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

Impact of climate and anthropogenic effects on the energy, water, and carbon budgets of monitored agrosystems: multi-site analysis combining modelling and experimentation

Les terres cultivées représentent une unité importante dans le climat mondial, et en réponse à la population, elles sont en expansion. Il est crucial de comprendre et de quantifier les interactions terre-atmosphère via les échanges d'eau, d'énergie et de carbone. Dans ce contexte, cette thèse a consisté à étudier la variabilité du bilan énergétique en fonction de différentes cultures, phénologies et pratiques agricoles via système Eddy-Covariance. En réponse au manque d'eau dans le sud-ouest de la France, deux modèles de surface (ISBA et ISBA-MEB) ont été évalués sur deux cultures (blé et maïs) pour évaluer leur capacité à estimer les flux d'énergie et d'eau. Enfin, en réponse à la contribution des terres cultivées à l'augmentation du dioxyde de carbone atmosphérique, la capacité du modèle ISBA-MEB à simuler correctement les principaux composants du carbone a été testée sur 11 saisons de maïs et de blé.Croplands represent an important unit within the global climate, and in response to population, they are expanding. Hence, understanding and quantifying the land-atmosphere interactions via water, energy and carbon exchanges is crucial. In this context, the first objective of this thesis studied the variability of the energy balance over different crops, phenologies, and farm practices at Lamasquère and Auradé. Secondly, in response to water scarcity and increasing drought in southwestern France, two land surface models (ISBA and ISBA-MEB) of different configurations were evaluated over some wheat and maize years to test their ability to estimate energy and water fluxes using measurements from an eddy covariance system as reference. Finally, in response to the contribution of croplands to increasing atmospheric carbon dioxide, the capability of the ISBA-MEB model to correctly simulate the major carbon components was tested over 11 seasons of maize and wheat

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under short-term, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under short-term, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions

Benefits and trade-offs of legume-led crop rotations on crop performance and soil erosion at various scales in SW Kenya

