Despite its potential benefits, dual land use for crop growth and electricity generation (agrivoltaics) is not widespread. This study investigates the effect of two types of organic photovoltaic (OPV) modules (red and blue), which differ by spectral characteristics, on greenhouse microclimate and crop performance. The characteristics of the OPV modules were first determined outside greenhouses. Then, experiments involving a tomato crop were done in three greenhouses. Two greenhouses had modules installed above the canopy, at gutter height, while the third served as a control without modules. Radiation transmittance values of the red and blue modules were 32.2 and 28.8%, respectively. The installation of OPV modules resulted in a similar reduction of irradiance at the canopy level, about 38%, in the two OPV greenhouses (OPVGs). Dust accumulation over 11 months of installation inside the greenhouses reduced radiation transmission of the red and blue modules by 2.6 & PLUSMN; 0.8% and 4.9 & PLUSMN; 1.8% (absolute values), respectively. The amount of solar radiation transferred to sensible and latent heat depended apparently on the modules' radiometric characteristics. The level of diffuse radiation in the global solar radiation affected the temperature of the modules. In the control greenhouse, the accumulated yield was higher than in the blue and red OPVGs by 15% and 9%, respectively. Yet, the ratio of accumulated yield to irradiance at the canopy level was higher in the OPVGs. There were no significant differences among the greenhouses concerning the acidity and sugar content of the tomatoes.& COPY; 2023 IAgrE. Published by Elsevier Ltd. All rights reserved.

Since leaf temperature (LT) is not a trivial measurement, deep-neural networks (DNN) and machine learning (ML) models were evaluated in this study as tools for estimating foliage temperature. Two DNN methods were used. The first DNN used convolutional layers, while the second DNN was based on fully-connected layers and was trained by cross-validation techniques. The machine learning used the K-nearest neighbors (KNN) method for LT estimation. All models used the meteorological and microclimatic parameters (hereafter referred to as features) of the examined greenhouses to determine the average foliage temperature. The models were trained on 75% of the collected data and tested on the remaining 25%. RMS and absolute error were used to evaluate the performance of the different models compared to the LT values measured by a thermal camera. In addition, after finding the correlation of each feature to the leaf temperature, the models were trained based on the high-correlated features only. The machine learning model was superior to DNN when all available features were used and when only high-correlated features were used, resulting in errors of 0.7 °C and 0.8 °C, respectively.

A study related to the application of organic photovoltaic (OPV) modules in greenhouses is presented. It considers the impact of nonhomogeneous shading by semitransparent OPV modules, placed on the cover of a greenhouse tunnel housing a tomato crop, on energy partitioning and the spatial variability of radiation, air temperature and vapour pressure deficit (VPD) within the tunnel. Experiments were conducted in two similar tunnels covered by a diffuse polyethylene sheet. Flexible semitransparent strips of OPV modules were placed on 37% of the roof area of one tunnel, creating an approximately 23% nonhomogeneous shading, while the other tunnel, homogeneously shaded by a 25% black shading net, served as a control greenhouse. The results show that on cloudy days (high diffuse radiation), spatial variability of radiation in the OPV tunnel was smaller than on sunny days (low diffuse radiation). Conversely, variability in air temperature and VPD did not change much with the change in diffuse radiation. Except when diffuse radiation was high, no significant difference in the energy partitioning between nonhomogeneous shading by OPVs and homogeneous shading was observed. Most of the net radiation in the tunnels was converted into latent heat. With a high solar elevation angle, the spatial variability of radiation within the tunnel was higher than with a low solar elevation angle. Additional experiments are needed to determine the best arrangement of semitransparent OPV modules on the roof, without resulting in any significant increase in spatial variability. Agronomic aspects of plant growth under the OPV modules are briefly presented.

Agricultural industry is facing a serious threat from plant diseases that cause production and economic losses. Early information on disease development can improve disease control using suitable management strategies. This study sought to detect downy mildew (Peronospora) on grapevine (Vitis vinifera) leaves at early stages of development using thermal imaging technology and to determine the best time during the day for image acquisition. In controlled experiments, 1587 thermal images of grapevines grown in a greenhouse were acquired around midday, before inoculation, 1, 2, 4, 5, 6, and 7 days after an inoculation. In addition, images of healthy and infected leaves were acquired at seven different times during the day between 7:00 a.m. and 4:30 p.m. Leaves were segmented using the active contour algorithm. Twelve features were derived from the leaf mask and from meteorological measurements. Stepwise logistic regression revealed five significant features used in five classification models. Performance was evaluated using K-folds cross-validation. The support vector machine model produced the best classification accuracy of 81.6%, F1 score of 77.5% and area under the curve (AUC) of 0.874. Acquiring images in the morning between 10:40 a.m. and 11:30 a.m. resulted in 80.7% accuracy, 80.5% F1 score, and 0.895 AUC.

