scholarly journals Dependence of CWSI-Based Plant Water Stress Estimation with Diurnal Acquisition Times in a Nectarine Orchard

2021 ◽  
Vol 13 (14) ◽  
pp. 2775
Author(s):  
Suyoung Park ◽  
Dongryeol Ryu ◽  
Sigfredo Fuentes ◽  
Hoam Chung ◽  
Mark O’Connell ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Data Acquisition ◽  
Irrigation Scheduling ◽  
Physiological Parameters ◽  
Acquisition Time ◽  
Plant Water ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Plant Water Stress

Unmanned aerial vehicle (UAV) remote sensing has become a readily usable tool for agricultural water management with high temporal and spatial resolutions. UAV-borne thermography can monitor crop water status near real-time, which enables precise irrigation scheduling based on an accurate decision-making strategy. The crop water stress index (CWSI) is a widely adopted indicator of plant water stress for irrigation management practices; however, dependence of its efficacy on data acquisition time during the daytime is yet to be investigated rigorously. In this paper, plant water stress captured by a series of UAV remote sensing campaigns at different times of the day (9h, 12h and 15h) in a nectarine orchard were analyzed to examine the diurnal behavior of plant water stress represented by the CWSI against measured plant physiological parameters. CWSI values were derived using a probability modelling, named ‘Adaptive CWSI’, proposed by our earlier research. The plant physiological parameters, such as stem water potential (ψstem) and stomatal conductance (gs), were measured on plants for validation concurrently with the flights under different irrigation regimes (0, 20, 40 and 100 % of ETc). Estimated diurnal CWSIs were compared with plant-based parameters at different data acquisition times of the day. Results showed a strong relationship between ψstem measurements and the CWSIs at midday (12 h) with a high coefficient of determination (R2 = 0.83). Diurnal CWSIs showed a significant R2 to gs over different levels of irrigation at three different times of the day with R2 = 0.92 (9h), 0.77 (12h) and 0.86 (15h), respectively. The adaptive CWSI method used showed a robust capability to estimate plant water stress levels even with the small range of changes presented in the morning. Results of this work indicate that CWSI values collected by UAV-borne thermography between mid-morning and mid-afternoon can be used to map plant water stress with a consistent efficacy. This has important implications for extending the time-window of UAV-borne thermography (and subsequent areal coverage) for accurate plant water stress mapping beyond midday.

Development of a Continuous Leaf Monitoring System to Predict Plant Water Status

2017 ◽  
Vol 60 (5) ◽  
pp. 1445-1455 ◽  
Author(s):  
Rajveer S. Dhillon ◽  
Shrini K. Upadhaya ◽  
Francisco Rojo ◽  
Jed Roach ◽  
Robert W. Coates ◽  
...  
Keyword(s):  
Water Stress ◽  
Data Collection ◽  
Water Status ◽  
Irrigation Scheduling ◽  
Leaf Temperature ◽  
Plant Water Status ◽  
Mesh Network ◽  
Plant Water ◽  
Plant Water Stress ◽  
Precision Irrigation

Abstract. There is increased demand for irrigation scheduling tools that support effective use of the limited supply of irrigation water. An efficient precision irrigation system requires water to be delivered based on crop needs by measuring or estimating plant water stress. Leaf temperature is a good indicator of water stress. In this study, a system was developed to monitor leaf temperature and microclimatic environmental variables to predict plant water stress. This system, called the leaf monitor, monitored plant water status by continuously measuring leaf temperature, air temperature, relative humidity, ambient light, and wind conditions in the vicinity of a shaded leaf. The system also included a leaf holder, a solar radiation diffuser dome, and a wind barrier for improved performance of the unit. Controlled wind speed and consistent light conditions were created around the leaf to reduce the effect of nuisance variables on leaf temperature. The leaf monitor was incorporated into a mesh network of wireless nodes for sensor data collection and remote valve control. The system was evaluated for remote data collection in commercial orchards. Experiments were conducted during the 2013 and 2014 growing seasons in walnut () and almond () orchards. The system was found to be reliable and capable of providing real-time visualization of the data remotely, with minimal technical problems. Leaf monitor data were used to develop modified crop water stress index (MCWSI) values for quantifying plant water stress levels. Keywords: Almonds, CWSI, Infrared sensor, Irrigation scheduling, Leaf temperature, Nut crops, Plant water stress, Precision irrigation, Stem water potential, Walnuts, Wireless mesh network.

Crop water stress index relationship with soybean seed, protein and oil yield under varying irrigation regimes in a Mediterranean environment

2020 ◽  
pp. 1-13
Author(s):  
Christos Vamvakoulas ◽  
Ioannis Argyrokastritis ◽  
Panayiota Papastylianou ◽  
Yolanda Papatheohari ◽  
Stavros Alexandris
Keyword(s):  
Water Stress ◽  
Seed Yield ◽  
Seed Protein ◽  
Soybean Seed ◽  
Irrigation Scheduling ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress

