Improving Irrigation Efficiency and Wine Quality monitoring using Crop Water Stress Index from Canopy Temperature; A Review and Proof of Concept.

2015 ◽  
Keyword(s):  
Water Stress ◽  
Canopy Temperature ◽  
Quality Monitoring ◽  
Stress Index ◽  
Proof Of Concept ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Wine Quality ◽  
Water Stress Index ◽  
Crop Water Stress

scholarly journals CROP WATER STRESS INDEX FOR PREDICTING YIELD LOSS IN COMMON BEAN

Irriga ◽  
2022 ◽  
Vol 1 (4) ◽  
pp. 687-695
Author(s):  
Carlos Quiloango-Chimarro ◽  
Rubens Duarte Coelho ◽  
Jéfferson de Oliveira Costa ◽  
Rafael Gomez-Arrieta
Keyword(s):  
Water Stress ◽  
Grain Yield ◽  
Common Bean ◽  
Yield Loss ◽  
Canopy Temperature ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress

The crop water stress index (CWSI), an index derived from canopy temperature, has been widely studied as a physiological indicator of plant water status to optimize irrigation in common beans. However, it is not clear how this index could contribute to yield prediction as a decision support tool in irrigation management. This paper aimed to use the CWSI for predicting yield loss in common bean (Phaseolus vulgaris L.) subjected to water stress under drip irrigation. A rain shelter experiment was conducted using a completely randomized design with five replications. The indeterminate growth cultivar TAA Dama was subjected to three irrigation treatments: 100% of the field capacity (FC), 75 and 50% FC from 20 days after sowing (DAS) until the end of the crop cycle. Grain yield was reduced by 42% under 50% FC treatment. Furthermore, stomatal conductance was reduced under this treatment, whereas the CWSI and canopy temperature increased as irrigation levels decreased. The relationship between grain yield and CWSI (R2=0.76, RSME=2.35g) suggests that canopy temperature data could be used to forecast grain yield losses. In conclusion, farmers can have a low-cost, effective technique for making water management decisions in common bean.

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.

scholarly journals Response of maize and black gram yield and water productivity to variation in canopy temperature and crop water stress index

2020 ◽  
Vol 34 (3) ◽  
pp. 381-390
Author(s):  
Afshin Khorsand ◽  
Vahid Rezaverdinejad ◽  
Hossein Asgarzadeh ◽  
Abolfazl Majnooni-Heris ◽  
Amir Rahimi ◽  
...  
Keyword(s):  
Water Stress ◽  
Water Productivity ◽  
Canopy Temperature ◽  
Stress Index ◽  
Black Gram ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress

scholarly journals Long-Term Assessment of Reference Baselines for the Determination of the Crop Water Stress Index in Maize under Mediterranean Conditions

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3119
Author(s):  
Alejandro Prior ◽  
Orly Enrique Apolo-Apolo ◽  
Pedro Castro-Valdecantos ◽  
Manuel Pérez-Ruiz ◽  
Gregorio Egea
Keyword(s):  
Water Stress ◽  
Canopy Temperature ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Maize Breeding ◽  
Water Stress Index ◽  
Mediterranean Conditions ◽  
Crop Water Stress

Canopy temperature has been proposed as a relevant variable for crop water stress monitoring. Since crop temperature is highly influenced by the prevailing climatic conditions, it is usually normalized with indices such as the crop water stress index (CWSI). The index requires the use of two baselines that relate canopy temperature under maximum stress and non-water stress conditions with vapor pressure deficit (VPD). These reference baselines are specific to each crop and climatic region. In maize, they have been extensively studied for certain climatic regions but very little is known on their suitability to be used under Mediterranean-type conditions nor their temporal stability, both diurnally and between seasons. Thus, the objective of this work was to determine the reference baselines for maize grown under Mediterranean conditions, as well as its diurnal and long-term stability. An experiment was conducted for 3 years in a maize breeding field, under well-watered and water-stressed irrigation treatments. The determined reference baselines for computing CWSI in maize have shown to be stable in the long term but markedly influenced by the meteorological variations between 10–17 h UTC (Coordinated Universal Time). These results indicate that several reference baselines should be used for CWSI computing throughout the abovementioned time interval. The CWSI values calculated for well-watered and water-stressed maize breeding plots using the reference baselines derived in this study were successfully correlated with other physiological indicators of plant water stress.

An insight to the performance of crop water stress index for olive trees

2013 ◽  
Vol 118 ◽  
pp. 79-86 ◽  
Author(s):  
N. Agam ◽  
Y. Cohen ◽  
J.A.J. Berni ◽  
V. Alchanatis ◽  
D. Kool ◽  
...  
Keyword(s):  
Water Stress ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Olive Trees ◽  
Crop Water Stress

Evaluation of Resistances for Bermudagrass Turf Crop Water Stress Index Models

1994 ◽  
Vol 86 (3) ◽  
pp. 574-581 ◽  
Author(s):  
H. R. Jalali‐Farahani ◽  
D. C. Slack ◽  
D. M. Kopec ◽  
A. D. Matthias ◽  
P. W. Brown
Keyword(s):  
Water Stress ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress

Quantifying Wheat Water Stress with the Crop Water Stress Index to Schedule Irrigations

1994 ◽  
Vol 86 (1) ◽  
pp. 195-199 ◽  
Author(s):  
Donald J. Garrot ◽  
Michael J. Ottman ◽  
D.D. Fangmeier ◽  
Stephen H. Husman
Keyword(s):  
Water Stress ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress
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