Precision Farming in India – A Review

2012 ◽  
Vol 41 (2) ◽  
pp. 139-143 ◽  
Author(s):  
Akhilesh Tiwari ◽  
Praveen Kumar Jaga
Keyword(s):  
Precision Farming

Study on The Economic Motivation Level of Farmers in The Adoption of Precision Farming Technology

2012 ◽  
Vol 2 (2) ◽  
pp. 402-403
Author(s):  
S. Sangeetha S. Sangeetha ◽  
◽  
S. Praveena S. Praveena ◽  
P. Jai Sridhar P. Jai Sridhar
Keyword(s):  
Precision Farming ◽  
Economic Motivation ◽  
Motivation Level ◽  
Precision Farming Technology

Territorial Features of Application of Precision Farming Technologies

2020 ◽  
pp. 59-66
Author(s):  
E.A. Skvortsov ◽  
◽  
A.S. Gusev ◽  
Keyword(s):  
Regional Development ◽  
Unemployment Rate ◽  
Negative Correlation ◽  
Agricultural Production ◽  
Agricultural Development ◽  
Precision Farming ◽  
Production Index ◽  
Scientific Problem ◽  
Development Indicators ◽  
Production Growth

The article discusses the issues of territorial patterns in the implementation of precision farming technologies, which are insufficiently studied and constitute a significant scientific problem. The purpose of the study is to identify the territorial patterns of the introduction of precision farming technologies in conjunction with the indicators of agricultural development in the regions. The number of applied precision farming technologies was clarified, 37 regions took part in the study, 24 of them provided information on the application of these technologies. The results of correlation of regional development indicators (12 indicators in three blocks) and the amount of equipment with precision farming elements are presented. The greatest positive correlation is observed between the introduction of precision farming technologies and the agricultural production index at comparable prices (0.51) and the level of subsidies (0.37). The greatest negative correlation is observed between the introduction of these technologies and the change in the registered unemployment rate (-0.3). Based on the results obtained, it can be assumed that in regions with high values of agricultural production growth and subsidies, precision farming technologies will be most intensively introduced.

Development of an unmanned tractor chassis for precision farming

2020 ◽  
pp. 47-53
Author(s):  
YU.V. Galyishev ◽  
R.Yu. Dobretsov ◽  
G.P. Porshnev ◽  
E.G. Saharova ◽  
D.V. Uvakina ◽  
...  
Keyword(s):  
Precision Farming ◽  
Autonomous Control ◽  
Kinematic Scheme ◽  
Local Complex ◽  
Friction Clutch

The development of the chassis of an unmanned tractor for a local complex of precision fanning is considered. The design is based on the kinematic scheme of the shaft gearbox, which implements a large number of modes and the principle of two-line transmission. A feature of this scheme is the presence of parallel load shafts. Keywords: wheeled tractor, autonomous control, two-line transmission, slipping, disc friction clutch. [email protected]

scholarly journals Reference Measurements in Developing UAV Systems for Detecting Pests, Weeds, and Diseases

2021 ◽  
Vol 13 (7) ◽  
pp. 1238
Author(s):  
Jere Kaivosoja ◽  
Juho Hautsalo ◽  
Jaakko Heikkinen ◽  
Lea Hiltunen ◽  
Pentti Ruuttunen ◽  
...  
Keyword(s):  
Reference Data ◽  
Measurement Techniques ◽  
Synthetic Data ◽  
Ground Truth ◽  
Precision Farming ◽  
Aerial Imaging ◽  
Aerial Vehicle ◽  
Uav Images ◽  
Reference Measurements

The development of UAV (unmanned aerial vehicle) imaging technologies for precision farming applications is rapid, and new studies are published frequently. In cases where measurements are based on aerial imaging, there is the need to have ground truth or reference data in order to develop reliable applications. However, in several precision farming use cases such as pests, weeds, and diseases detection, the reference data can be subjective or relatively difficult to capture. Furthermore, the collection of reference data is usually laborious and time consuming. It also appears that it is difficult to develop generalisable solutions for these areas. This review studies previous research related to pests, weeds, and diseases detection and mapping using UAV imaging in the precision farming context, underpinning the applied reference measurement techniques. The majority of the reviewed studies utilised subjective visual observations of UAV images, and only a few applied in situ measurements. The conclusion of the review is that there is a lack of quantitative and repeatable reference data measurement solutions in the areas of mapping pests, weeds, and diseases. In addition, the results that the studies present should be reflected in the applied references. An option in the future approach could be the use of synthetic data as reference.

Precision farming — the environmental challenge

2001 ◽  
Vol 30 (1-3) ◽  
pp. 31-43 ◽  
Author(s):  
Hermann Auernhammer
Keyword(s):  
Precision Farming ◽  
Environmental Challenge

The role of communication and co-operation in the adoption of precision farming

2009 ◽  
Vol 12 (1) ◽  
pp. 2-17 ◽  
Author(s):  
T. Kutter ◽  
S. Tiemann ◽  
R. Siebert ◽  
S. Fountas
Keyword(s):  
Precision Farming

Modelling of solar radiation influenced by topographic shading––evaluation and application for precision farming

2005 ◽  
Vol 30 (1-3) ◽  
pp. 143-149 ◽  
Author(s):  
Hannes Isaak Reuter ◽  
Kurt Christian Kersebaum ◽  
Ole Wendroth
Keyword(s):  
Solar Radiation ◽  
Precision Farming

Precision farming from Rockwell

2002 ◽  
Author(s):  
K.V. Bloom ◽  
L.C. Smith ◽  
C.A. Elliott ◽  
S.J. Boerhave
Keyword(s):  
Precision Farming

Precision Farming: An Introduction

1994 ◽  
Vol 23 (4) ◽  
pp. 275-280 ◽  
Author(s):  
Simon Blackmore
Keyword(s):  
Spatial Variability ◽  
Information Technologies ◽  
Management Practice ◽  
Precision Farming ◽  
Field Size ◽  
And Control

Traditional arable management practice has tended to manage fields uniformly and has tended to ignore the inherent spatial variability found on most farms. This has been exacerbated by the increase of field size due to pressures from mechanization. Precision farming is a management practice that has been made possible by the advent of suitable information technologies, and it provides a framework within which arable managers can more accurately understand and control what happens on their farms.

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