A two-year field experiment was conducted to determine the effect of water stress, including Crop Water Stress Index (CWSI), on seed, protein and oil yields, for two hybrids of drip-irrigated soybean in Central Greece. The experiment was set up as a split plot design with four replicates, five main plots (irrigation treatments) and two sub-plots (soybean hybrids, ‘PR91M10’ and ‘PR92B63’). Irrigation was applied to provide 100, 75, 50 and 25% of the crop evapotranspiration needs and 0% non-irrigated. Biomass weight, seed yield, oil and protein concentration were measured after harvest. To compute CWSI, lower and upper baselines were developed based on the canopy temperature measurements of I100 and I0 treatments, respectively. Deficit irrigation had a significant effect on biomass, seed, protein and oil yields. Hybrid PR92B63 was more responsive to irrigation and showed higher biomass, seed protein and oil yields, while the more sensitive hybrid PR91M10 had the ability to maintain productivity with increasing degrees of water stress. The rain-fed treatments significantly reduced biomass production and seed yield compared with the fully-irrigated ones. The highest and the lowest protein and oil yields were obtained in the I100 and I0 treatments respectively in both years and cultivars. Statistically significant exponential relationships were determined between CWSI and biomass, seed, protein and oil yields. Generally, CWSI could be used to measure crop water status and to improve irrigation scheduling of the crop and 0.10 for PR92B63 and 0.19 for PR91M10 could be offered as threshold values under the climatic conditions of the region.

scholarly journals Development of an Open-Source Thermal Image Processing Software for Improving Irrigation Management in Potato Crops (Solanum tuberosum L.)

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 472 ◽  
Author(s):  
Gonzalo Cucho-Padin ◽  
Javier Rinza ◽  
Johan Ninanya ◽  
Hildo Loayza ◽  
Roberto Quiroz ◽  
...  
Keyword(s):  
Image Processing ◽  
Water Stress ◽  
Open Source ◽  
Irrigation Scheduling ◽  
Thermal Image ◽  
Morphological Operations ◽  
Plant Water ◽  
Process Data ◽  
Crop Water Stress Index ◽  
Potato Crops

Accurate determination of plant water status is mandatory to optimize irrigation scheduling and thus maximize yield. Infrared thermography (IRT) can be used as a proxy for detecting stomatal closure as a measure of plant water stress. In this study, an open-source software (Thermal Image Processor (TIPCIP)) that includes image processing techniques such as thermal-visible image segmentation and morphological operations was developed to estimate the crop water stress index (CWSI) in potato crops. Results were compared to the CWSI derived from thermocouples where a high correlation was found ( r P e a r s o n = 0.84). To evaluate the effectiveness of the software, two experiments were implemented. TIPCIP-based canopy temperature was used to estimate CWSI throughout the growing season, in a humid environment. Two treatments with different irrigation timings were established based on CWSI thresholds: 0.4 (T2) and 0.7 (T3), and compared against a control (T1, irrigated when soil moisture achieved 70% of field capacity). As a result, T2 showed no significant reduction in fresh tuber yield (34.5 ± 3.72 and 44.3 ± 2.66 t ha - 1 ), allowing a total water saving of 341.6 ± 63.65 and 515.7 ± 37.73 m 3 ha - 1 in the first and second experiment, respectively. The findings have encouraged the initiation of experiments to automate the use of the CWSI for precision irrigation using either UAVs in large settings or by adapting TIPCIP to process data from smartphone-based IRT sensors for applications in smallholder settings.

scholarly journals Evaluation of yield, quality and crop water stress index of sugar beet under different irrigation regimes

2016 ◽  
Vol 17 (2) ◽  
pp. 571-578 ◽  
Author(s):  
Omid Bahmani ◽  
Ali Akbar Sabziparvar ◽  
Rezvan Khosravi
Keyword(s):  
Water Stress ◽  
Sugar Beet ◽  
Irrigation Scheduling ◽  
Sugar Yield ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Yield Quality ◽  
Crop Water Stress

This study was carried out to evaluate the use of the crop water stress index (CWSI) for irrigation scheduling of sugar beet for two years under the semi arid climate of Iran. Statistical relationships between CWSI and yield, quality parameters and irrigation water use efficiency (IWUE) were investigated. Irrigations were scheduled based on 100 (I100), 85 (I85), 70 (I50) and 0% (I0) of plant water requirement. CWSI values were calculated from the measurements of canopy temperatures by infrared thermometer, air temperatures and vapor pressure deficit values for all the irrigated treatments. The highest IWUE was found in I70 with 9.16 and 1.66 kg m−3 for the root and sugar yield, respectively, in 2013. A non-water stressed baseline (lower line) equation for sugar beet was measured from full irrigated plots as (Tc − Ta)ll = −0.832VPD + 2.1811; R2 = 0.6508. There was a high determination coefficient between CWSI with the root and sugar yield and IWUE. The CWSI could be used to determine the irrigation time of sugar beet, and 0.3 could be offered as a threshold value. Results indicated that the CWSI can be used to evaluate crop water stress and improve irrigation scheduling for sugar beet under semiarid conditions.

AIRBORNE REMOTE SENSING TO DETECT PLANT WATER STRESS IN FULL CANOPY COTTON

2006 ◽  
Vol 49 (3) ◽  
pp. 655-665 ◽  
Author(s):  
W. R. DeTar ◽  
J. V. Penner ◽  
H. A. Funk
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Plant Water ◽  
Airborne Remote Sensing ◽  
Plant Water Stress

Thermal remote sensing of plant water stress in natural ecosystems

2020 ◽  
Vol 476 ◽  
pp. 118433
Author(s):  
Na Liu ◽  
Zijuan Deng ◽  
Hailong Wang ◽  
Zidong Luo ◽  
Hugo A. Gutiérrez-Jurado ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Plant Water ◽  
Natural Ecosystems ◽  
Thermal Remote Sensing ◽  
Plant Water Stress
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