%, 60%, and 40% crop evapotranspiration (ETc)] as main plot factor and two cultivars (Poinsett 76 and Marketmore 76) as subplot factor with three replications. Results showed that root length density (RLD) was unaffected by the irrigation levels in 2019. In 2020, the RLD was comparable between 100% and 80% ETc, and it was significantly higher in 100% ETc than both 60% Eand 40% ETc. Root surface area density (RSAD) was not significantly different between 100% and 80% ETc, and it was significantly lower in both 60% and 40% ETc than 100% ETc in both years. Soil water depletion was the highest in 40% ETc followed by 60% and 80% ETc, and it was least in 100% ETc in both years. Evapotranspiration (ET) was the highest in 100% ETc followed by 80%, 60%, and 40% ETc. The WUE was not statistically different among the irrigation treatments. However, numerically, WUE was observed in the following order: 80% ETc > 100% ETc > 60% ETc > 40% ETc. The RLD, RSAD, soil water depletion, and ET were not significantly different between ‘Poinsett 76’ and ‘Marketmore 76’. However, fruit yield was significantly higher in ‘Poinsett 76’ than ‘Marketmore 76’, which resulted in higher WUE in Poinsett 76. It can be concluded that 80% ETc and Poinsett 76 cultivar can be adopted for higher crop water productivity and successful cucumber production in SHP.

In Texas, mesquite and yellow-bluestem invasions are widespread. Identifying and monitoring juvenile and adult plants using high-resolution imagery from airborne sensors while they colonize new areas across the landscape can help land managers prioritize locations for treatment and eradication. In this study, we evaluated how data collection design using an unmanned aerial system (UAS) can affect plant detection and mapping. We used a Phantom 3 Professional unmanned aerial vehicle with a Parrot Sequoia multispectral camera for detecting and mapping native honey mesquite (Prosopis glandulosa) and non-native yellow bluestem (Bothriochloa ischaemum) at a rangeland site in northwest Texas. Flights were conducted seasonally during the period from summer 2017 to fall 2018 to test the seasonal impact of detecting plant species. Flights were conducted at altitudes of 30, 60, and 100 m, and four image classification techniques were tested to determine their viability of detecting distinct plant species. Results suggest that flights at 100-m aircraft altitude during the spring season are more effective (>80% user accuracies) for mapping mesquite canopies based on reflectance values and image segmentation information. Yellow bluestem mapping accuracies were low (

Conservation management practices such as no-tillage and cover cropping can reduce soil erosion, enhance soil biological activity, increase water capture and storage, and sequester C. Cover crops, however, utilize stored soil water during the winter months, and the water depletion is thought to have negative impacts on the subsequent cotton (Gossypium hirsutum L.) crop in semi-arid ecoregions where water resources are limited. The objective of this research was to quantify the long-term impacts of conservation tillage and cover crop use on volumetric water content of soil in an irrigated cotton production system. Soil water was measured in a long-term (established 1998) conservation system in Lamesa, TX and water dynamics during the 2015–2017 growing seasons are presented here. Volumetric water content was reduced by cover crops prior to their termination but was replenished by spring precipitation and deficit irrigation prior to planting cotton. A stepwise regression analysis was used to determine changes in soil water at depth. In each of the study years, soil water increased more with no-tillage following cover crop termination and decreased less during cotton growth than the conventionally tilled system. Cotton water use efficiency was not significantly different between treatments in any year. Results from this study challenge the concept that winter cover crops result in reduced in-season soil water in irrigated systems, a supposition that has limited adoption of conservation tillage and cover crop use on the Texas High Plains.

Cotton producers on the southern High Plains of Texas face reduced seasonal irrigation capacities as groundwater resources from the Ogallala Aquifer decline. Technological advancements have allowed producers to achieve maximal water use efficiencies (>95 %); however, new management strategies are necessary to sustain producer profitability. By determining the optimal timing of irrigation, producers may be able to conserve irrigation water and reduce their pumping expenses. In a field experiment conduced from 2010 to 2013, cotton (Gossypium hirsutum L.) lint yield and profitability were compared across 27 irrigation treatments using a LEPA irrigation system on Pullman Clay/Olton soils. Irrigation was applied during three growing periods determined by growing degree days (GDD15.6), where P1=emergence to 525 GDD15.6, P2 = 525–750 GDD15.6, and P3 > 750 GDD15.6. Treatments for the experiment included three irrigation capacities of 0, 3.2, and 6.4 mm d−1 in a randomized block design with three replications. Profitability was assessed by calculating gross margin from economic budgets that included the management operations from each year. On average, treatments with an irrigation capacity of 0 mm d−1 in P1 made 6 % less yield, but saved 30 % more water and generated the same profitability as the IC treatments of 3.2 mm d−1. Irrigation during P3 at the 6.4 mm d−1 irrigation capacity (IC) was the most critical for yield potential, generating 114 % more yield than the 0 mm d−1 IC and 27 % more than the 3.2 mm d−1 IC treatments, resulting in a 468 % and 110 % increase in profit, respectively.

