Kaolin Film Increases Gas Exchange Parameters of Coffee Seedlings During Transference From Nursery to Full Sunlight

Increases in water use efficiency (WUE) and the reduction of negative impacts of high temperatures associated with high solar radiation are being achieved with the application of fine particle film of calcined and purified kaolin (KF) on the leaves and fruits of various plant species. KF was applied on young Coffea arabica and Coffea canephora plants before their transition from nursery to full sunlight during autumn and summer. The effects of KF were evaluated through the responses of leaf temperature (Tleaf), net CO2 assimilation rate (A), stomatal conductance (gs), transpiration (E), WUE, crop water stress index (CWSI), index of relative stomatal conductance (Ig), initial fluorescence (F0), and photosynthetic index (PI) in the first 2–3 weeks after the plant transitions to the full sun. All measurements were performed at midday. In Coffea plants, KF decreased the Tleaf up to 6.7°C/5.6°C and reduced the CWSI. The plants that were not protected with KF showed lower A, gs, E, and Ig than those protected with KF. C. canephora plants protected with KF achieved higher WUE compared with those not protected by 11.23% in autumn and 95.58% in summer. In both Coffea sp., KF application reduced F0, indicating reduced physical dissociation of the PSII reaction centers from the light-harvesting system, which was supported with increased PI. The use of KF can be recommended as a management strategy in the transition of Coffea seedlings from the nursery shade to the full sunlight, to protect leaves against the excessive solar radiation and high temperatures, especially in C. canephora during the summer.

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Estimation of Stomatal Conductance using Crop Water Stress Index based on the Thermal Image at a Leaf Scale

10.5194/egusphere-egu2020-11926 ◽

2020 ◽

Author(s):

Hoejeong Jeong ◽

Jae-Hyun Ryu ◽

Sang-il Na ◽

Jaeil Cho

Keyword(s):

Water Stress ◽

Stomatal Conductance ◽

Thermal Image ◽

Crop Growth ◽

Leaf Temperature ◽

Stress Index ◽

Crop Water ◽

Crop Water Stress Index ◽

Water Stress Index ◽

Crop Water Stress

&#160; In 1980s, Crop Water Stress Index (CWSI) is suggested to indicate the water stress of crops. CWSI is based on the leaf energy balance, which is closely related to leaf temperature. To calculate CWSI, meteorological factors such as air temperature and vapor pressure deficit should be measured besides leaf temperature. As recent technology has been developed, leaf temperature can be easily observed by thermal camera or infrared thermometer. Stomatal conductance (gs, mmol m-2 s-1) is one of the critical factors to understand crop photosynthesis and water demand. In addition, the behaviors of gs can represent the biotic and abiotic plant stresses. In abnormal condition, such as drought, insects or disease, gs getting lower. The observation of gs will make better to evaluate and predict crop growth and conditions. Therefore, the time series data of gs is useful for the monitoring of crop growth and the quick detection of abnormal crop condition in smart-farming system but there are some limitations to measure gs continuously and easily.&#160; We assume that there is some relationship between CWSI and gs because both has strong relation to leaf temperature. Thus, the aim of this study is to investigate possibility of estimation of gs using CWSI which is derived from thermal image. Through the data collected from literatures, negative correlations between CWSI and gs were revealed. The slope of correlation was changed according to crop types. In addition, as a result of simulation, there is almost linear negative relationship between CWSI and gs, and the slope was determined by maximum stomatal conductance (gs_max). Field measurement in this study was also demonstrated to identify such correlation. Further, various methods to measure CWSI were tested. This relationship will contribute to not only monitoring of crop stress for irrigation scheduling in smart farm system but also estimating evapotranspiration, photosynthesis, and crop yield.

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Monitoring Crop Water Status and Irrigation Needs Using Multispectral Airborne Sensors

HortScience ◽

10.21273/hortsci.30.4.905d ◽

1995 ◽

Vol 30 (4) ◽

pp. 905D-905

Author(s):

Thomas R. Clarke ◽

M. Susan Moran

Keyword(s):

Water Stress ◽

Near Infrared ◽

Water Status ◽

Canopy Cover ◽

Stress Index ◽

Crop Water ◽

Vegetative Cover ◽

Crop Water Stress Index ◽

Water Stress Index ◽

Subsurface Drip

Water application efficiency can be improved by directly monitoring plant water status rather than depending on soil moisture measurements or modeled ET estimates. Plants receiving sufficient water through their roots have cooler leaves than those that are water-stressed, leading to the development of the Crop Water Stress Index based on hand-held infrared thermometry. Substantial error can occur in partial canopies, however, as exposed hot soil contributes to deceptively warm temperature readings. Mathematically comparing red and near-infrared reflectances provides a measure of vegetative cover, and this information was combined with thermal radiance to give a two-dimensional index capable of detecting water stress even with a low percentage of canopy cover. Thermal, red, and near-infrared images acquired over subsurface drip-irrigated cantaloupe fields demonstrated the method's ability to detect areas with clogged emitters, insufficient irrigation rate, and system water leaks.

