Canopy Temperature Data Research Articles

Effect of site-specific irrigation management on grapevine yield and fruit quality attributes

Spatial variation in yield and fruit composition has been observed in many vineyards, leading to low productivity. In this study, site-specific irrigation was applied in a commercial vineyard (Vitis vinifera L. cv. Shiraz) block in the Sunraysia region of Australia to improve production in low-yielding areas of the block and decrease differences in yield and quality between irrigation management zones. Data collected under uniform irrigation management showed that spatial variation in canopy cover, yield and fruit composition across the vineyard block was substantial. Normalised difference vegetation index (NDVI) and canopy temperature data supported delineation of three irrigation management zones and decisions regarding irrigation strategy. Water use efficiency and yield improvements were achieved by implementing site-specific irrigation. Fruit composition results were varied; pH and titratable acidity showed increased similarity between zones, but other parameters maintained differences between zones. These results lend support to the use of NDVI to determine irrigation management zones.

Using radiation thermography and thermometry to evaluate crop water stress in soybean and cotton

Abstract The use of digital infrared thermography and thermometry to investigate early crop water stress offers a producer improved management tools to avoid yield declines or to deal with variability in crop water status. This study used canopy temperature data to investigate whether an empirical crop water stress index could be used to monitor spatial and temporal crop water stress. Different irrigation treatment amounts (100%, 67%, 33%, and 0% of full replenishment of soil water to field capacity to a depth of 1.5 m) were applied by a center pivot system to soybean ( Glycine max L.) in 2004 and 2005, and to cotton ( Gossypium hirsutum L.) in 2007 and 2008. Canopy temperature data from infrared thermography were used to benchmark the relationship between an empirical crop water stress index (CWSI e ) and leaf water potential ( Ψ L ) across a block of eight treatment plots (of two replications). There was a significant negative linear correlation between midday Ψ L measurements and the CWSI e after soil water differences due to irrigation treatments were well established and during the absence of heavy rainfall. Average seasonal CWSI e values calculated for each plot from temperature measurements made by infrared thermometer thermocouples mounted on a center pivot lateral were inversely related to crop water use with r 2 values >0.89 and 0.55 for soybean and cotton, respectively. There was also a significant inverse relationship between the CWSI e and soybean yields in 2004 ( r 2 = 0.88) and 2005 ( r 2 = 0.83), and cotton in 2007 ( r 2 = 0.78). The correlations were not significant in 2008 for cotton. Contour plots of the CWSI e may be used as maps to indicate the spatial variability of within-field crop water stress. These maps may be useful for irrigation scheduling or identifying areas within a field where water stress may impact crop water use and yield.

The crop water stress index (CWSI) for drip irrigated cotton in a semi-arid region of Turkey

This study was carried out to determine the crop water stress index (CWSI) for drip irrigated cotton grown on a heavy clay texture soil ( Palexerollic Chromoxerert ) under semi-arid climatic condition of East Mediterranean region for three years (2005 to 2007) in Adana, Turkey. Four irrigation treatments designated as full (I 100 ) with no water stress and slight (DI 70 ), moderate (DI 50 ) and strong water stress (continuous stress, dry land) (DI 00 ) were tested. The treatments of DI 70 and DI 50 received water amount of 70 and 50% of the control treatment and the DI 00 was not irrigated except for germination water given at the beginning of the growing season. Irrigation was initiated when leaf water potential (LWP) reached to -15 bar for full (I 100 ), -17 bar for DI 70 and -20 bar for DI50 irrigation treatments. After first irrigation, all the treatments were irrigated at one week interval. The deficit irrigation affected, the irrigation water use, seed cotton yield, dry matter and some yield components such as plant height and number of boll per plant of cotton. Average values of water use, seed cotton yield, dry matter and water use efficiency of full irrigated cotton were 578 mm, 3.28 tha -1 , 13.44 tha -1 and 0.59 kgm -3 , respectively. CWSI values were calculated from the measurements of canopy temperatures by infrared thermometer (IRT), ambient air temperatures and vapor pressure deficit values for all the irrigated treatments. A non-water stressed baseline (lower baseline) equation for cotton was developed using canopy temperature measured from full irrigated plots as, T c −T a = −1.7543VPD +1.56; R2=0.5327 and the non-transpiring baseline (upper baseline) equation was built using canopy temperature data taken from continuous stress plots as, T c −T a = −0.0217VPD + 3.2191. The trends in CWSI values were consistent with the varying soil water content due to the deficit irrigation programs. The relationships between mean CWSI and plant parameters considered in this study were linear except for irrigation water amount. Both dry matter and seed cotton yield decreased with increased soil water deficit. Seed cotton yield (SY) and seasonal mean CWSI values relationship were obtained as, SY = −2.3552CWSI + 3.5657 ; R 2 =0.499. This relationship can be used to predict the seed cotton yield. The results suggest that the cotton crop for this particular climate and soil conditions, should be irrigated when CWSI approaches 0.36. The CWSI approach, according to results of this study, can be accepted as a useful tool to schedule irrigations for cotton. Key words : Crop water stress index (CWSI), evapotranspiration, cotton, drip irrigation.

