Creating prescription maps from satellite imagery for site-specific management of cotton root rot

Cotton root rot is a century-old cotton disease that can now be controlled with Topguard Terra Fungicide. However, as this disease tends to occur in the same general areas within fields year after year, site-specific treatment can be more effective and economical. The objective of this study was to evaluate GeoEye-1 and Sentinel-2 satellite multispectral imagery for creating prescription maps for site-specific management of this disease. A GeoEye-1 2-m image acquired in 2009 and a Sentinel-2A 10-m image acquired in 2016 were used to map cotton root rot in two cotton fields, respectively. The multispectral images were classified into root rot-infested and non-infested areas using unsupervised classification. To accommodate the potential expansion and temporal variation of the disease, a 10-m buffer around the infested areas was added as part of the treatment areas in the prescription maps. The prescription map from the GeoEye-1 image for Field 1 was used for site-specific fungicide application in 2016 and the disease was effectively controlled. Airborne 1-m multispectral imagery acquired in 2016 was used to validate the classification accuracy of the Sentinel-2A image for mapping the disease in Field 2. Although the Sentinel-2A image missed some small infested areas as compared with the airborne imagery, prescription maps with the 10-m buffer from the Sentinel-2A and airborne images were very similar. The results from this study indicate that historical satellite images with 10-m spatial resolution or finer can be used to create prescription maps for site-specific management of cotton root rot

Detection of Verticillium wilt in olive using high-resolution hyperspectral and thermal remote sensing imagery

El olivo (Olea europaea L.) es el cultivo leñoso no tropical que ocupa mayor superficie en todo el mundo, con el 95% de la producción mundial localizada en la cuenca Mediterránea. España es el país con mayor superficie de olivar del mundo con 2.5 MHa y aproximadamente el 39% de la producción mundial. Durante las últimas décadas, la Verticilosis, causada por el hongo de suelo Verticillium dahliae Kleb., ha ocasionado severas pérdidas de rendimiento en el olivar, convirtiéndose en la enfermedad más limitante causada por patógenos de suelo de este cultivo a nivel mundial. Este patógeno coloniza el sistema vascular de la planta, bloqueando el flujo del agua y finalmente induciendo estrés hídrico. El desarrollo de la Verticilosis en el olivo puede estar influenciado por factores bióticos y abióticos, sin embargo, poco se sabe sobre la influencia del medio físico en él. Actualmente, ninguna medida de control aplicada individualmente es completamente efectiva para el tratamiento de la Verticilosis del olivo, no obstante, una estrategia de control integrado es la mejor forma de manejar la enfermedad, combinando el uso de medidas de control previas y posteriores a la plantación. Las medidas de control posteriores a la plantación serían más efectivas si las zonas del terreno con árboles afectados por Verticilosis fueran identificadas en etapas tempranas del desarrollo de la enfermedad con el objetivo de disminuir la expansión del patógeno y sucesivas infecciones a árboles o plantaciones vecinas. Sin embargo, la inspección visual en campo de síntomas de la enfermedad en estadios tempranos de su desarrollo es costosa en tiempo y recursos. Por lo tanto, la teledetección puede ser una herramienta muy útil para detectar el estrés hídrico inducido por la infección de V. dahliae en olivos en etapas tempranas del desarrollo de la enfermedad. Los principales objetivos de la presente Tesis Doctoral fueron: (i) evaluar el efecto de la temperatura del suelo en el desarrollo de la Verticilosis teniendo en cuanta diferentes patotipos de V. dahliae y cultivares de olivo; (ii) valorar el uso de la teledetección térmica e hiperespectral de alta resolución como herramienta para detectar la infección y severidad por Verticilosis en parcelas de olivar y áreas de mayor extensión, evaluando la temperatura e índices fisiológicos desde escala foliar a escala de cubierta. El primer objetivo se llevó a cabo con plantas de olivo de los cultivares (cv.) Arbequina y Picual que crecieron en suelo infestado con los patotipos defoliante (D) y no defoliante (ND) de V. dahliae bajo condiciones climáticas controladas en tanques de suelo con temperaturas de 16 a 32ºC. El desarrollo de la Verticilosis en plantas infectadas por el patotipo D fue más rápido y severo en cv. Picual que en cv. Arbequina. La temperatura de suelo óptima para el desarrollo de la infección del patotipo D fue de 16 a 24ºC para cv. Picual y de 20 a 24ºC para cv. Arbequina. Para el patotipo ND el rango de temperatura más favorable para la infección por V. dahliae fue de 16 a 20ºC. Estos resultados permiten...Olive (Olea europaea L.) is the most cultivated non-tropical fruit tree in the world, with 95% of the world production located in the Mediterranean Basin. Spain is the leading olive-producing country with 2.5 MHa and nearly 39% of the world production. During the last few decades, Verticillium wilt, caused by the soil-borne fungus Verticillium dahliae Kleb., has caused severe olive yield losses, becoming the most limiting soil-borne disease of this crop worldwide. This pathogen colonizes the vascular system of plants, blocking water flow and eventually inducing water stress. Development of Verticillium wilt in olive can be influenced by biotic and abiotic factors, nevertheless, little is known about the influence of the physical environment on it. Currently, no control measure applied singly is fully effective for the management of Verticillium wilt of olive; therefore an integrated disease management strategy is needed to manage the disease, combining the use of pre-planting and post-planting control measures. Post-planting control measures would be more efficient if Verticillium wiltaffected trees patches within fields are identified at early stages of disease development in order to mitigate the spread of the pathogen and successive infections to neighboring trees. However, visual inspection of disease symptoms at early stages of development in the field is time-consuming and expensive. Thus, remote sensing is thought to be a useful tool to detect water stress induced by V. dahliae infection in olive trees at early stages of disease development. The main objectives of this PhD Thesis were: (i) to assess the effect of soil temperature on Verticillium wilt development taking into account different V. dahliae pathotypes and olive cultivars; and (ii) to evaluate the use of high-resolution thermal and hyperspectral remote sensing imagery as a tool to detect Verticillium wilt infection and severity in olive orchards and larger areas, assessing temperature and physiological indices from leaf to canopy scale. The first objective was conducted with olive plants of cultivar (cv.) Arbequina and cv. Picual grown in soil infested with the defoliating (D) or non-defoliating (ND) pathotype of V. dahliae under controlled climatic conditions in soil tanks with a range of soil temperatures from 16 to 32ºC. Verticillium wilt development in plants infected by the D pathotype was faster and more severe on cv. Picual than on cv. Arbequina. Models estimated that infection by the D pathotype was promoted by soil temperature in a range of 16 to 24°C for cv. Picual and of 20 to 24ºC for cv. Arbequina. For the ND pathotype a range of 16 to 20ºC was estimated as the most favorable for infection. These results provide a better understanding of the differential geographic distribution of V. dahliae pathotypes and assess the potential effect of climate change on Verticillium wilt... development..

