scholarly journals Easy water stress detection system for vineyard irrigation management

2019 ◽  
Author(s):  
G. Brunel ◽  
L. Pichon ◽  
J. Taylor ◽  
B. Tisseyre
Keyword(s):  
Water Stress ◽  
Detection System ◽  
Irrigation Management ◽  
Stress Detection

Citrus Irrigation Management

EDIS ◽  
2017 ◽  
Vol 2017 (5) ◽  
Author(s):  
Davie Mayeso Kadyampakeni ◽  
Kelly T. Morgan ◽  
Mongi Zekri ◽  
Rhuanito Ferrarezi ◽  
Arnold Schumann ◽  
...  
Keyword(s):  
Water Stress ◽  
Physiological Activity ◽  
Irrigation Management ◽  
Fruit Size ◽  
Irrigation Scheduling ◽  
Leaf Expansion ◽  
Tree Canopy ◽  
Limiting Factor ◽  
Irrigation Frequency ◽  
Citrus Production

Water is a limiting factor in Florida citrus production during the majority of the year because of the low water holding capacity of sandy soils resulting from low clay and the non-uniform distribution of the rainfall. In Florida, the major portion of rainfall comes in June through September. However, rainfall is scarce during the dry period from February through May, which coincides with the critical stages of bloom, leaf expansion, fruit set, and fruit enlargement. Irrigation is practiced to provide water when rainfall is not sufficient or timely to meet water needs. Proper irrigation scheduling is the application of water to crops only when needed and only in the amounts needed; that is, determining when to irrigate and how much water to apply. With proper irrigation scheduling, yield will not be limited by water stress. With citrus greening (HLB), irrigation scheduling is becoming more important and critical and growers cannot afford water stress or water excess. Any degree of water stress or imbalance can produce a deleterious change in physiological activity of growth and production of citrus trees.  The number of fruit, fruit size, and tree canopy are reduced and premature fruit drop is increased with water stress.  Extension growth in shoots and roots and leaf expansion are all negatively impacted by water stress. Other benefits of proper irrigation scheduling include reduced loss of nutrients from leaching as a result of excess water applications and reduced pollution of groundwater or surface waters from the leaching of nutrients. Recent studies have shown that for HLB-affected trees, irrigation frequency should increase and irrigation amounts should decrease to minimize water stress from drought stress or water excess, while ensuring optimal water availability in the rootzone at all times.

Low-cost Smart Camera System for Water Stress Detection in Crops

2020 ◽  
Author(s):  
Paula Ramos-Giraldo ◽  
S. Chris Reberg-Horton ◽  
Steven Mirsky ◽  
Edgar Lobaton ◽  
Anna M. Locke ◽  
...  
Keyword(s):  
Water Stress ◽  
Low Cost ◽  
Smart Camera ◽  
Stress Detection ◽  
Camera System

scholarly journals Detecting Leaf Pulvinar Movements on NDVI Time Series of Desert Trees: A New Approach for Water Stress Detection

PLoS ONE ◽  
2014 ◽  
Vol 9 (9) ◽  
pp. e106613 ◽  
Author(s):  
Roberto O. Chávez ◽  
Jan G. P. W. Clevers ◽  
Jan Verbesselt ◽  
Paulette I. Naulin ◽  
Martin Herold
Keyword(s):  
Time Series ◽  
Water Stress ◽  
Stress Detection ◽  
New Approach ◽  
Ndvi Time Series

scholarly journals Support Vector Machine based Stress Detection System to manage COVID-19 pandemic related stress from ECG signal

2021 ◽  
Vol 20 (1) ◽  
pp. 8-16
Author(s):  
Md Fahim Rizwan ◽  
Rayed Farhad ◽  
Md. Hasan Imam
Keyword(s):  
Support Vector Machine ◽  
Detection System ◽  
Health Condition ◽  
Cardiac Patients ◽  
Gaussian Kernel ◽  
Training Dataset ◽  
Support Vector ◽  
Portable Devices ◽  
Stress Detection ◽  
Specialist Doctor

This study represents a detailed investigation of induced stress detection in humans using Support Vector Machine algorithms. Proper detection of stress can prevent many psychological and physiological problems like the occurrence of major depression disorder (MDD), stress-induced cardiac rhythm abnormalities, or arrhythmia. Stress induced due to COVID -19 pandemic can make the situation worse for the cardiac patients and cause different abnormalities in the normal people due to lockdown condition. Therefore, an ECG based technique is proposed in this paper where the ECG can be recorded for the available handheld/portable devices which are now common to many countries where people can take ECG by their own in their houses and get preliminary information about their cardiac health. From ECG, we can derive RR interval, QT interval, and EDR (ECG derived Respiration) for developing the model for stress detection also. To validate the proposed model, an open-access database named "drivedb” available at Physionet (physionet.org) was used as the training dataset. After verifying several SVM models by changing the ECG length, features, and SVM Kernel type, the results showed an acceptable level of accuracy for Fine Gaussian SVM (i.e. 98.3% for 1 min ECG and 93.6 % for 5 min long ECG) with Gaussian Kernel while using all available features (RR, QT, and EDR). This finding emphasizes the importance of including ventricular polarization and respiratory information in stress detection and the possibility of stress detection from short length data(i.e. form 1 min ECG data), which will be very useful to detect stress through portable ECG devices in locked down condition to analyze mental health condition without visiting the specialist doctor at hospital. This technique also alarms the cardiac patients form being stressed too  much which might cause severe arrhythmogenesis.

scholarly journals Water stress coefficient determined by orbital remote sensing techniques

2020 ◽  
Vol 24 (12) ◽  
pp. 847-853
Author(s):  
Élvis da S. Alves ◽  
Roberto Filgueiras ◽  
Lineu N. Rodrigues ◽  
Fernando F. da Cunha ◽  
Catariny C. Aleman
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Irrigation Management ◽  
Simple Algorithm ◽  
Landsat 8 ◽  
Stress Coefficient ◽  
Use Efficiency ◽  
Remote Sensing Techniques ◽  
Water Stress Coefficient ◽  
The Relationship

ABSTRACT In regions where the irrigated area is increasing and water availability is reduced, such as the West of the Bahia state, Brazil, the use of techniques that contribute to improving water use efficiency is paramount. One of the ways to improve irrigation is by improving the calculation of actual evapotranspiration (ETa), which among other factors is influenced by soil drying, so it is important to understand this relationship, which is usually accounted for in irrigation management models through the water stress coefficient (Ks). This study aimed to estimate the water stress coefficient (Ks) through information obtained via remote sensing, combined with field data. For this, a study was carried out in the municipality of São Desidério, an area located in western Bahia, using images of the Landsat-8 satellite. Ks was calculated by the relationship between crop evapotranspiration and ETa, calculated by the Simple Algorithm for Evapotranspiration Retrieving (SAFER). The Ks estimated by remote sensing showed, for the development and medium stages, average errors on the order of 5.50%. In the final stage of maize development, the errors obtained were of 23.2%.

Plant Water Stress Detection Using Leaf Temperature and Microclimatic Information

2011 ◽  
Author(s):  
Vasu Udompetaikul ◽  
Shrini K Upadhyaya ◽  
David C Slaughter ◽  
Bruce D Lampinen ◽  
Ken A Shackel
Keyword(s):  
Water Stress ◽  
Leaf Temperature ◽  
Plant Water ◽  
Stress Detection ◽  
Plant Water Stress
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