Within the Ogallala Aquifer Region of Texas, the irrigation capacity (IC) for a given field often changes within a growing season due to seasonal depletion of the aquifer, in-season changes in crop irrigation needs in dry years, or consequences of irrigation volume limits imposed by irrigation district rules. Irrigation planning is further complicated by erratic seasonal rainfall. A field experiment was conducted from 2010 to 2013 to determine cotton ( L.) irrigation productivity using a range of ICs common to the Texas South Plains during three irrigation periods. The treatments included in-season ICs (maximums of 0, 3.2, and 6.4 mm d-1) in combination with irrigation periods determined by accumulated growing degree days (GDD15.6) and were designated as period 1 (P1= emergence to 525 GDD15.6), period 2 (P2= 525 to 750 GDD15.6), and period 3 (P3>750 GDD15.6). Combinations of these factor levels resulted in 27 irrigation treatments with applications made by the low energy precision application (LEPA) method. Annual rainfall totals ranged from 137 to 557 mm over the four years. In all years, results indicated that attempting to store water in the soil profile, or irrigating in excess of the cotton evapotranspiration rate, early in the growing season reduced seasonal irrigation water use efficiency (SIWUE), and sometimes yield, compared to treatments with limited or no early irrigations. Treatments with 0 and 3.2 mm d-1 ICs during P1 used up to 20% less seasonal irrigation with minor yield loss (

Petiole-NO3, leaf N and chlorophyll (SPAD) meter readings are good in-season indicators of the N status of the uppermost part of cotton (Gossypium hirsutum L.) plants. Petiole-NO3, particularly is widely used in the USA as an in-season plant N test that guides N fertilizer recommendations in cotton. However, these N status indicators do not take account of plant biomass, canopy width or percent cover. The objectives of this study were to assess the effect of N fertilizer rates on the commonly used indicators of plant N status; leaf N, petiole sap NO3 and chlorophyll meter (SPAD) readings and the plant growth measurements; plant height, canopy width, and percent ground cover, and determine to inter-correlations among the them. Irrigated field studies were conducted at Lubbock, TX USA in 2010 and 2011, New Deal, TX in 2010, and at Halfway, TX in 2011. Zero-N and a full N fertilizer rate of 134, 101, and 112 kg N ha−1 were used at Lubbock, New Deal, and Halfway, respectively. The 2010 cotton growing season in West Texas was much wetter than average, and the 2011 season was much drier than normal. As a result, plant height, canopy width, and ground cover were greater in the 2010 sites than in 2011. The effects of N fertilizer were greatest for the two cultivars in subsurface drip irrigation (SDI) at New Deal in 2010 for all three N status indicators, and for the three plant growth measures compared to the other site-years. Correlation analysis indicated that among the three plant N indicators, leaf N was the most sensitive to plant parameters. These effects were positive in 2010 and negative in the 2011 dry year. Petiole NO3 was the plant N indicator that was the most insensitive to plant growth, but the marked seasonal decline pattern reduces its usefulness for late-season N management.

Although subsurface drip (SSD) is used as a water-efficient alternative to overhead irrigation in many crops, the effects of SSD on the distribution of bolls on cotton plants (Gossypium hirsutum L.) have not been thoroughly examined. The purpose of this study was to add to the current knowledge about the effects of SSD on cotton yield dynamics. Cultivar DP 488 BG/RR was grown in three studies during 2 yr with irrigation treatments consisting of overhead irrigation (Overhead), a nonirrigated control (Nonirrigated), SSD matched to overhead irrigation amounts and frequency (SSD Matched), and SSD based on soil moisture (SSD Fed) irrigated cotton. The cotton was grown in two locations in 2004 and one location in 2005 in Georgia. Crop height, maturity, and soil moisture status were monitored throughout the growing season in each location. At harvest, a subplot consisting of one harvest row measuring 3 m in length was removed from each plot and handpicked to determine cotton boll distribution in each plot. Irrigation method had a significant impact on boll distribution on the plants, with the overhead irrigation treatment consistently having less cotton near the bottom of the plant and more cotton near the top than either of the SSD methods. We conclude that SSD irrigation decreases early-season fruit loss, resulting in heavier carbohydrate sinks and decreasing overall growth and upper boll filling on the crop.

Subsurface drip (SSD) is used as a water-efficient alternative to overhead irrigation in many crops. This study compared soil water, water use, crop maturity, lint yield, and fiber quality of cotton (Gossypium hirsutum L.) grown with SSD to cotton grown with overhead irrigation. Three experiments were conducted at two Georgia locations in 2004 and 2005. Treatments consisted of overhead irrigated, nonirrigated, SSD matched to overhead irrigation rates (SSD Matched), and SSD based on soil water (SSD Fed). Cotton maturity was affected by irrigation treatment as nonirrigated cotton matured earliest, whereas overhead irrigated cotton matured latest. Subsurface drip irrigated cotton produced similar or higher lint yields than overhead irrigated cotton. Subsurface drip provided adequate soil water and irrigation amounts were 4.4, 8.2, and 0.5 cm less than overhead irrigation at the three locations. Water use efficiency (WUE) of cotton SSD irrigated was 23 and 15% higher than overhead-irrigated cotton in two experiments. Irrigation method did not substantially affect fiber quality; however, micronaire was higher in cotton from the SSD Fed treatment than cotton in the Overhead treatment in two locations. We conclude that SSD irrigation provides the same positive effects as overhead irrigation in cotton production while reducing irrigation water use and may allow for improved irrigation efficiency.