Monitoring root rot in flat-leaf parsley via machine vision by unsupervised multivariate analysis of morphometric and spectral parameters

\ua9 The Author(s) 2024.Use of vertical farms is increasing rapidly as it enables year-round crop production, made possible by fully controlled growing environments situated within supply chains. However, intensive planting and high relative humidity make such systems ideal for the proliferation of fungal pathogens. Thus, despite the use of bio-fungicides and enhanced biosecurity measures, contamination of crops does happen, leading to extensive crop loss, necessitating the use of high-throughput monitoring for early detection of infected plants. In the present study, progression of foliar symptoms caused by Pythium irregulare-induced root rot was monitored for flat-leaf parsley grown in an experimental hydroponic vertical farming setup. Structural and spectral changes in plant canopy were recorded non-invasively at regular intervals using a 3D multispectral scanner. Five morphometric and nine spectral features were selected, and different combinations of these features were subjected to multivariate data analysis via principal component analysis to identify temporal trends for early segregation of healthy and infected samples. Combining morphometric and spectral features enabled a clear distinction between healthy and diseased plants at 4–7 days post inoculation (DPI), whereas use of only morphometric or spectral features allowed this at 7–9 DPI. Minimal datasets combining the six most effective features also resulted in effective grouping of healthy and diseased plants at 4–7 DPI. This suggests that selectively combining morphometric and spectral features can enable accurate early identification of infected plants, thus creating the scope for improving high-throughput crop monitoring in vertical farms

Third Annual Earth Resources Program Review. Volume 2: Agriculture, forestry, and sensor studies

Remote sensing and data reduction techniques for Earth Resources Program applied to agriculture and forestry - conferenc

IPM2.0: PRECISION AGRICULTURE FOR SMALL-SCALE CROP PRODUCTION

In order to manage pests impacting New England crop production integrated pest management (IPM) practices should be reevaluated or updated regularly to ensure that effective control of crop pests is being achieved. Three fungal taxa, Colletotrichum gloeosporioides, C. acutatum, and Glomerella cingulata, are currently associated with bitter-rot of apple (Malus domestica), with C. acutatum typically being the dominant species found in the northeastern United States. However, a recent phylogenetic study demonstrated that both C. gloeosporioides and C. acutatum are species complexes with over 10 distinct species being recovered from apple between the two studies. Based on this recent information, the objectives of this study were 1) to complete a phylogenetic analysis to determine species diversity and distribution of Colletotrichum isolates associated with bitter-rot and Glomerella leaf spot in the northeastern United States and 2) to evaluate the sensitivity of these isolates to several commercially used fungicides. A multi-gene phylogenetic analysis was completed using ITS, GADPH and BT gene sequences in order to determine which species and how many species of Colletotrichum were infecting apples in the northeastern U.S. The results of this study demonstrated that C. fioriniae is the primary pathogen causing both bitter rot and Glomerella leaf spot in the northeastern U.S. A second experiment was conducted in order to update management practices for apple scab, caused by the ascomycete Venturia inaequalis. The objective of this project was to evaluate the ability of RIMpro, an apple scab warning system, to control apple scab in New England apple orchards in addition to evaluating the performance of potassium bicarbonate + sulfur as a low-cost alternative spray material for the control of apple scab suitable for organic apple production. Use of RIMpro allowed for the reduction in the total number of spray applications made during the primary scab season by two sprays in 2013 and one spray in 2014 (28% and 25% reductions, respectively). Also, the potassium bicarbonate + sulfur treatment was shown to provide the same level of control as Captan. Finally, disease outbreaks, insect infestation, nutrient deficiencies, and weather variation constantly threaten to diminish annual yields and profits in orchard crop production systems. Automated crop inspection with an unmanned aerial vehicle (UAV) can allow growers to regularly survey crops and detect areas affected by disease or stress and lead to more efficient targeted applications of pesticides, water and fertilizer. The overall goal of this project was to develop a low cost aerial imaging platform coupling imaging sensors with UAVs to be used for monitoring crop health. Following completion of this research, we have identified a useful tool for agricultural and ecological applications

