Search

Accurate canopy extraction and temperature calculations are crucial to minimizing inaccuracies in thermal image-based estimation of orchard water status. Currently, no quantitative comparison of canopy extraction methods exists in the context of precision irrigation. The accuracies of four canopy extraction methods were compared, and the effect on water status estimation was explored for these methods: 2-pixel erosion (2PE) where non-canopy pixels were removed by thresholding and morphological erosion; edge detection (ED) where edges were identified and morphologically dilated; vegetation segmentation (VS) using temperature histogram analysis and spatial watershed segmentation; and RGB binary masking (RGB-BM) where a binary canopy layer was statistically extracted from an RGB image for thermal image masking. The field experiments occurred in a four-hectare commercial peach orchard during the primary fruit growth stage (III). The relationship between stem water potential (SWP) and crop water stress index (CWSI) was established in 2018. During 2019, a large dataset of ten thermal infrared and two RGB images was acquired. The canopy extraction methods had different accuracies: on 12 August, the overall accuracy was 83% for the 2PE method, 77% for the ED method, 84% for the VS method, and 90% for the RGB-BM method. Despite the high accuracy of the RGB-BM method, canopy edges and between-row weeds were misidentified as canopy. Canopy temperature and CWSI were calculated using the average of 100% of canopy pixels (CWSI_T100%) and the average of the coolest 33% of canopy pixels (CWSI_T33%). The CWSI_T33% dataset produced similar SWP–CWSI models irrespective of the canopy extraction method used, while the CWSI_T100% yielded different and inferior models. The results highlighted the following: (1) The contribution of the RGB images is not significant for canopy extraction. Canopy pixels can be extracted with high accuracy and reliability solely with thermal images. (2) The T33% approach to canopy temperature calculation is more robust and superior to the simple mean of all canopy pixels. These noteworthy findings are a step forward in implementing thermal imagery in precision irrigation management. [ABSTRACT FROM AUTHOR]

An ecoinformatics approach was used to test how two noxious species in grapevines with varying host preferences and movement characteristics: the European grapevine moth (Lobesia botrana), and a parasitic fungus, the grape powdery mildew (Uncinula necator), are affected by local and landscape variables. Data were collected from 202 vineyards during four seasons: 2013, 2014, 2016 and 2017 and analysed using generalized mixed models. We hypothesized that the European grapevine moth would be affected most by the landscape variables, while the grape powdery mildew would be affected most by local ones. We found that the number of sprayings during the season was an important variable explaining variation in infestation levels between vineyards for both species. At the landscape scale, we found larger variations in the relationship between the studied variables and the two pests, but both were also affected by the surrounding land use including areas of deciduous orchards. Understanding the factors that affect the occurrence of various pests in the same environment might improve farmers' decision‐making. [ABSTRACT FROM AUTHOR]

Mediterranean Fruit Fly (medfly), Ceratitis capitata (Wiedemann), is considered to be one of the most destructive fruit insect pests throughout the world. In recent years, the temporal dynamics of the medfly have been extensively studied by season, and, to a lesser extent, on a daily basis. We exploited, for the first time, a sequential automatic medfly male trapping system, in combination with climate data, to characterize diel flight patterns of male medflies trapped. The process was carried out in four commercial citrus fields over three growing seasons. Results showed that throughout the year, medfly flight activity began 4–6 hr after sunrise and peaked up to 2 to 3 hr before sunset. Generalized additive models (GAM) of the 934 days sampled revealed that in the fall, the diurnal flight activity was unimodal, that is, it began increasing at noon, peaking in the afternoon. By contrast, in the spring and summer, the diurnal flight activity exhibited a bimodal pattern, decreasing at midday. GAMs also revealed that hour after sunrise and temperature influenced medfly captures, with the former the more dominant factor. Thus, photophase significantly impacted the medfly's diurnal flight activity in each season. This study demonstrated that automatic traps that timestamp each capture are a primary research tool in insect flight activity studies that contributes to understanding diurnal insect activity within the growing season. [ABSTRACT FROM AUTHOR]

Understanding species movement in the agroecological system is an important theme in ecology. A mark–release–capture experiment was conducted to study the dispersion behaviour of the Mediterranean fruit fly, Ceratitis capitata (Wied.; Diptera: Tephritidae; Medfly) in northern Israel. Four pairs of pear and citrus orchards were selected for the field experiments. Sterile flies dyed with different colours were released in three seasons during 2015 and 2016, based on the phenological stages of the hosts. The total number of captured marked sterile flies per trap (FT) was approx 300 in both April and August. In November, FT values decreased by about 35% to approximately 200. The wild Medfly that were also captured showed an opposite trend, from an FT of 1.8 and 6.4 in April and August, respectively, to an FT of about 330 in November. Marked sterile flies were captured in both the release and the neighbouring orchard sites. We found that the Medfly migrates from pear to citrus orchards during spring and from citrus to pear during summer, when there are no fruit‐bearing trees in the orchards. However, during November, when the wild Medfly population prevails in the area, a clear pattern of migration is hard to identify, perhaps because of a possible interaction with the wild fly's population. [ABSTRACT FROM AUTHOR]