This paper presents the electrical performance of organic photovoltaic modules (OPVs) on top of a polyethylene covered greenhouse high tunnel in a Mediterranean climate. Modules from a previous study were kept on the tunnel and monitored together with new modules with improved connectors installed on the greenhouse roof and on frames adjacent to the greenhouse. Measured module power conversion efficiencies ranged from 1% to 3%. The typical combined output of the modules across the tunnel roof were 105Wh on a sunny day and 81Wh on a cloudy day. Module burn-in period was about 15 days, losing around 36% of its initial efficiency. Ts80 lifetimes ranged from 7 days to 94 days. Tunnel integration was shown to accelerate module degradation.

The use of flexible and semi-transparent organic photovoltaic (OPV) modules as shading elements in a greenhouse tunnel with a tomato crop is presented. Experiments were performed in two similar greenhouse tunnels, covered by diffuse polyethylene sheet, during two summer growing seasons. In 2018, one tunnel was shaded using OPV modules (covering 37% of the roof area and resulting in 23% shading) and the second tunnel served as a control. In 2019, a 25% black shading screen was added to the control tunnel. The microclimate, yield, and physiological parameters were examined in the two tunnels. Results show that at noon (11:00 to 13:00), there was no significant difference in the mean seasonal (June-September 2018, May-August 2019) air temperature and humidity between the tunnels. In 2018, the tunnels differed in terms of the spatial radiation transmittance and leaf temperature. The average radiation level along the OPV tunnel centreline was much lower, and the radiation distribution was less homogeneous than in the control. In 2019, with similar shading percentages in the tunnels, similar average radiation levels were observed. The leaf temperature in the OPV was lower than in the control in 2018 and varied from higher to lower in 2019. The leaf area index (LAI), cumulative yield, and average fruit mass were higher in the OPV than in the control in 2018, and similar in 2019. The average value of the maximum power output of three OPV modules increased roughly linearly with irradiance. (C) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.

This study examines the feasibility of using semi-transparent, flexible organic photovoltaic (OPV) modules as greenhouse shading material. By using such modules, it may be possible to utilise existing greenhouse-based agricultural areas for electricity production. Using OPV modules to shade greenhouses and reduce excess solar energy may result in reduced heat load on the crop on the one hand, and use of renewable energy on the other. We examined the radiometric and thermal properties of an OPV module. Module transmissivity was measured under outdoor conditions at four different angles of radiation incidence: 0, 21, 41 and 46 degrees. Simultaneously, the open-circuit voltage, and short-circuit current of the module were recorded for power and efficiency calculations. Supplementary laboratory measurements of transmissivity, reflectivity and absorptivity were performed with a spectroradiometer. To further characterise the OPV module, its overall heat-transfer coefficient (U value) was determined. The examined module had about 20% transmissivity, 15% reflectivity and 65% absorptance in the photosynthetically active radiation (PAR) range. The mean daily power conversion efficiency of the module was about 0.8% and the overall heat transfer coefficient U, was about 6.0 Wm(-2) K-1. The temperature of a module placed on the polyethylene cover of a greenhouse high tunnel was about 50-55 degrees C at midday. Thermal images of the module revealed non-uniform heat distribution, with temperature differences between regions reaching up to 7.5 degrees C. OPV modules appear to be suitable for greenhouse shading and electricity generation but currently they are too expensive and their life duration is relatively short. (C) 2019 IAgrE. Published by Elsevier Ltd. All rights reserved.

An experiment was conducted to study the effect of structure height on air temperature and humidity, on air exchange rate and on transpiration and yield in an insect-proof screenhouse. Two houses with roof heights of 4 and 6 m, and impermeable polyethylene sheets on the sidewalls were examined. Air exchange with the outside environment took place only through the horizontal screened roof and tomato plants were grown in both houses. The results showed that the increase in screenhouse height from 4 to 6 m elicited almost no changes in daily mean air temperature, humidity ratio and consequently, in relative humidity within the canopy. However, it reduced by about 30% the airflow through the screenhouse and consequently the air exchange rate. Moreover, the increase in height did not elicit changes in crop transpiration, yield and plant development. Thus, it is concluded that in insect-proof screenhouses that are ventilated through the roof, there is no benefit in increasing structure height above the current common height of about 4 m. (C) 2017 IAgrE. Published by Elsevier Ltd. All rights reserved.