Soil erosion and land fragmentation threaten agricultural production in large parts of the Western Kenyan Highlands. In Rongo watershed, maizecommon bean intercropping systems, which dominate the agricultural landscape, are vulnerable to soil degradation, especially on long slope lengths where ground and canopy cover provision fail to protect the soil from the disruptive impact of raindrops. The inclusion of soil conservation measures like hedgerows, cover crops or mulch can reduce soil erosion, but compete with crops for space and labour. Knowledge of critical slope length can minimise interventions and tradeoffs. Hence, we evaluated maizecommon bean intercrop (MzBn) regarding runoff, erosion and crop yield in a slope length trial on 20, 60 and 84 m plot lengths, replicated twice on three farms during one rainy season in Rongo, Migori County. Additionally, we investigated systems of MzBn (farmers practice), MzBn with 5 Mg ha-1 Calliandra calothyrsus mulch (Mul), Arachis hypogaea (Gnt), Lablab purpureus (Lab) and Mucuna pruriens (Muc), regarding their impact on infiltration, runoff, soil loss, soil C and N loss during three rainy seasons (long and short rains, LR and SR, 2016, and LR 2017). Measured field data on soil, crop, spatial maps and meteorology were used as input datasets to parameterize and calibrate the LUCIA model. The calibrated and validated model was then used to simulate agronomic management scenarios related to planting date (planting with first rain vs baseline) and vegetation cultivar (short duration crop) to mitigate water stress. Based on the measurements, groundcover was most influential over rainfall intensity (EI30) and plant canopy cover in predicting soil loss. Dense groundcover of Mul at the beginning of the rainy seasons was decisive to significantly (p 5mm) in the topsoil under Mul at the end of SR 2016 significantly (p<0.05) increased infiltration rates (420 mm hr-1) in LR 2017 compared to Lab (200 mm hr-1) and Gnt (240 mm hr-1). Average C and N concentrations in eroded sediments were significantly reduced under Mul (0.74 kg C ha1, 0.07 kg N ha1) during the LR 2016 as compared to MzBn (3.20 kg C ha1, 0.28 kg N ha1) and Gnt (2.54 kg C ha1, 0.23 kg N ha1). Likewise, in SR 2016 Mul showed significantly lowered C and N losses of 3.26 kg C ha1 and 0.27 kg N ha1, respectively, over Lab (9.82 kg C ha1, 0.89 kg N ha1). Soil loss over 84 m slope length was overall significantly higher by magnitudes of 250 and 710% than on 60 and 20 m long plots, respectively, which did not differ significantly among each other (p<0.05). For runoff, 84 m plot length differed significantly from 60 and 20 m, but in the opposite trend as for soil loss. Across all three farms, slope gradient and slope length were the variables with highest explanatory power to predict soil loss. At the individual farm level, under homogeneous slope and texture, slope length and profile curvature were most influential. Considering results of slope length experiments, plot lengths less than 50 m appear to be preferential considering soil loss, sediment load, and soil loss to yield ratio under the given rainfall, soil and slope conditions. Our results call for integrating slope length options and cropping systems for effective soil conservation. We recommend planting Mucuna and Calliandrahedgerows as buffer strips below the critical slope length, and legume cash crops and maize uphill. Such approaches are critical in the backdrop of land fragmentation and labour limitation in the region to sustainably maximise land area. In the modelling exercise, crops planted one and three weeks after the baseline planting date increased Maize and Muc grain yield over the baseline during the three cropping seasons, the three weeks treatment in particular. This could be due to more favourable weather conditions during the shifted vegetation period. Increased grain yield corresponded to high water use efficiency (WUE). The short duration crop planted three weeks after the baseline planting date (PD3WL+SDC10) showed the highest grain yield after PD3WL (three weeks late plaing with BL variety). The use of cultivars with short growth cycle offers the flexibility of planting again where crops failed due to crop water stress or where the rains delay, ensuring completion of the growth cycle before the season ends. Given that short growth duration crops produce less grain yield compared to their counterpart full season crops, due to the length of their cycles, breeding programs must prioritize traits that can enhance the size of the grain-filling sink. At the plot level, management systems that reduce evaporation and retain soil moisture, e.g. mulching, application of farmyard manure etc., must be promoted to reduce evapotranspiration.Bodenerosion und Kleinteiligkeit von Betriebsflächen bedrohen die landwirtschaftliche Produktion in weiten Teilen des westkenianischen Hochlands. Im untersuchten Wassereinzugsgebiet von Rongo sind die weit verbreiteten Mais-Bohne-Mischkkultursysteme gefährdet durch Bodendegradierung. Dies ist