Remote Sensing for Precision Agriculture: Sentinel-2 Improved Features and Applications

The use of satellites to monitor crops and support their management is gathering increasing attention. The improved temporal, spatial, and spectral resolution of the European Space Agency (ESA) launched Sentinel-2 A + B twin platform is paving the way to their popularization in precision agriculture. Besides the Sentinel-2 A + B constellation technical features the open-access nature of the information they generate, and the available support software are a significant improvement for agricultural monitoring. This paper was motivated by the challenges faced by researchers and agrarian institutions entering this field; it aims to frame remote sensing principles and Sentinel-2 applications in agriculture. Thus, we reviewed the features and uses of Sentinel-2 in precision agriculture, including abiotic and biotic stress detection, and agricultural management. We also compared the panoply of satellites currently in use for land remote sensing that are relevant for agriculture to the Sentinel-2 A + B constellation features. Contrasted with previous satellite image systems, the Sentinel-2 A + B twin platform has dramatically increased the capabilities for agricultural monitoring and crop management worldwide. Regarding crop stress monitoring, Sentinel-2 capacities for abiotic and biotic stresses detection represent a great step forward in many ways though not without its limitations; therefore, combinations of field data and different remote sensing techniques may still be needed. We conclude that Sentinel-2 has a wide range of useful applications in agriculture, yet still with room for further improvements. Current and future ways that Sentinel-2 can be utilized are also discusse

Comparison of proximal remote sensing devices of vegetable crops to determine the role of grafting in plant resistance to meloidogyne incognita

Proximal remote sensing devices are novel tools that enable the study of plant health status through the measurement of specific characteristics, including the color or spectrum of light reflected or transmitted by the leaves or the canopy. The aim of this study is to compare the RGB and multispectral data collected during five years (2016–2020) of four fruiting vegetables (melon, tomato, eggplant, and peppers) with trial treatments of non-grafted and grafted onto resistant rootstocks cultivated in a Meloidogyne incognita (a root-knot nematode) infested soil in a greenhouse. The proximal remote sensing of plant health status data collected was divided into three levels. Firstly, leaf level pigments were measured using two different handheld sensors (SPAD and Dualex). Secondly, canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the Normalized Difference Vegetation Index (NDVI) measured with a portable spectroradiometer (Greenseeker). Third, we assessed plant level water stress, as a consequence of the root damage by nematodes, using stomatal conductance measured with a porometer and indirectly using plant temperature with an infrared thermometer, and also the stable carbon isotope composition of leaf dry matter.. It was found that the interaction between treatments and crops (ANOVA) was statistically different for only four of seventeen parameters: flavonoid (p < 0.05), NBI (p < 0.05), NDVI (p < 0.05) and the RGB CSI (Crop Senescence Index) (p < 0.05). Concerning the effect of treatments across all crops, differences existed only in two parameters, which were flavonoid (p < 0.05) and CSI (p < 0.001). Grafted plants contained fewer flavonoids (x¯ = 1.37) and showed lower CSI (x¯ = 11.65) than non-grafted plants (x¯ = 1.98 and x¯ = 17.28, respectively, p < 0.05 and p < 0.05) when combining all five years and four crops. We conclude that the grafted plants were less stressed and more protected against nematode attack. Leaf flavonoids content and the CSI index were robust indicators of root-knot nematode impacts across multiple crop typesY.H. acknowledges the support of the Tunisian government from the Ministery of Higher Education and Scientific Research. J.L.A. acknowledges support from the Institucio Catalana d'Investigacio i Estudis Avancats (ICREA) Academia, Generalitat de Catalunya, Spain. S.C.K. is supported by the Ramon y Cajal RYC-2019-027818-I research fellowship from the Ministerio de Ciencia e Innovacion, Spain. Thanks are also given to the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (FEDER) for funding the project AGL2013-49040-C2-1-R and to the Ministry of Science and Innovation from the Spanish Government for funding the AGL2017-89785-R, and to the European Regional Development Fund (FEDER) AGL2017-89785-R, and for providing the FPI grant PRE2018-084265 to AMF. This research was also supported by the COST Action CA17134 SENSECO (Optical synergies for spatiotemporal sensing of scalable ecophysiological traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu accessed on 29 April 2022)

Multi-scale and multi-sensor remote sensing in international agricultural development