Crop Disease Detection Using Remote Sensing Image Analysis

Pest and crop disease threats are often estimated by complex changes in crops and the applied agricultural practices that result mainly from the increasing food demand and climate change at global level. In an attempt to explore high-end and sustainable solutions for both pest and crop disease management, remote sensing technologies have been employed, taking advantages of possible changes deriving from relative alterations in the metabolic activity of infected crops which in turn are highly associated to crop spectral reflectance properties. Recent developments applied to high resolution data acquired with remote sensing tools, offer an additional tool which is the opportunity of mapping the infected field areas in the form of patchy land areas or those areas that are susceptible to diseases. This makes easier the discrimination between healthy and diseased crops, providing an additional tool to crop monitoring. The current book brings together recent research work comprising of innovative applications that involve novel remote sensing approaches and their applications oriented to crop disease detection. The book provides an in-depth view of the developments in remote sensing and explores its potential to assess health status in crops

Hyperspectral, thermal and LiDAR remote sensing for red band needle blight detection in pine plantation forests

PhD ThesisClimate change indirectly affects the distribution and abundance of forest insect pests and pathogens, as well as the severity of tree diseases. Red band needle blight is a disease which has a particularly significant economic impact on pine plantation forests worldwide, affecting diameter and height growth. Monitoring its spread and intensity is complicated by the fact that the diseased trees are often only visible from aircraft in the advanced stages of the epidemic. There is therefore a need for a more robust method to map the extent and severity of the disease. This thesis examined the use of a range of remote sensing techniques and instrumentation, including thermography, hyperspectral imaging and laser scanning, for the identification of tree stress symptoms caused by the onset of red band needle blight. Three study plots, located in a plantation forest within the Loch Lomond and the Trossachs National Park that exhibited a range of red band needle blight infection levels, were established and surveyed. Airborne hyperspectral and LiDAR data were acquired for two Lodgepole pine stands, whilst for one Scots pine stand, airborne LiDAR and Unmanned Aerial Vehicle-borne (UAV-borne) thermal imagery were acquired alongside leaf spectroscopic measurements. Analysis of the acquired data demonstrated the potential for the use of thermographic, hyperspectral and LiDAR sensors for detection of red band needle blight-induced changes in pine trees. The three datasets were sensitive to different disease symptoms, i.e. thermography to alterations in transpiration, LiDAR to defoliation, and hyperspectral imagery to changes in leaf biochemical properties. The combination of the sensors could therefore enhance the ability to diagnose the infection.Natural Environment Research Council (NERC) for funding this PhD program (studentship award 1368552) and providing access to specialist equipment through a Field Spectroscopy Facility loan (710.114). I would like to thank NERC Airborne Research Facility for providing airborne data (grant: GB 14-04) that made the PhD a challenge, to say the least. My sincere gratitude goes to the Douglas Bomford Trust for providing additional funds, which allowed for completion of the UAV-borne part of this research

Use of remote sensing in agriculture

Remote sensing studies in Virginia and Chesapeake Bay areas to investigate soil and plant conditions via remote sensing technology are reported ant the results given. Remote sensing techniques and interactions are also discussed. Specific studies on the effects of soil moisture and organic matter on energy reflection of extensively occurring Sassafras soils are discussed. Greenhouse and field studies investigating the effects of chlorophyll content of Irish potatoes on infrared reflection are presented. Selected ground truth and environmental monitoring data are shown in summary form. Practical demonstrations of remote sensing technology in agriculture are depicted and future use areas are delineated

Spectral Survey of Irrigated Region Corps and Soils

The applications of remote sensing techniques to spectral surveys of irrigation, crops, and soils are reported. Topics discussed include: (1) canopy temperature as an indication of plant water stress, (2) temperature of soils and of crop canopies differing in water conditions, (3) ERTS project, (4) spectrum matching and pattern recognition, (5) photographic procedures and interpretation, (6) interaction of light with plants, and (7) plant physiological and histological factors