Increasing global water deficit and demand for yield improvement call for high-resolution monitoring of irrigation, crop water stress, and crops' general condition. To provide high spatial resolution with high-temperature accuracy, remote sensing is conducted at low altitudes using radiometric longwave thermal infrared cameras. However, the radiometric cameras' price, and the low altitude leading to low coverage in a given time, limit the use of radiometric aerial surveys for agricultural needs. This paper presents progress toward solving both limitations using algorithmic and computational imaging methods: stabilizing the readout of low-cost thermal cameras to obtain radiometric data, and improving the latter's low resolution by applying convolutional neural network-based super-resolution. The two methods were merged by an end-to-end algorithm pipeline, providing a large mosaicked image of the field. First, the potential capabilities of a joint estimation method to correct unknown offset and gain were simulated on remotely sensed agricultural data. Comparison to ground-truth measurements showed radiometric accuracy with a root mean square error (RMSE) of 1.3 °C to 1.8 °C. Then, the proposed super-resolution method was demonstrated on experimental and simulated remotely sensed agricultural data. Preliminary experimental results showed 50% improvement in image sharpness relative to bicubic interpolation. The performance of the algorithm was evaluated on 22 simulated cases at × 2 and × 4 magnification. Finally, image mosaicking using the proposed pipeline was demonstrated. A mosaicked image composed of sub-images pre-processed by the proposed computational methods resulted in a RMSE in temperature of 0.8 °C, as compared to 8.2 °C without the initial processing. [ABSTRACT FROM AUTHOR]

The red palm weevil (RPW), Rhynchophorus ferrugineus, an oligophagous borer that specifically attacks the Arecaceae family, poses a serious threat to commercial and ornamental palms. Originally from tropical Asia, the RPW has spread to Africa and Europe, reaching the Mediterranean region 30 year ago. Characterizing its spread is a key aspect of effectively managing its geographical expansion. Using georeferenced RPW occurrence data from 2012 to 2013 in Israel, we sought to better understand its spatial spread. Our objectives were to: (1) describe the spatiotemporal distribution of RPW in three regions (northern, western and southern) that were thought to constitute a risk to the vast date palm plantations across the Beit She'an Valley (BSH), (2) quantify the dynamics of spread; and (3) initially characterize the influence of host species on RPW dispersal. We found that the spatiotemporal distribution of RPW significantly differed between regions. The weevils' geographical occupancy areas increased by 853% and 571% in the northern and western regions, respectively, while no increase was observed in the southern region. In the northern and western regions, RPW spread toward BSH date palm plantations and an initial analysis has shown that host area and RPW captures were significantly correlated. Based on our analysis, we propose the following hypotheses: (1) Ornamental and particularly Canary palms are highly favorable hosts for population establishment and dispersal in comparison with date palm plantations; (2) thus, the RPW spread from urban areas toward date palm plantations in BSH is attributed to the density and distribution of these hosts. [ABSTRACT FROM AUTHOR]

The Mediterranean fruit fly, Ceratitis capitata (Wied.) (Diptera: Tephritidae) (medfly), is a major pest among all varieties of citrus. Despite advances in recent years, knowledge about the effects of various variables on the spatiotemporal spread of the medfly is still limited. The goal of this study was to characterize the effects of various local and landscape variables on the population density of medfly in citrus orchards in Israel, utilizing the ecoinformatics approach. Data were collected during three citrus growing seasons (years). The medfly population data consisted of a weekly inspection of ~ 2300 traps. Thirteen potentially explanatory variables believed to influence the medfly populations were quantified. The contributions of the explanatory variables were analyzed using multimodel inference. Results show that the medfly population is affected by both local and landscape variables. Further analysis was focused on the data from November (representing the fall peak) and April (representing the beginning of the spring peak). The major findings were: Medfly population was higher in plots that were closer to human communicates, presumably due to their proximity to private gardens; the medfly population was negatively affected by the proportion of the surrounding crop; larger plots with lower perimeter-to-area ratio and plots inside large citrus clusters had smaller populations of medflies; variety had inconsistent effect; and elevation showed inverse response (positive in November and negative in April). Additionally, during the fall peak, the medfly population was positively affected by the proportion of the surrounding deciduous orchards and negatively affected by pest aerial spraying rounds up to a certain number. The results of this study demonstrate that the medfly populations in citrus are affected by the composition of the external landscape. Thus, similar to other studies, this study encourages the adoption of area-wide integrated pest management protocols. [ABSTRACT FROM AUTHOR]