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

Agricultural Water Management ◽

10.1016/j.agwat.2012.12.004 ◽

2013 ◽

Vol 118 ◽

pp. 79-86 ◽

Cited By ~ 47

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

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Practical Applications of a Multisensor UAV Platform Based on Multispectral, Thermal and RGB High Resolution Images in Precision Viticulture

Agriculture ◽

10.3390/agriculture8070116 ◽

2018 ◽

Vol 8 (7) ◽

pp. 116 ◽

Cited By ~ 30

Author(s):

Alessandro Matese ◽

Salvatore Di Gennaro

Keyword(s):

Water Stress ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Stress Index ◽

Crop Water Stress Index ◽

Practical Applications ◽

Water Stress Index ◽

Sensing Applications ◽

Wide Range ◽

Precision Viticulture

High spatial ground resolution and highly flexible and timely control due to reduced planning time are the strengths of unmanned aerial vehicle (UAV) platforms for remote sensing applications. These characteristics make them ideal especially in the medium–small agricultural systems typical of many Italian viticulture areas of excellence. UAV can be equipped with a wide range of sensors useful for several applications. Numerous assessments have been made using several imaging sensors with different flight times. This paper describes the implementation of a multisensor UAV system capable of flying with three sensors simultaneously to perform different monitoring options. The intra-vineyard variability was assessed in terms of characterization of the state of vines vigor using a multispectral camera, leaf temperature with a thermal camera and an innovative approach of missing plants analysis with a high spatial resolution RGB camera. The normalized difference vegetation index (NDVI) values detected in different vigor blocks were compared with shoot weights, obtaining a good regression (R2 = 0.69). The crop water stress index (CWSI) map, produced after canopy pure pixel filtering, highlighted the homogeneous water stress areas. The performance index developed from RGB images shows that the method identified 80% of total missing plants. The applicability of a UAV platform to use RGB, multispectral and thermal sensors was tested for specific purposes in precision viticulture and was demonstrated to be a valuable tool for fast multipurpose monitoring in a vineyard.

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Detecting Plant Stress Using Thermal and Optical Imagery From an Unoccupied Aerial Vehicle

Frontiers in Plant Science ◽

10.3389/fpls.2021.734944 ◽

2021 ◽

Vol 12 ◽

Author(s):

Bonny Stutsel ◽

Kasper Johansen ◽

Yoann M. Malbéteau ◽

Matthew F. McCabe

Keyword(s):

Salinity Stress ◽

Vegetation Index ◽

Plant Stress ◽

Infrared Camera ◽

Water Security ◽

Optical Data ◽

Stress Index ◽

Crop Water Stress Index ◽

Water Stress Index ◽

Management Interventions

Soil and water salinization has global impact on the sustainability of agricultural production, affecting the health and condition of staple crops and reducing potential yields. Identifying or developing salt-tolerant varieties of commercial crops is a potential pathway to enhance food and water security and deliver on the global demand for an increase in food supplies. Our study focuses on a phenotyping experiment that was designed to establish the influence of salinity stress on a diversity panel of the wild tomato species, Solanum pimpinellifolium. Here, we explore how unoccupied aerial vehicles (UAVs) equipped with both an optical and thermal infrared camera can be used to map and monitor plant temperature (Tp) changes in response to applied salinity stress. An object-based image analysis approach was developed to delineate individual tomato plants, while a green–red vegetation index derived from calibrated red, green, and blue (RGB) optical data allowed the discrimination of vegetation from the soil background. Tp was retrieved simultaneously from the co-mounted thermal camera, with Tp deviation from the ambient temperature and its change across time used as a potential indication of stress. Results showed that Tp differences between salt-treated and control plants were detectable across the five separate UAV campaigns undertaken during the field experiment. Using a simple statistical approach, we show that crop water stress index values greater than 0.36 indicated conditions of plant stress. The optimum period to collect UAV-based Tp for identifying plant stress was found between fruit formation and ripening. Preliminary results also indicate that UAV-based Tp may be used to detect plant stress before it is visually apparent, although further research with more frequent image collections and field observations is required. Our findings provide a tool to accelerate field phenotyping to identify salt-resistant germplasm and may allow farmers to alleviate yield losses through early detection of plant stress via management interventions.

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