Off-the-shelf consumer digital cameras are convenient and user-friendly. However, the use of these cameras in remote sensing is limited because convenient methods for concurrently determining visible and near-infrared (NIR) radiation using these cameras have not been developed. Two Nikon Coolpix 4300 digital cameras were evaluated in tandem to determine the effectiveness of a cross-camera calibration procedure that would allow concurrent use of an unmodified digital camera and a NIR-sensitive digital camera without preset shutter speeds or aperture settings. The NIR-sensitive camera was modified to detect NIR radiation by replacing the internal hot mirror with a Hoya RM72 filter. Each camera was calibrated at five exposure levels using a Gretag-Macbeth ColorCheckerTM reflectance panel, and raw camera brightness values were converted to relative reflectance by exposure compensation equations. The method was tested on a series of 26 diffuse reflectance targets, which also yielded the same exposure compensation relationships. The relationship between camera channel brightness and target reflectance was nonlinear within each exposure, but sensitivity was linear between exposures. The procedure was tested on 36 cotton plots (Gossypium hirsutum) in an irrigation study in 2006. Images obtained on eight dates during the season were corrected for exposure and converted to relative reflectance values. The normalized difference vegetation index (NDVI) values from the plots were then compared with ground-based spectrometer measurements of NDVI. Corrected camera-based NDVI values were closely correlated with the spectrometer NDVI values (r2 = 0.72), suggesting that the camera system can more consistently estimate crop reflectance characteristics if exposure compensation is applied.

Cumulative absorbed radiation is highly correlated with crop biomass and yield. In this chapter we describe the use of a digital camera and commercial imaging software for estimating daily radiation capture, canopy photosynthesis, and relative growth rate. Digital images were used to determine percentage of ground cover of lettuce (Lactuca sativa L.) communities grown at five temperatures. Plants were grown in a steady-state, 10-chamber CO2 gas exchange system, which was used to measure canopy photosynthesis and daily carbon gain. Daily measurements of percentage of ground cover were highly correlated with daily measurements of both absorbed radiation (r(sup 2) = 0.99) and daily carbon gain (r(sup 2) = 0.99). Differences among temperature treatments indicated that these relationships were influenced by leaf angle, leaf area index, and chlorophyll content. An analysis of the daily images also provided good estimates of relative growth rates, which were verified by gas exchange measurements of daily carbon gain. In a separate study we found that images taken at hourly intervals were effective for monitoring real-time growth. Our data suggests that hourly images can be used for early detection of plant stress. Applications, limitations, and potential errors are discussed. We have long known that crop yield is determined by the efficiency of four component processes: (i) radiation capture, (ii) quantum yield, (iii) carbon use efficiency, and (iv) carbon partitioning efficiency (Charles-Edwards, 1982; Penning de Vries & van Laar, 1982; Thornley, 1976). More than one-half century ago, Watson (1947, 1952) showed that variation in radiation capture accounted for almost all of the variation in yield between sites in temperate regions, because the three other components are relatively constant when the crop is not severely stressed. More recently, Monteith (1977) reviewed the literature on the close correlation between radiation capture and yield. Bugbee and Monje (1992) demonstrated the close relationship between absorbed radiation and yield in an optimal environment.

Nitrogen (N) is often supplied to plants in excess to minimize the possibility of encountering N deficiency that would reduce the plant quality due to leaf chlorosis and necrosis. This is not only costly, but it can reduce the quality of plants, predispose the plants to biotic stress such as Botrytisgray mold, and extend the production cycle. Several tools can be used to identify N deficiency in plants, and most are based on chlorophyll reflectance or transmittance. While sensitive when plants are experiencing N deficiency, spectral signals can saturate in an ample N supply and make it difficult to discern sufficient and supra-optimal N nondestructively. Three diverse ornamental species (begonia, Begoniacea×tuberhybrida; butterflybush, Buddlejadavidii; and geranium, Pelargonium×hortorum) were grown with a broad range of N supplied (1.8 to 58 mm) in three separate studies that resulted in a range of 1.8% to 6% tissue N concentration. Using a spectroradiometer, we measured reflectance from the whole plants twice over a period of 3 weeks. A first-derivative analysis of the data identified six wavebands that were strongly correlated to both begonia and butterflybush tissue N concentration (r2 ∼ 0.9), and two of these also correlated well to geranium N concentration. These wavebands did not correlate to chlorophyll peak absorbance, but rather blue, green, red, and far-red “edges” of known plant pigments. These wavebands hold promise for use as a nondestructive indicator of N status over a much broader range of tissue N concentration than current sensors can reliably predict.