Artificial Intelligence Applications in Specialty Crops
Author : Yiannis Ampatzidis
Publisher : Frontiers Media SA
Page : 444 pages
File Size : 21,70 MB
Release : 2022-03-02
Category : Science
ISBN : 2889745570
Artificial Intelligence and Data Science in Agriculture
Author : Chandrasekar Vuppalapati
Publisher :
Page : 0 pages
File Size : 29,65 MB
Release : 2024-10-15
Category : Business & Economics
ISBN : 9783111438412
Book Description
This book presents some of the most important applications of Artificial Intelligence, Data Science and Machine Learning for questions arising in agriculture. The book introduces data sources and methods used to estimate crop yields and prices under different climate scenarios. The methods and models introduced in the book can be applied across a large set of concrete questions across technology, industry, economics and sustainablility.
Artificial Intelligence Applications in Agriculture and Food Quality Improvement
Author : Khan, Mohammad Ayoub
Publisher : IGI Global
Page : 352 pages
File Size : 37,87 MB
Release : 2022-05-27
Category : Technology & Engineering
ISBN : 1668451433
Book Description
Food is a necessary aspect of human life, and agriculture is crucial to any country’s global economy. Because the food business is essential to both a country’s economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.
Specialty Crops for Climate Change Adaptation
Author : Chandrasekar Vuppalapati
Publisher : Springer Nature
Page : 836 pages
File Size : 41,55 MB
Release : 2023-11-15
Category : Computers
ISBN : 3031383990
Book Description
Specialty crops are defined as fruits and vegetables, tree nuts, dried fruits, horticulture, and nursery crops including floriculture. The value of specialty crop production in the United States accounted for 18.44 % of the $433.569 billion in agriculture cash receipts collected in 2021. In 2020, that ratio was 21.47% of the $363.464 billion. Specialty crops are gaining increasing attention across nation as demonstrated in the 2018 farm bill (Agricultural Act of the 2018 Farm Bill (P.L. 115-334)) with the increased number of provisions addressing specialty crop issues, reflecting their growing role in the global economy. The cultivation of Specialty crops, nevertheless, has its own challenges. Specialty crops are generally more sensitive to climatic stressors and require more comprehensive management compared to traditional row crops. Specialty crops face significant financial risks threatening US$1.6 Trillion global market due to their higher water demand. The mission of the book is to prepare current and future software engineering teams, agriculture students, economists, macroeconomists with the skills and tools to fully utilize advanced data science, artificial intelligence, climate patterns, and economic models to develop software capabilities that help to achieve Specialty crops and economic sustainability, through improved productivity for years to come and ensure enough food for the future of the planet and generations to come!
Machine Learning Applications for Agricultural Economics
Author : Kennedy Odongo
Publisher :
Page : 0 pages
File Size : 22,19 MB
Release : 2023
Category : Agriculture
ISBN :
Book Description
This dissertation utilizes machine learning to answer questions in agricultural economics in three related but independent essays. Machine learning and data science are increasingly being adopted in interdisciplinary work providing complimentary analytical methods and data tools for economics research. I use machine learning to investigate how COVID-19 and the resulting media coverage affected specialty crop markets dynamics and to develop insights into how attributes of a new apple variety can be utilized in an advertising campaign to derive demand.The first paper of my dissertation investigates how COVID-19 and related social and traditional media coverage affected shipping point prices of specialty crops. I use Twitter data to estimate how the prevalence COVID-19 topics affect crop demand. The results show that crops that are usually consumed as food away from home (FAFH) were the most affected by COVID-19 relative to crops usually consumed as food at home (FAH). The impact of the pandemic was heterogenous across specialty crops with crops whose usage is concentrated in FAFH settings experiencing a decrease in demand compared to crops used mostly in FAH settings.The second compares the performance of two time series forecasting techniques in the context of event studies. The event in this paper is the economy-wide COVID-19 shutdown. The results show that the prices in strawberry and apples markets were higher during the pandemic than they should have been. In comparing the two forecasting methods, the neural network outperforms ARIMA on error metrics such as the Mean Absolute Error.The third paper evaluates how attributes for newly developed WA 38 apple sold under the Cosmic Crisp brand can be used to accelerate demand. I identify the market segments where marketing is effective and identify the attributes of the brand that most appeal to consumers. The results show that sentiment on Cosmic Crisp brand is positive with an overall compound score of 0.2263. The online conversation on the brand revolves around the history and novelty of the variety, farm tours to drive demand, the taste and appearance of the apple and its affiliation to the university where it was developed.
Artificial Intelligence in Agriculture
Author : Rajesh Singh
Publisher : CRC Press
Page : 186 pages
File Size : 18,66 MB
Release : 2021-11-23
Category : Technology & Engineering
ISBN : 1000506215
Book Description
This book is a platform for anyone who wishes to explore Artificial Intelligence in the field of agriculture from scratch or broaden their understanding and its uses. This book offers a practical, hands-on exploration of Artificial Intelligence, machine learning, deep Learning, computer vision and Expert system with proper examples to understand. This book also covers the basics of python with example so that any anyone can easily understand and utilize artificial intelligence in agriculture field. This book is divided into two parts wherein first part talks about the artificial intelligence and its impact in the agriculture with all its branches and their basics. The second part of the book is purely implementation of algorithms and use of different libraries of machine learning, deep learning and computer vision to build useful and sightful projects in real time which can be very useful for you to have better understanding of artificial intelligence. After reading this book, the reader will an understanding of what Artificial Intelligence is, where it is applicable, and what are its different branches, which can be useful in different scenarios. The reader will be familiar with the standard workflow for approaching and solving machine-learning problems, and how to address commonly encountered issues. The reader will be able to use Artificial Intelligence to tackle real-world problems ranging from crop health prediction to field surveillance analytics, classification to recognition of species of plants etc. Note: T&F does not sell or distribute the hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. This title is co-published with NIPA.