[eng] Personal food security means that they have physical and economic access to sufficient, safe, and quality food. On the other hand, there are three main causes of food insecurity: 1. the high vulnerability of agriculture to climate change; 2. local, national, or international conflicts; and 3. economic inequality. The United Nations (UN) Sustainable Development Goals (SDGs), which are objectives that should be attained by 2030, are targeted at both developing and developed nations. The second SDG, "Zero Hunger," aims to double small-scale food producers' productivity and earnings while promoting resilient agricultural methods and ensuring sustainable food production. Agriculture is heavily reliant on factors related to climate change conditions such as abiotic stress, which includes soil nutrient deficiencies, accelerating temperature rises, drought, and rising CO2 concentrations; and biotic stress, which includes invasive pests, disease outbreaks, and decreased crop output. Remote sensing (RS) technologies can provide several non-destructive methods for identifying and quantifying various types of stress. For the application of RS, it is relevant to consider the different types of resolution: spectral, spatial, temporal, and radiometric. Also, the different observation scales are ground- based, aerial, space-based, or using orbital satellites. In this thesis, we evaluated the practical implementation of non-destructive methods using RS technologies across the four chapters. Moreover, we compared the maturity levels between different types of technologies using Technological Readiness Level (TRL) assessments. In the first chapter, our objective was to estimate the grain yield of the maize under low nitrogen using Vegetation Indices (VIs) from RGB (Red, Green, Blue composite color images) sensors at the ground and aerial levels in Sub-Saharan Africa (SSA). We developed an RS system in the second chapter to monitor an early warning fall armyworm (FAW) across SSA. In the third one, using leaf spectral reflectance and advanced regression models, we estimated the Vc,max, and Jmax of soybean and peanut. And in the last chapter, we developed a user-friendly mobile app for the Middle East and North Africa (MENA) countries for plant disorders detection on tomatoes, cucumbers, peppers, and quinoa, covering everything from data collection to deep learning model creation, to web and mobile app launch. Different RS technologies were used in different countries at different scales and with different types of sensors. Nevertheless, it was very relevant to consider the objectives of each study because they determined the type of spectral, spatial, and temporal resolution and the scale of observation. Regarding the TRLs across the four chapters, they suggest that the level of technology readiness depends on the goals, the time to develop the project, the amount of data collection required, and the robustness of the validation.[spa] La seguridad alimentaria personal significa que tienen acceso físico y económico a alimentos suficientes, seguros y de calidad. Por otro lado, existen tres causas principales de la inseguridad alimentaria: 1. la alta vulnerabilidad de la agricultura al cambio climático; 2. conflictos locales, nacionales o internacionales; y 3. desigualdad económica. Los Objetivos de Desarrollo Sostenible (ODS) de las Naciones Unidas (ONU), que son objetivos que deben alcanzarse para 2030, están dirigidos tanto a las naciones en desarrollo como a las desarrolladas. El segundo ODS, "Hambre cero", tiene como objetivo duplicar la productividad y los ingresos de los productores de alimentos a pequeña escala, al tiempo que promueve métodos agrícolas resilientes y garantiza la producción sostenible de alimentos. La agricultura depende en gran medida de factores relacionados con las condiciones del cambio climático, como el estrés abiótico, que incluye deficiencias de nutrientes del suelo, aumentos acelerados de temperatura, sequía y aumento de las concentraciones de CO2; y estrés biótico, que incluye plagas invasoras, brotes de enfermedades y disminución de la producción de cultivos. Las tecnologías de teledetección remota (RS) pueden proporcionar varios métodos no destructivos para identificar y cuantificar varios tipos de estrés. Para la aplicación de RS, es relevante considerar los diferentes tipos de resolución: espectral, espacial, temporal y radiométrica. Además, las diferentes escalas de observación son terrestres, aéreas, espaciales o utilizando satélites orbitales. En esta tesis, evaluamos la implementación práctica de métodos no destructivos utilizando tecnologías RS en los cuatro capítulos. Además, comparamos los niveles de madurez entre diferentes tipos de tecnologías utilizando evaluaciones de nivel de preparación tecnológica (TRL). En el primer capítulo, nuestro objetivo era estimar el rendimiento de grano del maíz bajo un nivel bajo de nitrógeno usando índices de vegetación (VI) de sensores RGB (imágenes compuestas de color rojo, verde y azul) a nivel del suelo y del aire en el África subsahariana (SSA). Desarrollamos un sistema RS en el segundo capítulo para monitorear un gusano cogollero de advertencia temprana (FAW) en SSA. En el tercero, usando reflectancia espectral de hoja y modelos de regresión avanzada, estimamos la Vc,max y Jmax de soja y maní. Y en el último capítulo, desarrollamos una aplicación móvil fácil de usar para los países de Medio Oriente y África del Norte (MENA) para la detección de trastornos de las plantas en tomates, pepinos, pimientos y quinua, que cubre todo, desde la recopilación de datos hasta la creación de modelos de aprendizaje profundo, al lanzamiento de aplicaciones web y móviles. Se utilizaron diferentes tecnologías RS en diferentes países a diferentes escalas y con diferentes tipos de sensores. Sin embargo, fue muy relevante considerar los objetivos de cada estudio porque determinaron el tipo de resolución espectral, espacial, temporal y la escala de observación. Con respecto a los TRL en los cuatro capítulos, sugieren que el nivel de preparación tecnológica depende de los objetivos, el tiempo para desarrollar el proyecto, la cantidad de recopilación de datos requerida y la solidez de la validación

Heterosis and reciprocal effects for physiological and morphological traits of popcorn plants under different water conditions

In spite of the benefits of heterosis in maize breeding, little is known about the physiological mechanisms of this phenomenon and its genetic control under different water regimes. This study aimed to understand the heterosis effects on plant growth, the photosynthetic and transpiration traits, and the root traits of four inbred popcorn lines and their hybrids, including their reciprocal combinations. Plants were grown in lysimeters, inside a rain shelter, under two water conditions (water stress - WS; well-watered - WW) until anthesis. Plant growth traits included shoot biomass, plant height, and leaf area. Photosynthetic traits comprised leaf pigment and total nitrogen content, chlorophyll fluorescence, gas exchange, water use efficiency and stomatal index and density, along with the stable carbon (δ13C) and nitrogen (δ15N) isotope compositions of the last developed leaf. Root weight density and specific root length were also recorded. Greater heterosis effects were observed for traits related to plant growth and root weight density, and specifically under WS. Traits related to root weight density in deeper soil layers benefited markedly from heterosis, but there were no advantages in terms of stomatal conductance and water status in general. Apparently, only δ13C supported a better water status under WS, and was observed in the hybrids in particular. Non-additive gene effects were predominant in controlling of most of the growth and root traits studied, supporting the conclusion that the heterosis effect is especially favorable under water-limiting conditions. Moreover, the choice of the female parent is essential for traits related to gas exchange when breeding for better resilience to drought