Automation of a Center Pivot Using the Temperature-Time-Threshold Method of Irrigation Scheduling

A center pivot was completely automated using the temperature-time-threshold method of irrigation scheduling. An array of infrared thermometers was mounted on the center pivot, and these were used to remotely determine the crop leaf temperature as an indicator of crop water stress. We describe methods used to automatically collect and analyze the canopy temperature data and control the moving irrigation system based on the data analysis. Automatic irrigation treatments were compared with manually scheduled irrigation treatments under the same center pivot during the growing seasons of 2004 and 2005. Manual irrigations were scheduled on a weekly basis using the neutron probe to determine the profile water content and the amount of water needed to replenish the profile to field capacity. In both years, there was no significant difference between manual and automatic treatments in soybean water use efficiency or irrigation water use efficiency. The automatic irrigation system has the potential to simplify management, while maintaining the yields of intensely managed irrigation.

Modeling Diurnal Canopy Temperature Dynamics Using One‐Time‐of‐Day Measurements and a Reference Temperature Curve

The application of the temperature–time threshold (TTT) method of irrigation scheduling to self‐propelled irrigations systems requires a method of estimating the diurnal canopy temperature dynamics using only a one‐time‐of‐day measurement. Other research efforts such as the crop water stress index (CWSI) and field canopy temperature mapping using moving irrigation systems could also be served by the use of this method. This was accomplished using a stationary reference measurement to capture the canopy temperature dynamics. Two different methods were developed for estimating a temperature curve for a remote location from a one‐time‐of‐day measurement at that location. The first method (scaled method) uses the ratio between the reference temperature and the remote location temperature, referenced to the predawn temperature, to scale the reference curve to yield the predicted curve. In the second method (Gaussian difference method), a three‐parameter Gaussian equation was empirically fitted to the temperature differences between the reference and the measured remote canopy temperature curves. To test these two methods, canopy temperature data, sensed using stationary infrared thermometers, from three different crops {corn (Zea mays L.), cotton (Gossypium hirsutum L.), and soybean [Glycine max (L.) Merr.]} were analyzed. For a few hours after dawn and before sunset, the scaled method was generally more accurate while during the middle of the day, the Gaussian difference method was more accurate. The average absolute value of the error between the predicted and actual temperatures from the best of both methods during daylight hours was roughly 0.5°C. For all 3 yr, the total irrigation for a season using the extrapolated temperatures were within 18 mm on average of those actually scheduled using the TTT method and measured data.

Alternative Design Formulae for the Ventilation Rate of Greenhouses

A fresh look at a standard design formulae for ventilation of greenhouses is presented. The new approach emphasizes crop-canopy temperature rather than air temperature and covers situations with positive as well as negative ventilation Bowen ratios (ratio of sensible to latent heat). The latter situation is characteristic of arid conditions, and is the result of intense evapotranspirational cooling on hot, dry days. Two design formulae are considered, depending on the availability of experimental data for parameter estimation. First, a midday crop-in-greenhouse model is developed. It relates canopy temperature to environmental and operational conditions and can be used, at least in principle, to find the dependence of stomatal and aerodynamic conductances on the ventilation rate. If canopy-temperature data are not available, but transpiration data make it possible to develop a simple predictive formulae, representative values of the stomatal and aerodynamic conductances can be obtained. These can then be used to calculate the required ventilation rate. The procedure is illustrated with data from a temperate-maritime climate. Some improvement over the standard approach can be made even with just standard environmental data. With these an empirical relationship may be found between the Bowen ratio and the temperature rise in the greenhouse. The Bowen ratio is then used in the revised design formulae. This approach removes some of the guesswork currently involved in selecting the evaporation coefficient for the standard design formulae. This procedure is illustrated with data sets from mediterranean locations, which also demonstrate the effect of evaporative cooling.