Nondestructive Evaluation of Agro-products by Intelligent Sensing Techniques
Author : Jiangbo Li
Publisher : Bentham Science Publishers
Page : 312 pages
File Size : 35,25 MB
Release : 2021-01-22
Category : Science
ISBN : 9789811485794
Book Description
With rapid progress being made in both theory and practical applications, Artificial Intelligence (AI) is transforming every aspect of life and leading the world towards a sustainable future. AI technology is fundamentally and radically affecting agriculture with a move towards smart systems. The outcome of this transition is improved efficiency, reduced environmental pollution, and enhanced productivity of crops.Nondestructive Evaluation of Agro-products by Intelligent Sensing Techniques is a reference which provides readers timely updates in the progress of intelligent sensing techniques used for nondestructive evaluation of agro-products. Chapters, each contributed by experts in food safety and technology, describe existing and innovative techniques that could be or have been applied to agro-products quality and safety evaluation, processing, harvest, traceability, and so on. The book includes 11 individual chapters, with each chapter focusing on a specific aspect of intelligent sensing techniques applied in agriculture. Specifically, the first chapter introduces the reader to representative techniques and methods for nondestructive evaluation. Subsequent chapters present detailed information about the processing and quality evaluation of agro-products (e.g., fruits, and vegetables), food grading, food tracing, and the use of robots for harvesting specialty crops.Key Features: - 11 chapters, contributed by experts that cover basic and applied research in agriculture- introduces readers to nondestructive evaluation techniques- covers food quality evaluation processes- covers food grading and traceability systems- covers frontier topics that represent future trends (robots and UAVs used in agriculture)- familiarizes the readers with several intelligent sensing technologies used in the agricultural sector (including machine vision, near-infrared spectroscopy, hyperspectral/multispectral imaging, bio-sensing, multi-technology fusion detection)- provides bibliographic references for further reading- gives applied examples on both common and specialty cropsThis reference is intended as a source of updated information for consultants, students and academicians involved in agriculture, crops science and food biotechnology. Professionals involved in food safety and security planning and policymaking will also benefit from the information presented by the authors
Nondestructive Evaluation of Agro-products by Intelligent Sensing Techniques
Author : Jiangbo Li
Publisher : Bentham Science Publishers
Page : 314 pages
File Size : 13,72 MB
Release : 2021-01-22
Category : Technology & Engineering
ISBN : 981148578X
Book Description
With rapid progress being made in both theory and practical applications, Artificial Intelligence (AI) is transforming every aspect of life and leading the world towards a sustainable future. AI technology is fundamentally and radically affecting agriculture with a move towards smart systems. The outcome of this transition is improved efficiency, reduced environmental pollution, and enhanced productivity of crops. Nondestructive Evaluation of Agro-products by Intelligent Sensing Techniques is a reference which provides readers timely updates in the progress of intelligent sensing techniques used for nondestructive evaluation of agro-products. Chapters, each contributed by experts in food safety and technology, describe existing and innovative techniques that could be or have been applied to agro-products quality and safety evaluation, processing, harvest, traceability, and so on. The book includes 11 individual chapters, with each chapter focusing on a specific aspect of intelligent sensing techniques applied in agriculture. Specifically, the first chapter introduces the reader to representative techniques and methods for nondestructive evaluation. Subsequent chapters present detailed information about the processing and quality evaluation of agro-products (e.g., fruits, and vegetables), food grading, food tracing, and the use of robots for harvesting specialty crops. Key Features: - 11 chapters, contributed by experts that cover basic and applied research in agriculture - introduces readers to nondestructive evaluation techniques - covers food quality evaluation processes - covers food grading and traceability systems - covers frontier topics that represent future trends (robots and UAVs used in agriculture) - familiarizes the readers with several intelligent sensing technologies used in the agricultural sector (including machine vision, near-infrared spectroscopy, hyperspectral/multispectral imaging, bio-sensing, multi-technology fusion detection) - provides bibliographic references for further reading - gives applied examples on both common and specialty crops This reference is intended as a source of updated information for consultants, students and academicians involved in agriculture, crops science and food biotechnology. Professionals involved in food safety and security planning and policymaking will also benefit from the information presented by the authors.
Computer Vision and Machine Learning in Agriculture, Volume 2
Author : Mohammad Shorif Uddin
Publisher : Springer Nature
Page : 269 pages
File Size : 34,56 MB
Release : 2022-03-13
Category : Technology & Engineering
ISBN : 9811699917
Book Description
This book is as an extension of previous book “Computer Vision and Machine Learning in Agriculture” for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.
Application of Machine Learning in Agriculture
Author : Mohammad Ayoub Khan
Publisher : Academic Press
Page : 332 pages
File Size : 11,13 MB
Release : 2022-05-14
Category : Business & Economics
ISBN : 0323906680
Book Description
Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning. As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development. This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics. - Addresses the technology of smart agriculture from a technical perspective - Reveals opportunities for technology to improve and enhance not only yield and quality, but the economic value of a food crop - Discusses physical instruments, simulations, sensors, and markets for machine learning in agriculture
