Automatic irrigation scheduling of apple trees using theoretical crop water stress index with an innovative dynamic threshold

2015 ◽  
Vol 118 ◽  
pp. 193-203 ◽  
Author(s):  
Yasin Osroosh ◽  
R. Troy Peters ◽  
Colin S. Campbell ◽  
Qin Zhang
Keyword(s):  
Water Stress ◽  
Irrigation Scheduling ◽  
Stress Index ◽  
Dynamic Threshold ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Apple Trees ◽  
Water Stress Index ◽  
Crop Water Stress

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 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.

scholarly journals Application of a Daily Crop Water Stress Index to Deficit Irrigate Malbec Grapevine under Semi-Arid Conditions

Agriculture ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 492
Author(s):  
Krista C. Shellie ◽  
Bradley A. King
Keyword(s):  
Water Stress ◽  
Water Status ◽  
Irrigation Scheduling ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Irrigation Amount ◽  
Water Stress Index ◽  
Arid Conditions ◽  
Crop Water Stress

Precision irrigation of wine grape is hindered by the lack of an automated method for monitoring vine water status. The objectives of this study were to: Validate an automated model for remote calculation of a daily crop water stress index (CWSI) for the wine grape (Vitis vinifera L.) cultivar Malbec and evaluate its suitability for use in irrigation scheduling. Vines were supplied weekly with different percentages of evapotranspiration-based estimated water demand (ETc) over four growing seasons. In the fifth growing season, different daily CWSI threshold values were used to trigger an irrigation event that supplied 28 mm of water. All three indicators of vine water status (CWSI, midday leaf water potential (Ψlmd), and juice carbon isotope ratio (δ13C)) detected an increase in stress severity as the irrigation amount decreased. When the irrigation amount decreased from 100% to 50% ETc, 70% to 35% ETc, or the daily CWSI threshold value increased from 0.4 to 0.6, berry fresh weight and juice titratable acidity decreased, juice δ13C increased, the weekly CWSI increased, and Ψlmd decreased. Under the semi-arid conditions of this study, utilizing a daily CWSI threshold for irrigation scheduling reduced the irrigation amount without compromising the yield or changes in berry composition and remotely provided automated decision support for managing water stress severity in grapevine.

Morning crop water stress index as a sensitive indicator of water status in apple trees

2019 ◽  
Author(s):  
Abdelmoneim Zakaria Mohamed ◽  
Yasin Osroosh ◽  
Troy Robert Peters ◽  
Travis Bates ◽  
Colin Sanford Campbell ◽  
...  
Keyword(s):  
Water Stress ◽  
Water Status ◽  
Sensitive Indicator ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Apple Trees ◽  
Water Stress Index ◽  
Crop Water Stress

Monitoring water status in apple trees using a sensitive morning crop water stress index *

2020 ◽  
Author(s):  
Abdelmoneim Z. Mohamed ◽  
Yasin Osroosh ◽  
R. Troy Peters ◽  
Travis Bates ◽  
Colin S. Campbell ◽  
...  
Keyword(s):  
Water Stress ◽  
Water Status ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Apple Trees ◽  
Water Stress Index ◽  
Crop Water Stress

scholarly journals Data-Driven Models for Canopy Temperature-Based Irrigation Scheduling

2020 ◽  
Vol 63 (5) ◽  
pp. 1579-1592
Author(s):  
Bradely A. King ◽  
Krista C. Shellie ◽  
David D. Tarkalson ◽  
Alexander D. Levin ◽  
Vivek Sharma ◽  
...  
Keyword(s):  
Water Stress ◽  
Canopy Temperature ◽  
Irrigation Scheduling ◽  
Data Driven ◽  
Stress Index ◽  
Wine Grape ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress

HighlightsArtificial neural network modeling was used to predict crop water stress index lower reference canopy temperature.Root mean square error of predicted lower reference temperatures was <1.1°C for sugarbeet and Pinot noir wine grape.Energy balance model was used to dynamically predict crop water stress index upper reference canopy temperature.Crop water stress index for sugarbeet was well correlated with irrigation and soil water status.Crop water stress idex was well correlated with midday leaf water potential of wine grape.Abstract. Normalized crop canopy temperature, termed crop water stress index (CWSI), was proposed over 40 years ago as an irrigation management tool but has experienced limited adoption in production agriculture. Development of generalized crop-specific upper and lower reference temperatures is critical for implementation of CWSI-based irrigation scheduling. The objective of this study was to develop and evaluate data-driven models for predicting the reference canopy temperatures needed to compute CWSI for sugarbeet and wine grape. Reference canopy temperatures for sugarbeet and wine grape were predicted using machine learning and regression models developed from measured canopy temperatures of sugarbeet, grown in Idaho and Wyoming, and wine grape, grown in Idaho and Oregon, over five years under full and severe deficit irrigation. Lower reference temperatures (TLL) were estimated using neural network models with Nash-Sutcliffe model efficiencies exceeding 0.88 and root mean square error less than 1.1°C. The relationship between TLL minus ambient air temperature and vapor pressure deficit was represented with a linear model that maximized the regression coefficient rather than minimized the sum of squared error. The linear models were used to estimate upper reference temperatures that were nearly double the values reported in previous studies. A daily CWSI, calculated as the average of 15 min CWSI values between 13:00 and 16:00 MDT for sugarbeet and between 13:00 and 15:00 local time for wine grape, were well correlated with irrigation events and amounts. There was a significant (p < 0.001) linear relationship between the daily CWSI and midday leaf water potential of Malbec and Syrah wine grapes, with an R2 of 0.53. The data-driven models developed in this study to estimate reference temperatures enable automated calculation of the CWSI for effective assessment of crop water stress. However, measurements taken under conditions of wet canopy or low solar radiation should be disregarded as they can result in irrational values of the CWSI. Keywords: Canopy temperature, Crop water stress index, Irrigation scheduling, Leaf water potential, Sugarbeet, Wine grape.

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