vor allem auf langen Hängen und dort der Fall, wo der Oberboden nicht durch entsprechende Bodenbedeckung vor Schlagregen geschützt ist. Bodenschutzmaßnahmen wie Hecken, Bodendecker oder Mulch können das Ausmaß von Bodenerosion verringern, konkurrieren aber oft mit der Hauptkultur um Raum bzw. Arbeitskraft. Der gezielte Einsatz solcher Interventionen ausschliesslich in Bereichen kritischer Hangpositionen kann solcherlei Aufwand und Konkurrenzeffekte minimieren. In diesem Zusammenhang wurden in der hier vorgestellten Studie Mais-Bohne-Mischkulturen (MzBn) während einer Anbausaison auf drei unterschiedlichen Hanglängen (20, 60 und 84 m) mit jeweils zwei Wiederholungen auf drei Betrieben in Rongo, Migori County, hinsichtlich Oberflächenabfluss, Erosion und Ertrag verglichen. Zudem wurden MzBn, MzBn mit 5 Mg ha-1 Calliandra calothyrsus Mulch (Mul), Arachis hypogaea (Gnt), Lablab purpureus (Lab) und Mucuna pruriens (Muc) hinsichtlich Infiltration, Oberflächenabfluss, Erosion, organischem Boden-C und Gesamt-Boden-N während dreier Anbauperioden (lange und kurze Regenzeit 2016 und lange Regenzeit 2017) verglichen. Gemessene Boden- und Pflanzenparameter sowie Boden-, Landnutzungskarten und ein digitales Höhenmodell wurden nebst tagesgenauen Wetterdaten als Eingaben für das Lucia (Land Use Change Impact Assessment)-Modell verwendet. Mit dem kalibrierten und validierten Modell wurden dann Szenarien zum Wasserstressmanagement mit Fokus auf Aussaatzeitpunkten und Sortenwahl (verschiedene Vegetationsdauer) getetstet. Die Auswertung der Feldversuche zeigte, dass der Grad der Bodenbedeckung (durch Biomasse, Mulch und Streu) stärkeren Einfluss auf Bodenabtrag hatte als Regenintensität (EI30) und Bodenbedeckung des Blätterdachs allein. Die dichte Bodenbedeckung durch Calliandramulch in Mul zu Beginn der Saison war dabei entscheidend für signifikant geringeren Oberflächenabfluss (88, 87 und 84% niedriger als in MzBn, Lab und Gnt) und Bodenabtrag (66 und 65% niedriger als in Gnt und Lab). Der hohe Anteil großer Bodenaggregate > 5mm im Oberboden zum Ende der kurzen Regenzeit (SR) 2016 stand in Zusammenhang mit im Vergleich zu Lab (200 mm hr-1) and Gnt (240 mm hr-1) signifikant erhöhten Infiltrationsraten unter Mul (420mm h-1) in der langen Regenzeit (LR) 2017. Durchschnittliche C- und N-Konzentrationen in Sedimenten waren in der LR 2016 unter Mul (0.74 kg C ha1, 0.07 kg N ha1) signifikant niedriger als unter MzBn (3.20 kg C ha1, 0.28 kg N ha1) und Gnt (2.54 kg C ha1, 0.23 kg N ha1). Ebenso waren in der SR 2016 C- und N-Verluste deutlich geringer als unter Lab (3.26 kg C ha1 und 0.27 kg N ha1 im Vergleich zu 9.82 kg C ha1 und 0.89 kg N ha1). Bodenabtrag bei 84 m Hanglänge war 250 bzw. 710% höher als auf den 60 und 20 m Anlagen, wobei sich letztere statistisch (p<0.05) nicht unterschieden. Hinsichtlich Oberflächenabfluss unterschieden sich die Hanglängen ebenfalls statistisch, aber in entgegengesetzter Richtung. Im Vergleich der Flächen auf allen drei Betrieben waren Hangneigung und länge die statistisch einflussreichsten Faktoren bezüglich Bodenabtrag. Auf den einzelnen Betrieben, d.h. bei gleich Hangneigung und Bodenart, waren Hanglänge und Hangform ausschlaggebend. Als Ergebnis der Hanglängenversuche erwies sich eine Länge von 50 m unter den gegebenen Wetter-, Boden- und Geländebedingungen als kritisch bzgl. Erosion, Sedimentmengen und dem Verhältnis von Erosion zu Ertrag. Die Ergebnisse dieser Studie legen nahe, dass effektiver Bodenschutz vor allem durch die Integration von Hanglänge und Anbausystem (Pflanzenwahl) erreicht werden kann. Es wird empfohlen Calliandra-Hecken mit Mucuna-Unterpflanzung als Pufferzonen in Streifen unterhalb der kritischen Hanglänge anzulegen sowie Körnerleguminosen und Mais als cash crops oberhalb. Durch diesen Ansatz kann vor dem Hintergrund der Landfragmentierung und Knappheit an Arbeitskraft in der Untersuchungsregion die nutzbare Landfläche nachhaltig optimiert werden. Der Modellierungsteil dieser Studie zeigte, dass Erträge bei einer und besonders bei drei Wochen späterem Aussaatzeitpunkt im Vergleich zum lokal üblichen Termin während aller drei Anbauperioden zu höheren Kornerträgen führte. Grund hierfür könnten günstigere Wetterbedingungen während der somit verschobenen Vegetationsperiode sein. Die höheren Erträge gingen einher mit effizienterer Wassernutzung der Pflanzen. Eine Sorte mit verkürzter Vegetationsperiode, drei Wochen nach dem üblichen Termin gepflanzt (PD3WL+SDC10), erzielte die höchsten Erträge. Sorten kürzerer Vegetationsdauer bieten allgemein höhere Flexibilität in Fällen spät einsetzender Regenfälle oder von Pflanzenmortalität, da auch bei wiederholter Aussaat die Regenzeit noch hinreichend genutzt werden kann. Angesichts der niedrigereren Ertragbildung während verkürzter Vegetationsdauer sollte ein höherer Kornanteil prioritäres Zuchtziel für zukünftige Sorten sein. Auf der Seite der Landwirte bedeutet dies, dass vermehrt Anbausysteme, die Evaporation verringern und Bodenfeuchte konservieren (z.B. Mulchen, Mistgaben), zur Anwendung kommen sollten

