Farmers’ willingness to adopt precision agricultural technologies to reduce mycotoxin contamination in grain: evidence from grain farmers in Spain and Lithuania

IF 5.4 2区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Enoch Owusu-Sekyere, Assem Abu Hatab, Carl-Johan Lagerkvist, Manuel Pérez-Ruiz, Egidijus Šarauskis, Zita Kriaučiūnienė, Muhammad Baraa Almoujahed, Orly Enrique Apolo-Apolo, Abdul Mounem Mouazen
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Abstract

Purpose

This study examines the willingness of Spanish and Lithuanian grain farmers to adopt a combined approach of preventive site-specific spraying (PSSS) and selective harvesting (SH), two precision agricultural technologies (below referred to as PSSS-SH) aimed at mitigating the risk of mycotoxin contamination in barley and wheat.

Methods

Data were collected from 190 commercial grain farmers using a choice experimental survey. The empirical analysis relied on the estimation of mixed logit and integrated latent class models.

Results

The surveyed farmers were heterogeneous in their preference for the PSSS-SH technology, with a majority (81%) reporting that they were willing to adopt and pay for the PSSS-SH technology. Furthermore, the farmers’ willingness to adopt PSSS-SH technology was influenced by the trade-offs between the potential production, economic and environmental changes.

Conclusion

Profit maximization is not the only motivation for a farmer’s decision to adopt PSSS-SH, there are also important non-financial benefits that align with the observed choices. Furthermore, the perceived usefulness of the technology, the willingness and readiness to use the technology, and the farmer characteristics (e.g. cooperative membership, employment status, share of household income from grain production and past experience with precision farming technology) were positively associated with uptake of the PSSS-SH technology. Therefore, extension programmes should have a special focus on the perceived usefulness of the technology, the willingness and readiness of farmers to use it, and its unique characteristics.

Abstract Image

农民采用精准农业技术减少谷物霉菌毒素污染的意愿:来自西班牙和立陶宛谷物种植者的证据
目的 本研究探讨了西班牙和立陶宛谷物种植者是否愿意采用预防性定点喷洒(PSSS)和选择性收获(SH)这两种旨在降低大麦和小麦霉菌毒素污染风险的精准农业技术(以下简称 PSSS-SH)。结果接受调查的农民对 PSSS-SH 技术的偏好各不相同,大多数农民(81%)表示愿意采用 PSSS-SH 技术并支付相关费用。此外,农民采用 PSSS-SH 技术的意愿受到潜在生产、经济和环境变化之间权衡的影响。此外,农民对技术有用性的感知、使用技术的意愿和准备程度以及农民的特征(如合作社成员资格、就业状况、家庭收入中来自粮食生产的比例以及过去使用精准农业技术的经验)都与 PSSS-SH 技术的采用呈正相关。因此,推广计划应特别关注技术的实用性、农民使用技术的意愿和准备情况以及技术的独特性。
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来源期刊
Precision Agriculture
Precision Agriculture 农林科学-农业综合
CiteScore
12.30
自引率
8.10%
发文量
103
审稿时长
>24 weeks
期刊介绍: Precision Agriculture promotes the most innovative results coming from the research in the field of precision agriculture. It provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of precision farming. There are many topics in the field of precision agriculture; therefore, the topics that are addressed include, but are not limited to: Natural Resources Variability: Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc. Managing Variability: Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc. Engineering Technology: Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fertigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc. Profitability: MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc. Environment: Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc. Technology Transfer: Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.
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