Accounting for humidity in canopy-temperature-controlled irrigation scheduling

High moisture content in the air surrounding crop canopies can reduce transpiration and increase canopy temperature ( T c ) independently of soil moisture. Humid conditions can affect the accuracy of irrigation signals produced by a canopy-temperature-based irrigation scheduling procedure that uses a time threshold (TT), which is the daily summation of time above the temperature threshold ( T o) defined as the midpoint of the crop's optimum temperature range. Because historical crop canopy temperature data were unavailable, an energy balance model was used to simulate time threshold values for different climates. A limiting relative humidity (LRH) algorithm was added to the model to estimate whether canopy temperatures that exceed the ( T o) were affected by high humidity. The LRH was computed from T a and δ T, denoted as ( T o) - T wb ∗ , where T wb ∗ is the highest wet bulb temperature that does not increase T c. Time periods of restricted transpiration were identified by calculating ambient relative humidity (RH) and comparing it to the LRH value. If RH > LRH, canopy temperature was assumed to be increased by a reduction in transpiration. In a humid climate the LRH criterion reduced the simulated average TT value by 27%, 51%, and 69%, respectively, for δ T values between 3°C and 5°C. This same LRH reduced the TT values by 16%, 32% and 36%, respectively, in a semiarid climate. The LRH criterion had no effect on the average TT value in the and climate. Estimated TT values had the lowest variability among years for a AT value of 4°C in the humid and semiarid climates. A generalized curve described the TT versus ΔT relationship across a wide spectrum of climates. The LRH procedure produced consistent adjustments to TT; however, further refinements may be needed to improve the accuracy of estimating daily TT when weather conditions are highly variable.

Scheduling Considerations for Automated Irrigation in the 1990s

This work focuses on recent developments and examples of irrigation scheduling that concern where in the root system and when in the plant's phenology water should be applied. Information is provided on using and measuring soil variability to help schedule irrigation. An irrigation model is described that emphasizes the soil water-holding capacity and root distribution in designing irrigation systems and scheduling water application. Recent research is reviewed on the subject of fruit crops that can tolerate severe water stress during specific growth periods of the fruit. Finally, a method of using infrared thermometers and canopy temperature data in cloudy, humid regions is presented that has the potential to extend the use of this technology.

Influence of water and nitrogen levels on canopy temperatures of winter wheat grown in the North American Great Plains

Canopy temperatures of winter wheat were measured with infrared thermometers in 1985 and 1986 at five locations in the North American Great Plains. These measurements were made to determine the occurrence and severity of water stress resulting from different water treatments and to evaluate the influence of nitrogen (N) fertilization on canopy temperatures. Study results suggest that water stress occurred at locations in the northern and southern Great Plains in both 1985 and 1986, but not at the mid-Plains locations. The influence of N fertilization on canopy temperature was not consistent among locations nor even between years at the same location. At Mandan, ND, the level of N fertilization had a significant impact on the canopy temperature in both years while at Lethbridge, Canada, it had no effect in either year. At the other locations, the level of N fertilization influenced the canopy temperature in one year, but not the other. In some locations, there was an apparent cultivar effect on the canopy temperature. Colt, as indicated by canopy temperature data, did not grow as well at the northern and southern locations as it did at the mid-Plains locations. Colt was developed in the mid-Plains environment, which may explain its better performance at the mid-Plains locations.