Simulation and management of on-demand irrigation systems: a combined agrohydrological and remote sensing approach

Rational use of water resources in agriculture requires improvements in the efficiency of irrigation. Many irrigation systems, particularly in Mediterranean regions, have been enhanced by replacing open channel conveyance systems with pressurised pipelines. This allows to provide water on-demand. Increased demand of water for civil and industrial uses and a progressive reduction of available water resources compel a more efficient use of irrigation water. To achieve this goal irrigation managers need to understand and to monitor the processes which determine the operation of an irrigation system.In this thesis a procedure integrating the agrohydrological aspects of irrigation with hydraulic and management aspects has been developed. The procedure named SIMODIS (SImulation and Management of On-Demand Irrigation Systems) is based on the integration of different tools such as agrohydrological and hydraulic simulation models, remote sensing and GIS techniques.An irrigation system is described as a set of elementary (e.g. individual fields) connected by the pressurised conveyance system. The spatial distribution of soil water deficit in each elementary unit is computed daily by combining the soil water model SWAP with occasional satellite-based estimates of crop water requirements. A methodology has been developed to obtain spatially distributed input data for the soil water model SWAP i.e. the soil hydraulic properties and the upper and lower boundary conditions.Multispectral satellite images are used to map the crop coefficients needed for the definition of the SWAP upper boundary condition in each elementary unit of the irrigation district. Two different approaches have been proposed. The first is based on classification techniques, where clustering algorithms are applied to derive the spectral classes corresponding to different crop coefficient values. In the second approach, the crop coefficient is analytically related to the canopy variables determining the potential evapotranspiration i.e. leaf area index, surface albedo and crop height. At-surface directional spectral reflectance are used to estimate these canopy variables from which the value of crop coefficient is calculated.The spatial distribution of farmers' water demand is derived on a daily basis from the soil water deficit according to predefined irrigation scheduling criteria. Before applying this farmers' water demand distribution for the given day, the SIMODIS procedure assess whether water demand is consistent with the available amount of water resources and with the structural and operational constraints imposed by the conveyance and distribution system. For this purpose a steady-state simulation model of pipeline hydraulics is used in SIMODIS. The final distribution of farmers' water demand is then resulting from a three-tiered adaptation of irrigation schedule considering: i) the limitation of flow rate at delivery outlets, ii) the limitation of available water resources, iii) the required minimum hydraulic head at the delivery outlets.The procedure SIMODIS has been applied in the Gromola irrigation district of approximately 3000 ha in southern Italy. Measurements of irrigation volumes were used to identify the parameters driving irrigation scheduling. Irrigation efficiency indicators were calculated from the spatial distribution of actual transpiration rates and of the corresponding irrigation volumes applied. To illustrate the use of SIMODIS in support of irrigation decision making, alternative scenarios of water management were simulated and compared.The development of SIMODIS demonstrated that agrohydrological simulation models and remote sensing can be effectively combined to describe the operation of an irrigation system. These techniques have reached a sufficient degree of reliability to be transferred to practical applications. The estimation of crop coefficients by means of remote sensing techniques is of general usefulness in the definition of the upper boundary condition of distributed hydrological simulation models and it can be applied to evaluate with satisfactory accuracy the crop water requirements at regional scale. In the future new types of satellite sensors will probably allow for a more precise determination of the canopy variables, thus providing novel opportunities in the integration between agrohydrological simulation models and remote sensing techniques.</p

