Determinants of adoption and adoption intensity of precision agriculture technologies: evidence from South Dakota

Deepthi E Kolady,Md Mahi Uddin,Evert Van Der Sluis,Allen P Deutz

doi:10.1007/s11119-020-09750-2

Deepthi E Kolady, Md Mahi Uddin + Show 2 more

Open Access

https://doi.org/10.1007/s11119-020-09750-2

Copy DOI

Journal: Precision Agriculture	Publication Date: Aug 19, 2020
Citations: 23	License type: open-access

Affiliation: South Dakota State University

Abstract

Precision agriculture technologies (PATs) are promoted as part of both economically efficient and environmentally sustainable agriculture practices. Available PATs are generally classified into two groups; namely, embodied-knowledge and information-intensive PATs. Adoption levels of embodied-knowledge PATs are high relative to information-intensive PATs. Previous studies on the adoption of PATs do not differentiate between embodied-knowledge and information-intensive PATs. Additionally, most studies focus on the adoption of one or two of the available PATs rather than on adoption intensity—defined as the total number of individual PATs adopted. This study fills this gap in the literature by focusing on PAT adoption in general, and adoption intensity of embodied-knowledge and information-intensive PATs in particular. The study uses data from 198 farm-operator respondents in eastern South Dakota from a 2017 survey and employs descriptive statistics and probit and Poisson regression models for the analyses. As per the study, GPS guidance, yield monitor, and automatic section control systems are the most popular PATs, each with adoption rates of over 50%. Overall, findings from the study show that the effect of cropland size, producers’ perceptions of profitability, and operator off-farm income are similar for both adoption and adoption intensity of embodied-knowledge and information-intensive PATs. However, there are differences in the effect of land productivity and familiarity with computer use between adoption and adoption intensity and between embodied-knowledge and information-intensive PATs. The effect of producers’ perception of the environmental benefits of PATs is inconclusive and needs to be investigated in future research. The results indicate that analyzing PATs as a group of technologies masks differences in determinants between embodied-knowledge and information-intensive PATs. The study provides insights for developing programs, policies, and outreach efforts that encourage the adoption and adoption intensity of both embodied-knowledge and information-intensive PATs. Findings from the study will also be of interest to precision agriculture researchers, extension personnel, agribusinesses, and policymakers who may consider PATs as tools for improving agricultural sustainability and food security.

Highlights

In recent years much attention has been paid to soil health, water quality, and long-term sustainability of agricultural production globally
As reported by Miller et al (2019), embodied-knowledge precision agriculture technologies (PATs) such as GPS guidance, autosteer, and automatic section control are more popular than information-intensive PATs in South Dakota
This study analyzes the determinants of adoption and adoption intensity of embodiedknowledge and information-intensive PATs, separately and by pooling them together

Summary

Introduction

In recent years much attention has been paid to soil health, water quality, and long-term sustainability of agricultural production globally. Approaches to addressing the negative environmental and ecosystem impacts of agriculture while ensuring long-term economic sustainability and food security include the adoption of precision agriculture technologies (PATs). The International Society of Precision Agriculture (ISPA 2018) defines precision agriculture as: “a management strategy that gathers, processes and analyses temporal, spatial and individual data and combines it with other information to guide site, plant or animal specific management decisions to improve resource efficiency, productivity, quality, profitability and sustainability of agricultural production.”. Many agricultural producers utilize this data-driven technology as they seek to optimize the amounts, precise locations, and timing of applying seeds, fertilizers, and herbicides to their fields, with the aims of improving input utilization, increasing crop output and optimizing profits (Tey and Brindal 2012; Chen et al 2009). PAT allows producers to conserve inputs and improve efficiencies while maintaining or even improving output, and enhancing profitability (Deutz 2018)

Objectives

Methods

Results

Conclusion