Infrared Thermometry for Scheduling Irrigation of Corn1

AbstractIrrigation scheduling is an increasingly important practice in the management of valuable water resources in agricultural regions. The study reported here was conducted to evaluate the feasibility of scheduling irrigation in corn (Zea mays L.) using canopy temperature data obtained with a hand‐held infrared thermometer (IRT).Specific objectives of the study were: 1) to determine whether irrigations can be scheduled from crop canopy temperature data and 2) to evaluate the effectiveness of various canopy temperature irrigation scheduling methods through their effects on some plant responses and the soil water balance.The study was conducted at the Sandhills Agricultural Laboratory located near Tryon, Neb. The soil at the site is classified as a Typic Ustipsamment (Valentine fine sand). The range in temperature of six readings made with an IRT—defined as the canopy temperature variability (CTV)—in a fully irrigated reference plot (WW) was less than 0.7 C. As the temperature difference between a water‐stressed plot and the WW plot increased so did CTV values until a critical stress level was reached beyond which CTV values stabilized. The onset of water stress can, therefore, be signaled when CTV values exceed 0.7 C.Observations of CTV were the basis for one type of irrigation scheduling procedure. Irrigation was initiated when the range of six measurments in a plot exceeded 0.7 C. A second procedure consisted of comparing the difference between the average canopy temperature of the well‐watered plot (WW) with that of the plot to be scheduled. Irrigations were initiated when plot temperatures became either 1.0 (1SMW; SWM = Stressed Minus Well‐watered) or 3.0 C (3SMW) warmer than the well‐watered plot.A total of 283 mm of irrigation water was applied to the WW plot whereas the CTV plot received 127 mm. By the end of the growing season almost all available water had been extracted from the soil in the temperature scheduled plots but the soil profile remained near field capacity in the WW plot. This suggests that during the growing season soil water was most effectively used in the temperature scheduled plots.Grain yields (Y) were reduced in the order of increasing water stress as follows: YWW > YCTV > Y1SMW > Y3SMW > YDL YDL is the yield from a dryland (DL) plot which received no supplemental irrigation. Yields of grain in the CTV treatment were slightly lower than in the WW plot, but not significantly so. This suggests that plants in the CTV plot received adequate water. Grain yields in the other temperature‐scheduled plots were significantly reduced below those of the WW plot. However, only about 50 to 60 mm of irrigation water were applied to these plots.

The Brown‐Rosenberg Resistance Model of Crop Evapotranspiration Modified Tests in an Irrigated Sorghum Field1

AbstractThe Brown‐Rosenberg (1973) resistance model was modified to simplify its calculation and increase its usefulness for estimating evapotranspiration. The model requires inputs of net radiation, air temperature, and vapor pressure and canopy and boundary layer resistance. The first three of these parameters are measured. In the modified version canopy resistance is estimated from a functional dependence on irradiance. The boundary layer resistance is estimated from a functional dependence on windspeed. The modification was tested in an irrigated sorghum (Sorghum bicolor Moench, cv ‘Rs 633’) field at Mead, Neb.The model predictions generally agreed to within 10%, on both an hourly and daily basis, with direct lysimetric and Bowen ratio‐energy balance measurements of evapotranspiration from the sorghum.The Brown‐Rosenberg model in its original and modified forms is useful when neither direct nor remotely sensed crop canopy temperature data are available and when there is need to evaluate the impact on evapotranspiration of several of the aforementioned environmental and crop parameters.

Evaluation of Resistance and Mass Transport Evapotranspiration Models Requiring Canopy Temperature Data1

AbstractThe increasing use of thermal scanners on aircraft and satellites makes it likely that data on surface temperature for large areas will become routinely available. If reliable evapotranspiration methods which incorporate surface temperature data can be developed an important tool for research and application in hydrology, in irrigation scheduling, and in other water management procedures will result.A ‘resistance model’ which stems from the work of Brown and Rosenberg and a mass transport (Daltonian) model for estimating evapotranspiration (ET) were tested on large fields of naturally subirrigated alfalfa (Medicago sativa L.). Both models make use of crop canopy temperature data. Temperature data were obtained with an IR thermometer and with leaf thermocouples. A Bowen ratio‐energy balance (BREB) model, adjusted to account for underestimation of ET during periods of strong sensible heat advection, was used as the standard against which the resistance and mass transport models were compared.Daily estimates by the resistance model were within 1C% of estimates made by the BREB model. Daily estimates by the mass transport model did not agree quite as well. Performance was good on clear and cloudy days and also during periods of nonadvection and strong advection of sensible heat.The performance of the mass transport and resistance models was less satisfactory for estimation of fluxes of latent heat for short term (15 min) periods. Both models tended to overestimate at low LE fluxes.