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New information and knowledge are important aspects of innovation in modern farming systems. There is currently an abundance of digital and data-driven solutions that can potentially transform our food systems. At a time when the general public has concerns about how food is produced and the impact of farm production systems on the environment, strategies to increase public acceptance and the sustainability of food production are required more than ever. New tools and technology can provide timely insights into aspects such as nutrient profiles, the tracking of animal or plant wellbeing, and land-use options to enhance inputs and outputs associated with the farm business. Such solutions have the ultimate aim of enhancing production efficiency and contributing to the process of learning about the advantages of the innovation, while ensuring more sustainable food supplies. At the farm level, any new information needs to be in a useful format and beneficial for management and farm decision-making. The papers in this Special Issue evaluate agri-business innovation that can enhance farm-level decision-making.

Research & information: general --- Biology, life sciences --- Technology, engineering, agriculture --- dairy cows --- computer vision --- behaviors --- monitoring --- management --- behavior --- birth --- observations --- sheep --- proximal --- sensing --- LiDAR --- photogrammetry --- grasslands --- pastures --- Adversarial-VAE --- tomato leaf disease identification --- image generation --- convolutional neural network --- potato management --- tuber formation stage --- precipitation patterns

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Plant Adaptation to Global Climate Change discusses the issues of the impact of climate change factors (abiotic and biotic) on vegetation. This book also deals with simulation modeling approaches to understanding the long-term effects of different environmental factors on vegetation. This book is a valuable resource for the environmental science research community, including those interested in assessing climate change impacts on vegetation and researchers working on simulation modeling.

Research & information: general --- climate change impacts --- sugarcane --- yield --- harvested area --- production --- Thai agriculture --- rice --- heat stress --- whole genome DNA microarray --- yield loss --- MapMan analysis --- HRDE --- anthesis and maturity date --- crop yield --- SimCLIM --- DSSAT model --- planting date --- basal area increment --- air temperature --- precipitation --- Taylor’s power law --- tree ring analysis --- climate change --- farm work --- WBGT --- mitigation --- East Africa --- leaf temperature --- infrared thermography --- thermal imagery --- tropical rain forest --- isoprenoid exchanges --- ground --- litter emissions --- soil --- Pinus pinea --- distance gradient --- Mediterranean turf --- agro-ecosystems --- biodiversity --- weed communities --- Ethiopia highlands --- seasonal climate --- crop impacts --- bananas --- Black Sigatoka Leaf Disease --- climate --- global spread &amp --- impact --- habitat suitability --- species distribution --- conservation --- P. africana --- actual evapotranspiration --- modified Penman–Monteith --- sap flow --- scaling methods --- allometric correlations --- sapwood depth --- sapwood area --- leaf area index --- species distribution model --- scenarios --- GIS --- ecological niche --- grapevine --- n/a --- Taylor's power law --- modified Penman-Monteith

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Plant Adaptation to Global Climate Change discusses the issues of the impact of climate change factors (abiotic and biotic) on vegetation. This book also deals with simulation modeling approaches to understanding the long-term effects of different environmental factors on vegetation. This book is a valuable resource for the environmental science research community, including those interested in assessing climate change impacts on vegetation and researchers working on simulation modeling.

Research & information: general --- climate change impacts --- sugarcane --- yield --- harvested area --- production --- Thai agriculture --- rice --- heat stress --- whole genome DNA microarray --- yield loss --- MapMan analysis --- HRDE --- anthesis and maturity date --- crop yield --- SimCLIM --- DSSAT model --- planting date --- basal area increment --- air temperature --- precipitation --- Taylor's power law --- tree ring analysis --- climate change --- farm work --- WBGT --- mitigation --- East Africa --- leaf temperature --- infrared thermography --- thermal imagery --- tropical rain forest --- isoprenoid exchanges --- ground --- litter emissions --- soil --- Pinus pinea --- distance gradient --- Mediterranean turf --- agro-ecosystems --- biodiversity --- weed communities --- Ethiopia highlands --- seasonal climate --- crop impacts --- bananas --- Black Sigatoka Leaf Disease --- climate --- global spread &amp --- impact --- habitat suitability --- species distribution --- conservation --- P. africana --- actual evapotranspiration --- modified Penman-Monteith --- sap flow --- scaling methods --- allometric correlations --- sapwood depth --- sapwood area --- leaf area index --- species distribution model --- scenarios --- GIS --- ecological niche --- grapevine

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Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publication of the results, among others.

Research & information: general --- Geography --- geographic information system (GIS) --- pocket beaches --- coastal management --- Interreg --- climate change --- remote sensing --- drone --- Sicily --- Malta --- Gozo --- Comino --- systematic literature review --- anomaly intrusion detection --- deep learning --- IoT --- resource constraint --- IDS --- evapotranspiration --- penman-monteith equation --- artificial neural network --- canopy conductance --- Ziz basin --- water quality --- satellite image analysis --- modeling approach --- nitrate --- dissolved oxygen --- chlorophyll a --- time series analysis --- environmental monitoring --- water extraction --- modified normalized difference water index (MNDWI) --- machine learning algorithm --- hyperspectral --- proximal sensing --- panicle initiation --- normalized difference vegetation index (NDVI) --- green ring --- internode-elongation --- Sentinel 1 and 2 --- Copernicus Sentinels --- crop classification --- food security --- agricultural monitoring --- data analysis --- SAR --- random forest --- 3D bale wrapping method --- equal bale dimensions --- mathematical model --- minimal film consumption --- optimal bale dimensions --- round bales --- Sentinel-2 --- SVM --- RF --- Boufakrane River watershed --- irrigation requirements --- water resources --- sustainable land use --- agriculture --- invasive plants --- precision agriculture --- rice farming --- site-specific weed management --- nitrogen prediction --- 1D convolution neural networks --- cucumber --- crop yield improvement --- mango leaf --- CCA --- vein pattern --- leaf disease --- cubic SVM --- chlorophyll-a concentration --- transfer learning --- overfitting --- data augmentation --- guava disease --- plant disease detection --- crops diseases --- entropy --- features fusion --- machine learning --- object-based classification --- density estimation --- histogram --- land use --- crop fields --- soil tillage --- data fusion --- multispectral --- sensor --- probe --- temperature profile --- forest roads --- simulation --- autonomous robots --- smart agriculture --- environmental protection --- photogrammetry --- path planning --- internet of things --- modeling --- convolutional neural networks --- machine vision --- computer vision --- modular robot --- selective spraying --- vision-based crop and weed detection --- Faster R-CNN --- YOLOv5 --- band selection --- CNN --- NDVI --- hyperspectral imaging --- crops --- urban flood --- Sentinel-1a --- Synthetic Aperture Radar (SAR) --- 3D Convolutional Neural Network --- multi-temporal data --- land use classification --- GIS --- Coatzacoalcos --- algorithms --- clustering --- pest control --- site-specific --- virtual pests --- rice plant --- weed --- hyperspectral imagery --- sustainable agriculture --- green technologies --- Internet of Things --- natural resources --- sustainable environment --- IoT ecosystem --- hyperspectral remoting sensing --- crop mapping --- image classification --- deep transfer learning --- hyperparameter optimization --- metaheuristic --- soil attribute --- ordinary Kriging --- rational sampling numbers --- spatial heterogeneity --- sampling --- soil pH --- spatial variation --- ordinary kriging --- Land Use/Land Cover --- LISS-III --- Landsat --- Vision Transformer --- Bidirectional long-short term memory --- Google Earth Engine --- Explainable Artificial Intelligence