Sustainable Cropping Systems

Global crop production must substantially increase to meet the needs of a rapidly growing population. This is constrained by the availability of nutrients, water, and land. There is also an urgent need to reduce the negative environmental impacts of crop production. Collectively, these issues represent one of the greatest challenges of the twenty-first century. Sustainable cropping systems based on ecological principles are the core of integrated approaches to solve this critical challenge. This special issue provides an international basis for revealing the underlying mechanisms of sustainable cropping systems to drive agronomic innovations. It includes review and original research articles that report novel scientific findings on improvement in cropping systems related to crop yields and their resistance to biotic and abiotic stressors, resource use efficiency, environmental impact, sustainability, and ecosystem services

The effects of atmospheric CO2 on silicon accumulation, plant defensive traits and herbivore attack

The general aim of this thesis is to examine effects of atmospheric change, particularly different CO2 concentrations, on Si uptake and accumulation in the Poaceae family (e.g. grasses, wheat) and the consequences for a polyphagous insect herbivore, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae). A model grass Brachypodium distachyon was the main study species used in this work due to its phylogenetic and anatomical similarities with important cereal crops such as wheat, maize and barley as well as its short generation time, simple growth requirements and comparable levels of shoot Si to most grass crops. This makes this species useful for studying the transport, accumulation and functional properties of Si in crop plants. Tall fescue (Festuca arundinacea Schreb. and wheat (Triticum aestivum L.) were also used in some chapters (chapters 4 and 6). Helicoverpa armigera was used as a model of an aboveground insect herbivore since it is a global pest of many economically important agricultural crops, particularly in Africa, America, Asia, Australia, and Europe which causes crop losses estimated at US$7 billion every year. This insect can damage at least 172 plant species due to its polyphagy and wide host range, and long persistence in cropping areas. Additionally, this insect has developed broad-spectrum pesticide resistance which makes it difficult to control using conventional techniques and thus developing alternative control strategies is necessary. Taken together, this PhD research highlights the contrasting effect of Miocene and Anthropocene CO2 levels on Si uptake, and accumulation as well as Si-based plant defence responses against the generalist aboveground insect herbivores and interactions between herbivores. This provides novel insights into the evolutionary basis for grasses utilising Si as an anti-herbivore defence and how Si defences may change under future conditions. Overall, this work provides evidence that Si accumulation plays an important role in plant biology and ecology in terms of providing plant resistance by altering plant physical, biochemical and secondary metabolite defence responses. Further, the contrasting effect of Miocene and Anthropocene CO2 levels on Si accumulation suggests that some grasses may become more susceptible to insect herbivores due to declines in Si-based defences against insect herbivory under projected climate change scenarios. Avenues for future research and the limitations of the current work are discussed

A study into the effects of pyrolysis fuels, pyrolysis conditions and the identification of chemical markers in grapes and wine as smoke taint

Taxonomically distinct vegetation fuels were used to generate smoke for fumigating grapevines to examine the influence of lignin makeup on smoke taint compounds that accrue in wine. Vegetation type had no effect on taint accumulation. Phenol, m-cresol and p-cresol glycoconjugates were closely associated with harsh smoke taint descriptors. While cultivars had similar smoke uptake sensitivity, winemaking method had distinct impact: red winemaking releases 80% of grape phenols compared to 20-35% for white winemaking

Earth Resources: A continuing bibliography with indexes

This bibliography lists 475 reports, articles and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1984. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis