Comparative environmental analysis of sugar beet production using a solar-driven robot and conventional systems from a sustainability perspective

IF 6.1 Q2 ENGINEERING, ENVIRONMENTAL Cleaner Environmental Systems Pub Date : 2024-04-13 DOI:10.1016/j.cesys.2024.100186
Indrė Bručienė, Dainius Savickas, Egidijus Šarauskis
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Abstract

In the context of rapid global population growth and climate change, balancing agricultural productivity with environmental sustainability has never been more important. Precision farming technologies, including robotics, are touted as having huge potential to increase farm productivity, reduce energy and resource use and compact soil, while reducing the overall environmental impact of on-farm production. This comprehensive study presents, for the first time, a detailed analysis and environmental benchmarking of two organic sugar beet production (SBP) systems, conventional (CONV) and robotic (RBT), based on field experiments in Lithuanian conditions where a solar-powered robot is integrated into the production system to carry out sowing and weeding operations. In order to reduce the potential environmental impact and to understand the consequences of using the robot in agriculture, a Life Cycle Assessment (LCA) of the entire SBP process up to the factory gate was carried out. The results of the analysis show that the conventional system has higher total GHG emissions than the robotic system, 36.98 and 27.18 kg CO2eq t−1, respectively, with poultry manure being the largest contributor. The higher beet yield in the RBT system, mainly due to effective weed control, resulted in a higher GHG emissions ratio (14.72) and a higher sustainability index (13.72). The LCA results showed that the CONV system had a higher negative environmental impact than the RBT in all eleven environmental impact categories assessed, with the most pronounced difference in the Ozone Depletion (OD) category. Diesel fuel was identified as the most important environmental factor for organically growing sugar beet in all considered impact categories, with the most notable environmental impact (about 94%) in the terrestrial ecotoxicity category in both systems. Normalization of the results showed that marine aquatic ecotoxicity (ME) had the greatest (78%) influence of all exposure categories for both cultivation systems, CONV – 22079.82, and RBT 18121.61 kg 1.4-DBeq per ton of produced sugar beet. The study found that increasing yields and reducing fossil fuel use in organic farming are the two most promising strategies for achieving sustainability and efficiency in food production.

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从可持续性角度对使用太阳能驱动机器人和传统系统生产甜菜的环境进行比较分析
在全球人口快速增长和气候变化的背景下,平衡农业生产率与环境可持续性变得空前重要。包括机器人技术在内的精准农业技术被认为在提高农场生产率、减少能源和资源使用以及压实土壤方面具有巨大潜力,同时还能减少农场生产对环境的整体影响。本综合研究首次详细分析了两种有机甜菜生产(SBP)系统,即传统系统(CONV)和机器人系统(RBT),并根据立陶宛的田间试验,将太阳能机器人集成到生产系统中,进行播种和除草作业。为了减少对环境的潜在影响,并了解在农业中使用机器人的后果,对直至工厂大门的整个 SBP 流程进行了生命周期评估(LCA)。分析结果表明,传统系统的温室气体总排放量高于机器人系统,分别为 36.98 千克二氧化碳当量吨-1 和 27.18 千克二氧化碳当量吨-1,其中家禽粪便的排放量最大。RBT 系统甜菜产量较高,主要原因是有效控制了杂草,因此温室气体排放比(14.72)和可持续性指数(13.72)较高。生命周期评估结果表明,在评估的所有 11 个环境影响类别中,CONV 系统对环境的负面影响均高于 RBT 系统,其中臭氧消耗(OD)类别的差异最为明显。在所有考虑的影响类别中,柴油被确定为有机种植甜菜最重要的环境因素,在陆地生态毒性类别中,两种系统对环境的影响最为显著(约 94%)。结果归一化显示,海洋水生生态毒性(ME)在两种种植系统的所有影响类别中影响最大(78%),CONV - 22079.82,RBT 18121.61 kg 1.4-DBeq per ton produced sugar beet。研究发现,在有机农业中,提高产量和减少化石燃料的使用是实现粮食生产可持续性和效率的两个最有前途的战略。
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来源期刊
Cleaner Environmental Systems
Cleaner Environmental Systems Environmental Science-Environmental Science (miscellaneous)
CiteScore
7.80
自引率
0.00%
发文量
32
审稿时长
52 days
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