An experiment was conducted to assess the effect of leaf pruning on energy partitioning and microclimate in a screenhouse with a tomato crop. The experiment was conducted in a flat-roof insect-proof screenhouse, 4 m in height with a floor area of 745 m(2), which was ventilated only through the roof. Measurements included global solar radiation inside and outside the screenhouse, net radiation, soil heat flux, transpiration, air velocity and air temperature and humidity. The results showed that leaf pruning in a tomato crop significantly affects energy partitioning in a screenhouse: it reduced transpiration at noon by more than 100%, increased soil heat flux by more than 200% and consequently increased sensible heat flux from crop to screenhouse air by nearly 70%. As a result of leaf pruning, air temperature increased slightly, but vapour-pressure deficit increased significantly. Furthermore, leaf pruning strongly reduced the gradients of temperature and vapour pressure deficit in the air layer above the canopy at noon, resulting in a more homogeneous environment in the vertical direction. Finally, leaf pruning contributed to a higher air velocity within the canopy, especially at high wind speed. (C) 2016 IAgrE. Published by Elsevier Ltd. All rights reserved.

Hexokinase (HXK) is a sugar-phosphorylating enzyme involved in sugar-sensing. It has recently been shown that HXK in guard cells mediates stomatal closure and coordinates photosynthesis with transpiration in the annual species tomato and Arabidopsis. To examine the role of HXK in the control of the stomatal movement of perennial plants, we generated citrus plants that express Arabidopsis HXK1 (AtHXK1) under KST1, a guard cell-specific promoter. The expression of KST1 in the guard cells of citrus plants has been verified using GFP as a reporter gene. The expression of AtHXK1 in the guard cells of citrus reduced stomatal conductance and transpiration with no negative effect on the rate of photosynthesis, leading to increased water-use efficiency. The effects of light intensity and humidity on stomatal behavior were examined in rooted leaves of the citrus plants. The optimal intensity of photosynthetically active radiation and lower humidity enhanced stomatal closure of AtHXK1-expressing leaves, supporting the role of sugar in the regulation of citrus stomata. These results suggest that HXK coordinates photosynthesis and transpiration and stimulates stomatal closure not only in annual species, but also in perennial species.

In many countries fine mesh screens are used to protect agricultural crops. The low porosity of such screens impedes the exchange of mass, heat and momentum between the air around the crop and that occur in the atmosphere, thereby modifying the crop microclimate. Experiments were carried out aimed at determining the internal airflow characteristics and patterns of screenhouses. The results showed that screenhouses reduced air velocity compared to that in an open field. For a given windspeed the air velocity inside the screenhouse increased with height. The internal air velocity increased with external windspeed but it increased to a greater extent near to the roof. Flow patterns and characteristics were affected by whether the screenhouse was ventilated only via the roof or via the roof and sidewalls. When the screenhouse was ventilated from the roof and side panels the air velocity was higher than under roof ventilation alone, and the airflow direction, both within the canopy and above it, was usually in a similar direction to that of the outside wind. However, under roof ventilation alone the internal airflow direction was generally opposite to that of the external wind, resulting in outflow through the windward section of the roof and inflow through the leeward section. In the central region of the screenhouse the mean vertical velocity within the canopy was near zero and its fluctuations with time were relatively small. Near the roof, there was a mean net inflow and the velocity fluctuations were much larger. (C) 2015 IAgrE. Published by Elsevier Ltd. All rights reserved.

Thermal crop sensing technologies have potential as tools for monitoring and mapping crop water status. To create maps of water status from thermal images, a reliable relationship between direct water status measures like leaf water potential (LWP) and thermal water status measures like temperature and crop water stress index (CWSI) should be established for different crops and for different growth stages. The objective of this study was to define the relationships for cotton between LWP and CWSI derived from high-resolution ground-based thermal images and more specifically to examine whether robust relationships exist between the two measures for different varieties, through a cotton growing season, across seasons and under different geographical areas (different climate and soils). A dataset from three cotton growing seasons and from different geographical areas was built to explore the relationship between CWSI and LWP in cotton. CWSI was calculated based on ground-based thermal images and measured dry (T air  + 5 °C) and wet references (Artificial wet reference surface—AWRS). A linear CWSI–LWP relationship was found with high coefficient of determination (R2 = 0.7). This relationship changed over the cotton growth stages and different CWSI–LWP relationships were established to the flowering, boll-filling and defoliation stages. The boll-filling relationship was found to be insensitive to a range of meteorological conditions. The flowering and the boll-filling models were initially validated using diagonal (oblique) thermal images from dates that were not used for calibration. For CWSI calculation, the average temperature of the lowest decile was used for the wet reference instead of the AWRS. The comparison between predicted and observed values of the validation sets yielded RMSE of 0.18 and 0.15 for the flowering and boll-filling stages, respectively. The successful use of the lowest decile as the wet reference enables a future application of the CWSI–LWP relationship to map LWP at a commercial field scale.

Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved.