Egyptian broomrape (Phelipanche aegyptiaca) is one of the main threats to tomato production in Israel. The seed bank of P. aegyptiaca rapidly develops and spreads in the field. Knowledge about the spatio-temporal distribution of such weeds is required in advance of emergence, as they emerge late in their life cycle when they have already caused major crop damage. The aim of this study is to reveal the effects of two major internal infestation sources: crop rotation and infestation history; and one external source: proximity to infested tomato fields; on infestation of P. aegyptiaca in processing tomatoes. Ecoinformatics, spatial analysis and geostatistics were used to examine these effects. A regional survey was conducted to collect data on field history from 238 tomato fields between 2000 and 2012, in a major tomato-growing region in Israel. Multivariate logistic regression in the framework of generalized linear models (GLM) has demonstrated the importance of all three variables in predicting infestation in tomato fields. The parameters of the overall model indicated a high specificity between tomatoes and P. aegyptiaca, which is potentially responsible for aggravating infestation. In addition, P. aegyptiaca infestation levels were intensively mapped in 43 of the 238 tomato fields in the years 2010-2012. Geostatistical measures showed that 40% of the fields had clustered infestation spatial patterns with infestation clusters located along the fields' borders. Strong linear and negative relationships were found between infestation level and distance from a neighboring infested field, strengthening the role of infested tomato fields in P. aegyptiaca spread. An experiment specifically designed for this study showed that during harvest, P. aegyptiaca seeds are blown from an infested field to a distance of at least 90 m, and may initiate infestation in neighboring fields. Integrating current knowledge about the role of agricultural practices on the spread of P. aegyptiaca with the results of this study enabled us to propose a mechanism for the spread of P. aegyptiaca. Given the major effect of agricultural practices on infestation levels, it is assumed that the spread of this weed can be suppressed by implementing sanitation and using decision support tools for herbicide application. [ABSTRACT FROM AUTHOR]

Salt stress is a major limiting factor in avocado (Persea americana) cultivation, exacerbated by global trends towards scarcity of high-quality water for irrigation. Israeli avocado orchards have been irrigated with relatively high-salinity recycled municipal wastewater for over three decades, over which time rootstocks were selected for salt-tolerance. This study's objective was to evaluate the physiological salt response of avocado as a function of the rootstock. We irrigated fruit-bearing 'Hass' trees grafted on 20 different local and introduced rootstocks with water high in salts (electrical conductivity of 1.4–1.5 dS/m). The selected rootstocks represent a wide range of genetic backgrounds, propagation methods, and horticultural characteristics. We investigated tree physiology and development during two years of salt exposure by measuring Cl and Na leaf concentrations, leaf osmolality, visible damages, trunk circumference, LAI, CO2 assimilation, stomatal conductance, spectral reflectance, stem water potential, trichomes density, and yield. We found a significant effect of the rootstocks on stress indicators, vegetative and reproductive development, leaf morphogenesis and photosynthesis rates. The most salt-sensitive rootstocks were VC 840, Dusa, and VC 802, while the least sensitive were VC 159, VC 140, and VC 152. We conclude that the rootstock strongly influences avocado tree response to salinity exposure in terms of physiology, anatomy, and development. [ABSTRACT FROM AUTHOR]

Wine quality is the final outcome of the interactions within a vineyard between meteorological conditions, terrain and soil properties, plant physiology and numerous viticultural decisions, all of which are commonly summarized as the terroir effect. Associations between wine quality and a single soil or topographic factor are usually weak, but little information is available on the effect of terrain (elevation, aspect and slope) as a compound micro-terroir factor. We used the topographic wetness index (TWI) as a steady-state hydrologic and integrative measure to delineate management zones (MZs) within a vineyard and to study the interactions between vine vigor, water status and grape and wine quality. The study was conducted in a commercial 2.5-ha Vitis vinifera 'Cabernet Sauvignon' vineyard in Israel. Based on the TWI, the vineyard was divided into three MZs located along an elongate wadi that crosses the vineyard and bears water only in the rainy winter season. MZ1 was the most distant from the wadi and had low TWI values, MZ3 was closest to the wadi and had high TWI values. Remotely sensed crop water stress index (CWSI) was measured simultaneously with canopy cover (as determined by normalized difference vegetation index; NDVI) and with field measurements of midday stem water potential (Ψstem) and leaf area index (LAI) on several days during the growing seasons of 2017 and 2018. Vines in MZ1 had narrow trunk diameter and low LAI and canopy cover on most measurement days compared to the other two MZs. MZ1 vines also exhibited the highest water stress (highest CWSI and lowest Ψstem), lowest yield and highest wine quality. MZ3 vines showed higher LAI on most measurement days, lowest water deficit stress (Ψstem) during phenological stage I, highest yield and lowest wine quality. Yet, in stage III, MZ3 vines exhibited a similar water deficit stress (CWSI and Ψstem) as MZ2, suggesting that the relatively high vigor in MZ3 vines resulted in higher water deficit stress than expected towards the end of the season, possibly because of high water consumption over the course of the season. TWI and its classification into three MZs served as a reliable predictor for most of the attributes in the vineyard and for their dynamics within the season, and, thus, can be used as a key factor in delineation of MZs for irrigation. Yet, in-season remotely sensed monitoring is required to follow the vine dynamics to improve precision irrigation decisions. [ABSTRACT FROM AUTHOR]