Digital revolution and Big Data: a new revolution in agriculture.

Himesh, S.; Rao, E. V. S. Prakasa; Gouda, K. C.; Ramesh, K. V.; S, Rakesh V; Mohapatra, Geetilaxmi; Rao, B. Krishna; Sahoo, Saroj Kumar; Ajilesh, P.

doi:10.1079/pavsnnr201813021

Cited by 56 publications

(32 citation statements)

References 5 publications

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“…Unlike precision agriculture, which takes into account only the variability of the field, intelligent agriculture goes further, including the entire agricultural production cycle, aiming to improve context and situation awareness triggered by real-time events [25]. Combining digital agriculture and precision farming technologies will be possible to reduce costs and maximize yields and profits [24].…”

Section: 2mentioning

confidence: 99%

Reference Model as Support for the Implementation of Agriculture 4.0

Iaksch

Camatti

Borsato

et al. 2021

Advances in Transdisciplinary Engineering

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Agriculture is facing increasing challenges due to several factors such as population growth, climate change, and variation of prices practiced by the market. It has been looking for ways to improve profitability and agricultural efficiency through better management control based on information and knowledge generated on the farm in its specific context. Innovative technologies and solutions have been applied as an alternative for the collection and processing of this information with the fourth industrial revolution, which is generated by systems, equipment, markets, and agents involved in agricultural production. Transforming this data collected in the field into valuable data that supports better decision-making is essential. Through a literature review, it was established that the artifact to be developed in this project corresponds to an information model over an agricultural scenario. Following the Design Science Research (DSR) methodology, to reach this objective will be necessary to develop three artifacts. In this article, the first artifact is presented: a model that provides a systemic view and characterizes Agriculture 4.0.

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Section: 2mentioning

confidence: 99%

Reference Model as Support for the Implementation of Agriculture 4.0

Iaksch

Camatti

Borsato

et al. 2021

Advances in Transdisciplinary Engineering

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show abstract

“…Combination of technologies and tools, simulation, modeling, BD, remote sensing data, Geographical Information System (GIS), Automatic Weather Stations (AWS), and internet of things (IoTs) can be used to promote the implementation of IPM. New generation of GPS, sensors-fitted farm equipment, e-tablets, and mobile applications (Plantix) could be used for future pests and diseases identification and monitoring [47]. Since implementation of IPM programs depends largely on information, it is anticipated that a giant step being taken in areas such as principles of insect sampling, computer programming and mathematics, understanding of pests biological and ecological aspects, and simulation techniques and modeling [11].…”

Section: Future Prospects Of Ipmmentioning

confidence: 99%

Integrated Insect Pest Management

El-Shafie¹

2020

Pests Control and Acarology

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Insect pests cause substantial losses to food and fiber crops worldwide. Additionally, they vector human and domestic animal diseases. The dependence on pesticides as a sole method of control has resulted in the development of insect resistance and negative effects on human health, natural enemies, and the environment. The concept of integrated pest management (IPM) originated almost 60 years ago in response to these negative impacts of pesticides. Currently, IPM is a robust paradigm of pest control around the globe. This chapter reviews the history of IPM, its main principles, decision-making rules, the components, and main tactical methods used. Innovative tactical methods such as sterile insect technique (SIT), incompatible insect technique (IIT), and push-pull strategy are discussed. Moreover, challenges of implementation and future prospects of IPM are highlighted.

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“…The agriculture sector is undergoing a transformation driven by new technologies, which seems very promising as it will enable this primary sector to move to the next level of farm productivity and profitability [1]. Precision Agriculture, which consist of applying inputs (what is needed) when and where is needed, has become the third wave of the modern agriculture revolution (the first was mechanization and the second the green revolution with its genetic modification [2]), and nowadays, it is being enhanced with an increase of farm knowledge systems due to the availability of larger amounts of data.…”

Section: Introductionmentioning

confidence: 99%

From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management

2020

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The information that crops offer is turned into profitable decisions only when efficiently managed. Current advances in data management are making Smart Farming grow exponentially as data have become the key element in modern agriculture to help producers with critical decision-making. Valuable advantages appear with objective information acquired through sensors with the aim of maximizing productivity and sustainability. This kind of data-based managed farms rely on data that can increase efficiency by avoiding the misuse of resources and the pollution of the environment. Data-driven agriculture, with the help of robotic solutions incorporating artificial intelligent techniques, sets the grounds for the sustainable agriculture of the future. This paper reviews the current status of advanced farm management systems by revisiting each crucial step, from data acquisition in crop fields to variable rate applications, so that growers can make optimized decisions to save money while protecting the environment and transforming how food will be produced to sustainably match the forthcoming population growth.

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Digital revolution and Big Data: a new revolution in agriculture.

Cited by 56 publications

References 5 publications

Reference Model as Support for the Implementation of Agriculture 4.0

Reference Model as Support for the Implementation of Agriculture 4.0

Integrated Insect Pest Management

From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management

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