Information regarding tree water status in irrigated olive orchards is essential for managing growth to optimize yields and olive oil quality. One management practice option is to monitor or sample individual trees and use this information for orchard-scale management. This study assessed the ability of thermal imaging to provide the spatial distribution and variability of tree water status in a commercial irrigated olive orchard, and described strategies and a procedure for choosing which individual trees best represent the orchard. The study employed gradual upscaling from individual trees grown in lysimeters, through a controlled experimental field plot, to a commercial orchard. Thermal imaging of olive trees grown in lysimeters attested the sensitivity of the technique to identify mild-level water stress by correlating crown temperatures to stem water potential. Knowledgeable choice of five or ten representative trees in the experimental plot, based on the histogram distribution obtained for the entire experimental orchard, lead to successful reconstruction of the spatial distribution of canopy temperature, and thus of water status. Positively skewed distributions of crown temperatures found in both the field plot and commercial orchard suggested distinct patterns, where the canopy temperature of the majority of the trees was lower than the average, and a relatively small number of trees had significantly higher temperatures and suggest commercial practicality of the proposed methodology. Thermal imaging can therefore serve as a useful tool for determining representative trees that, if frequently monitored, or instrumented with continuous water status sensors, can provide important information for orchard water management.

Potato yield and quality are highly dependent on an adequate supply of water. In this study, 3 years of information from thermal and RGB images were collected to evaluate water status in potato fields. Irrigation experiments were conducted in commercial potato fields (Desiree; drippers). Two water-deficit scenarios were tested: a short-term water deficit (by suppressing irrigation for a number of days before image acquisition), and a long-term cumulative water deficit. Ground and aerial images were acquired in various phenological stages along the potato growing season. Effects of irrigation treatments were recorded by thermal indices and biophysical measurements of stomatal conductance (SC), leaf water potential, leaf osmotic potential and gravimetric water potential in soil. Canopy temperature was delineated from the thermal images with and without fused information from the RGB image. Crop water stress index (CWSI) was calculated, using three forms of minimum baseline temperature: empirical, theoretical and statistical. An empirical evaluation of maximum baseline temperature of Tair + 7 °C was used in all CWSI forms examined. Statistical tests and comparison of CWSI with biophysical measurements were performed to evaluate the responses to irrigation treatments. The results indicated a high correlation of CWSI with SC from tuber initiation to maturity based on ground and aerial data (0.64 ≤ R2 ≤ 0.99). Similar trends of increasing CWSI from well to deficit-irrigated treatments were found in all three growing seasons. The results also showed that CWSI may be calculated based merely on thermal imagery data.

Increased expression of the aquaporin NtAQP1, which is known to function as a plasmalemma channel for CO2 and water, increases the rate of both photosynthesis and transpiration. In contrast, increased expression of Arabidopsis hexokinase1 (AtHXK1), a dual-function enzyme that mediates sugar sensing, decreases the expression of photosynthetic genes and the rate of transpiration and inhibits growth. Here, we show that AtHXK1 also decreases root and stem hydraulic conductivity and leaf mesophyll CO2 conductance (g m). Due to their opposite effects on plant development and physiology, we examined the relationship between NtAQP1 and AtHXK1 at the whole-plant level using transgenic tomato plants expressing both genes simultaneously. NtAQP1 significantly improved growth and increased the transpiration rates of AtHXK1-expressing plants. Reciprocal grafting experiments indicated that this complementation occurs when both genes are expressed simultaneously in the shoot. Yet, NtAQP1 had only a marginal effect on the hydraulic conductivity of the double-transgenic plants, suggesting that the complementary effect of NtAQP1 is unrelated to shoot water transport. Rather, NtAQP1 significantly increased leaf mesophyll CO2 conductance and enhanced the rate of photosynthesis, suggesting that NtAQP1 facilitated the growth of the double-transgenic plants by enhancing mesophyll conductance of CO2.

In previous studies, a model for assessing leaf water potential (LWP) in cotton plants based on Crop Water Stress Index (CWSI) calculated using ground thermal imagery and artificial wet reference (AWR), as the minimum temperature, was developed and validated. The AWR cannot be measured from aerial thermal images and in order to implement this approach, it is essential to characterize the minimum boundary reference temperature and to evaluate the validity of the CWSI-LWP relationship. Four types of minimum references were examined: artificial, theoretical, plant and virtual. Three aerial thermal images were acquired above a cotton field. The best relationship was found between calculated and measured LWP using the virtual reference: high correlation and 1:1 fit. This means that a reliable LWP map of a cotton field can be created using only an aerial thermal image and air temperature. Using the LWP-CWSI relationship, the LWP can be mapped for each pixel or for each area of interest such as an irrigation section or pre-defined management zone.