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Contour farming --- Tillage --- #ABIB:FAOdeposit --- Soil conservation --- Cultivation of soils --- Soil cultivation --- Soil tillage --- Tilling --- Agricultural systems --- Agriculture --- Soil management --- No-tillage

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This book is for those who are seriously engaged in the problems of tillage. Mechanical tillage plays a very important role in shaping the harvest on all soil types under normal weather conditions. The preparation of soil with specified properties (characteristics) depending on arable crops has always been a significant problem. The task of preparing soil can be solved by many types (sorts) of working bodies, tools and traction machines, and in the future by a direct effect on the soil of various types of radiation: thermal, acoustic, microwave, etc. Which technology should be chosen, which me

Tillage. --- Soil management --- Soil productivity --- Productivity, Soil --- Agricultural productivity --- Crop yields --- Crops and soils --- Plant-soil relationships --- Soil fertility --- Soils --- Soil science --- Agronomy --- Cultivation of soils --- Soil cultivation --- Soil tillage --- Tilling --- Agricultural systems --- Agriculture --- No-tillage --- Mathematical models. --- Management

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Charrue --- Ploughs --- Travail du sol --- Tillage --- Expérimentation --- experimentation --- History --- Denmark --- 631.312 --- 631.51 --- Plows --- -Tillage --- -#IHE:BWET --- Cultivation of soils --- Soil cultivation --- Soil tillage --- Tilling --- Agricultural systems --- Agriculture --- Soil management --- No-tillage --- Agricultural machinery --- Soil preparation and ploughing --- History. --- 631.51 Soil preparation and ploughing --- 631.312 Ploughs --- #IHE:BWET --- experimentation. --- Archeologie experimentale --- Copenhague

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Concerns over environmental and human health impacts of conventional weed management practices, herbicide resistance in weeds, and rising costs of crop production and protection have led agricultural producers and scientists in many countries to seek strategies that take greater advantage of ecological processes and thereby allow a reduction in herbicide use. This book provides principles and practices for ecologically based weed management in a wide range of temperate and tropical farming systems. After examining weed life histories and processes determining the assembly of weed communities, the authors describe how tillage and cultivation practices, manipulations of soil conditions, competitive cultivars, crop diversification, grazing livestock, arthropod and microbial biocontrol agents, and other factors can be used to reduce weed germination, growth, competitive ability, reproduction and dispersal. Special attention is given to the evolutionary challenges that weeds pose and the roles that farmers can play in the development of new weed-management strategies.

Weeds --- Agricultural ecology. --- Tillage. --- Agricultural systems. --- Farming systems --- Systems, Agricultural --- Systems, Farming --- Agricultural geography --- Farm management --- Cultivation of soils --- Soil cultivation --- Soil tillage --- Tilling --- Agricultural systems --- Agriculture --- Soil management --- No-tillage --- Agroecology --- Ecology --- Permaculture --- Pest plants --- Weed plants --- Weedy plants --- Plant pests (Plants) --- Agricultural pests --- Botany, Economic --- Plants --- Bio-control of weeds --- Biocontrol of weeds --- Biological control of weeds --- Weed biocontrol --- Weed biological control --- Biological control. --- Ecology. --- Environmental aspects --- Control --- noxious plants --- pest control --- Integrated control --- Biological control --- Plant competition --- Tropical zones --- Temperate zones --- world

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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 publishing 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