This book describes how models are used to monitor crops and soils in precision agriculture, and how they are used to support farmers’ decisions. The introductory section starts with an overview of precision agriculture from the early days of yield monitoring in the 1980s to the present, with a focus on the role of models. The section continues with descriptions of the different kinds of models and the opportunities for their application in precision agriculture. The section concludes with a chapter on socio-economic drivers and obstacles to the adoption of precision agriculture technologies. The middle section of the book explores the state-of-the-art in modeling for precision agriculture. Individual chapters focus on the major processes in precision agriculture: water use, nitrogen and other amendments, as well as weeds, pests and diseases. The final section contains a series of short chapters that each describe a commercial, model-based service that is currently available to farmers. The book aims to provide useful information to graduate-level professionals that want to broaden their knowledge of precision agriculture; to scientists who want to learn about using academic knowledge in practical farming; and to farmers, farm consultants and extension workers who want to increase their understanding of the science behind some of the commercial software available to the farming community.

Machine vision applications in precision agriculture have attracted a great deal of attention. They focus on monitoring, protection, and management of various plant populations. These applications have shown potential value in reforming crucial components of plant production, including fine-grained ripeness recognition of all kinds of plants and detecting and classifying weeds, seeds, and pests for crop health, quality, and quantity enhancement. In recent decades, the extensive achievements of deep learning techniques have shown significant opportunities for almost all fields. Accordingly, many deep learning models have been presented for different types of images and have achieved promising outcomes. The deep learning-based approaches can contribute to gaining insights into the plants' inherent characteristics and the surrounding environmental elements. This research topic's primary value is providing a platform for deep learning-based applications for precision agriculture. These applications can be fairly evaluated and compared with each other. Accordingly, more effective and efficient detection and classification approaches for precision agriculture can be developed or optimized.

Precision Agriculture is becoming ever more relevant as the agricultural industry struggles to come to terms with the environment, economics, traceability, vehicle guidance and crop management. Whilst some benefits have proved elusive, others contribute positively to today’s agriculture. Research continues to be necessary and needs to be reported and disseminated to a wide audience. These proceedings contain the reviewed papers from the 7th European Conference on Precision Agriculture. The papers reflect the wide range of disciplines that impinge upon precision agriculture including remote sensing, plant disease and weed detection, yield monitoring, soil sensing, geo statistics and path planning, regional and crop modelling, cooperation and guidance of robots, precision application, ICT in precision agriculture, future farming and European relevance for precision agriculture. The broad range of research topics reported is a valuable resource for researchers, advisors, teachers and professionals in agriculture. Also note that the reviewed papers from the 4th European Conference on Precision Livestock Farming are presented in a companion publication.

"With ever-increasing pressures on world agriculture in both economic and environmental terms, application of the concept of precision agriculture is one way of enabling farmers and producers to cope. ‘Doing arable agriculture and horticulture more precisely’ means that the use of inputs is optimised, crop yield and quality are maximised and leakage of agro-chemicals and fertilisers to the environment is minimised. This publication contains papers presented at the 6th European Conference on Precision Agriculture. The papers reflect the wide range of disciplines encompassed by precision agriculture, including: soil physics, crop physiology, agronomy, IT, agricultural technology, sensor technology, remote sensing, geostatistics and environmental science. The wide range of research topics reported will be a valuable resource for researchers, advisors, teachers and professionals in agriculture long after the conference has finished. Peer-reviewed papers from the 3rd European Conference on Precision Livestock Farming are presented in a companion proceedings, Precision livestock farming ’07."

This book investigates new agricultural systems such as organic and green manuring, as well as integrated pest management practices, and looks at how they can improve farm productivity against the enhancements for the environment. Much of the information presented focuses on microinvestigation of the soil, and on the effects of soil variability within fields on yields and nutrient flows.

Precision agriculture is a reality in agriculture and is playing a key role as the industry comes to terms with the environment, market forces, quality requirements, traceability, vehicle guidance and crop management. Sensors now in use in agriculture are generating ‘Big Data’ leading to the use of machine learning and AI - an increasing challenge for agriculture. Research continues to be necessary, and needs to be reported and disseminated to a wide audience. These edited proceedings contain peer reviewed papers presented at the 14th European Conference on Precision Agriculture, held in Bologna, Italy. The papers reflect the wide range of disciplines that impinge on precision agriculture - technology, crop science, soil science, agronomy, information technology, decision support, remote sensing, data analysis and others. The broad range of research topics reported will be a valuable resource for researchers, advisors, teachers and professionals in agriculture long after the conference has finished.

Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling, provide insight into the diversity and the complexity of developments of RS applications in agriculture. Five thematic focuses have emerged from the published papers: yield estimation, land cover mapping, soil nutrient balance, time-specific management zone delineation and the use of UAV as agricultural aerial sprayers. All contributions exploited the use of remote sensing data from different platforms (UAV, Sentinel, Landsat, QuickBird, CBERS, MODIS, WorldView), their assimilation into crop models (DSSAT, AQUACROP, EPIC, DELPHI) or on the synergy of Remote Sensing and modeling, applied to cardamom, wheat, tomato, sorghum, rice, sugarcane and olive. The intended audience is researchers and postgraduate students, as well as those outside academia in policy and practice.

Precision Agriculture presents the latest scientific results from worldwide research, field studies and practical application. The book contains peer-reviewed papers that were presented at the 4th European Conference on Precision Agriculture. The papers focus on precision agriculture research containing interdisciplinary site analysis, integrative measures and management strategies as well as on practical applications. The economic and environmental effects of implementing the precision agriculture concept are featured in many of them. The unique feature of the fourth conference was that it was held in parallel with the 1st European Conference on Precision Livestock Farming - the links between both technologies were drawn and the possible interactions between them were shown for the first time. The potential is to integrate both technologies to encompass the whole farm. Peer-reviewed papers from the Precision Livestock conference are presented in a companion proceedings, Precision Livestock Farming.

Precision agriculture is now 'main stream' in agriculture and is playing a key role as the industry comes to terms with the environment, market forces, quality requirements, traceability, vehicle guidance and crop management. Research continues to be necessary and needs to be reported and disseminated to a wide audience. This book contains peer reviewed papers presented at the 9th European Conference on Precision Agriculture, held in Lleida, Spain. The papers reflect the wide range of disciplines that impinge on precision agriculture: technology, crop science, soil science, agronomy, information technology, decision support, remote sensing and others. The broad range of research topics reported will be a valuable resource for researchers, advisors, teachers and professionals in agriculture long after the conference has finished.

Most books covering the use of computer models in agricultural management systems target only one or two types of models. There are few texts available that cover the subject of systems modeling comprehensively and that deal with various approaches, applications, evaluations, and uses for technology transfer. Agricultural System Models in Field Res