Adoption of precision agriculture technologies in India and in some developing countries: Scope, present status and strategies

Mondal, Prasenjit; Basu, Manisha

doi:10.1016/j.pnsc.2008.07.020

Cited by 140 publications

(104 citation statements)

References 15 publications

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“…Traditionally farmers used oxen to level the fields, which yielded approximately 800 kilograms per harvest. The Tata experiment used a small precision leveller tractor with GPS; yields rose to 2.25 tonnes, a 281% increase (Mondal, 2009). Increasing the productivity of smallscale farms through precision agriculture has enormous implications for developing countries, as several such as India and Indonesia face demographic booms over the coming decades.…”

Section: The Capacity To Link the Physical World To Digital Network mentioning

confidence: 99%

Harnessing the digital economy for developing countries

2016

OECD Development Centre Working Papers

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OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the authors.This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to the OECD Development Centre, 2 rue André Pascal, 75775 PARIS CEDEX 16, France; or to dev.contact@oecd.org. Documents may be downloaded from: www.oecd.org/dev/wp.

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Section: The Capacity To Link the Physical World To Digital Network mentioning

confidence: 99%

Harnessing the digital economy for developing countries

2016

OECD Development Centre Working Papers

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“…Many related studies have investigated the adoption of ICT tools in the agrifood sector in specific countries using questionnaires (e.g. Domenech et al 2014;Batterink et al 2006;Mondal and Basu 2009). The majority of the papers published (e.g.…”

Section: Introductionmentioning

confidence: 99%

Factors affecting innovation and imitation of ICT in the agrifood sector

2018

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Diffusion of innovations has gained a lot of attention and concerns different scientific fields. Many studies, which examine the determining factors of technological innovations in the agricultural and agrifood sector, have been conducted using the widely used Technology Accepted Model, for a random sample of farmers or firms engaged in agricultural sector. In the present study, a holistic examination of the determining factors that affect the propensity of firms to innovate or imitate, is conducted. The diffusion of ICT tools of firms which are engaged in the NACE 02/03 as well as in the NACE 10/11 classifications for 49 heterogeneous national markets is examined, using the Bass model. The innovation parameter is positively associated with rural income, female employment, export activity and education of farmers, while the imitation parameter is increased in countries whose societies are characterized by uncertainty avoidance.

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“…2 Full-scale airborne imaging via airplanes and helicopters typically rely on multicamera/multispectral systems, which can be costly and difficult to operate, inhibiting their widespread adoption, particularly by farmers in developing countries. 3 In this paper, a simple low-cost alternative is proposed in the form of a commercially available digital camera converted for use in remote sensing of crop health. This system works by detecting spectral reflectance changes in crops and using these as input in an expectation maximization (EM) cluster analysis (with a Gaussian mixture model) to generate early warning indicators of crop stress.…”

Section: Introductionmentioning

confidence: 99%

Low-cost multispectral imaging for remote sensing of lettuce health

Ren

Tripathi

2017

J. Appl. Remote Sens

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, "Low-cost multispectral imaging for remote sensing of lettuce health," J. Appl. Remote Sens. 11(1), 016006 (2017), doi: 10.1117/1.JRS.11.016006. Abstract. In agricultural remote sensing, unmanned aerial vehicle (UAV) platforms offer many advantages over conventional satellite and full-scale airborne platforms. One of the most important advantages is their ability to capture high spatial resolution images (1-10 cm) on-demand and at different viewing angles. However, UAV platforms typically rely on the use of multiple cameras, which can be costly and difficult to operate. We present the development of a simple low-cost imaging system for remote sensing of crop health and demonstrate it on lettuce (Lactuca sativa) grown in Hong Kong. To identify the optimal vegetation index, we recorded images of both healthy and unhealthy lettuce, and used them as input in an expectation maximization cluster analysis with a Gaussian mixture model. Results from unsupervised and supervised clustering show that, among four widely used vegetation indices, the blue wide-dynamic range vegetation index is the most accurate. This study shows that it is readily possible to design and build a remote sensing system capable of determining the health status of lettuce at a reasonably low cost (

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Adoption of precision agriculture technologies in India and in some developing countries: Scope, present status and strategies

Cited by 140 publications

References 15 publications

Harnessing the digital economy for developing countries

Harnessing the digital economy for developing countries

Factors affecting innovation and imitation of ICT in the agrifood sector

Low-cost multispectral imaging for remote sensing of lettuce health

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