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The fourth volume of the IPMD Series covers, in three Sections, emerging issues in the integrated management of main nematode parasites of fruit, tree and forest crops. The chapters provide basic data about the crops concerned, listing main nematode threats, in order to facilitate their detection and management. Special attention is given to the management strategies as experienced by farmers, nematologists and consultants, in different areas of the world, including exploitation of plant resistance sources and integrated or organic management. The first Section covers key nematode parasites of tropical fruit crops, including banana, cocoa, coffee, citrus and other tropical crops, and the related management options. In the second Section, nematode problems of grapevine and other Mediterranean crops like pistachio, Prunus spp. and olive are revised. Epidemiology data and management options are given, ranging from the status of grapevine resistance to vector species, to available chemicals, plant quarantine schemes and virus vectors control tools. In the third final Section, an updated review of Pine Wilt Nematode is provided, with new data on the threat represented by its spreading in Western Europe. The book approaches a broad range of subjects in a traditional way, with dedicated and detailed chapters, written by experienced nematologists, on defined topics. This approach provides a focus on the nematological issue of interest or that the reader has to afford, allowing the problem identification and illustrating the solutions developed and experienced by the authors. The general aim of the book, in an integration effort with Vol. 2 of the same IPMD series, is to provide updated background data together with a range of solutions for important nematode pests, worldwide. The volume is directed to students, technicians, extensions and scientists, providing contents of a professional level. Basic concepts and practical examples are provided, useful to enable the reader to analyse and act in relation to his own conditions, crop environment and nematode population parameters. Among the features and benefits of the book also figure practical management data, updated bibliographies and exhaustive illustrations.

Plant nematodes --Integrated control. --- Tree crops --Diseases and pests --Integrated control. --- Tropical crops --Diseases and pests --Integrated control. --- Tropical fruit. --- Nematodes. --- Eelworms --- Nemas --- Nemata --- Nemates --- Nematoda --- Nematoidea --- Round worms --- Roundworm --- Roundworms --- Thread worms --- Threadworms --- Subtropical fruit --- Subtropical fruits --- Tropical fruits --- Life sciences. --- Agriculture. --- Plant science. --- Botany. --- Plant pathology. --- Invertebrates. --- Life Sciences. --- Plant Pathology. --- Plant Sciences. --- Bilateria --- Worms --- Fruit --- Tropical plants --- Plant diseases. --- Botanical science --- Phytobiology --- Phytography --- Phytology --- Plant biology --- Plant science --- Biology --- Natural history --- Plants --- Farming --- Husbandry --- Industrial arts --- Life sciences --- Food supply --- Land use, Rural --- Invertebrata --- Animals --- Botany --- Communicable diseases in plants --- Crop diseases --- Crops --- Diseases of plants --- Microbial diseases in plants --- Pathological botany --- Pathology, Vegetable --- Phytopathology --- Plant pathology --- Vegetable pathology --- Agricultural pests --- Crop losses --- Diseased plants --- Phytopathogenic microorganisms --- Plant pathologists --- Plant quarantine --- Pathology --- Diseases and pests --- Diseases --- Wounds and injuries --- Floristic botany

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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