Sensors and Monitoring for Production and Distribution of a Tropical Fruit

Q3 Agricultural and Biological Sciences Environmental Control in Biology Pub Date : 2018-04-01 DOI:10.2525/ECB.56.23
S. Fukuda, W. Spreer, Marcus Mnagle, E. Yasunaga
{"title":"Sensors and Monitoring for Production and Distribution of a Tropical Fruit","authors":"S. Fukuda, W. Spreer, Marcus Mnagle, E. Yasunaga","doi":"10.2525/ECB.56.23","DOIUrl":null,"url":null,"abstract":"able development goals (SDGs) of the United Nations (2016). These comprehensive goals cover all possible topics toward sustainable development. Agriculture is a human activity which heavily relies on natural resources for food production, and thus directly and indirectly impacts natural systems. Considering the balance between environment and natural resources management including agriculture, the water-energy-food (WEF) nexus (Flammini et al., 2014) has emerged as a key approach towards SDGs. Self-evidently, human beings depend on WEF, and conserving them under the pressure of population growth and climate change is an important challenge. Worldwide, agricultural water use accounts for 70% of total water use, and more than 90% in the least developed countries (WWAP, 2012). It is expected to increase because of population growth and changing food demands. Water use for agriculture is in competition with domestic and industrial sectors. Climate change may further foster such conflicts, resulting in overexploitation of both surface water and groundwater resources. Therefore, agricultural water use and distribution need to be efficiently managed considering local conditions. Energy is another important factor for agriculture, covering the entire chain from production, harvesting, processing, distribution and consumption. Pressurized irrigation systems (e.g. drip and sprinkler irrigation) are important tools for water saving and increasing production but consumes significant amounts of energy. Fuels are used for processing, storage and transportation of fresh agricultural products to achieve a long shelf life during a supply chain. Advanced storage and transportation allow for supplying quality products to distant markets. A comprehensive research framework, adopting the WEF nexus approach, is needed for research and developed for an improved food system (e.g., from field to fork) from a viewpoint of sustainable development. In 2013, the research consortium established a project aiming at the development of intensive production system with improved distribution systems of fresh mango fruit (Mangifera indica L.) between Thailand and Japan. To this end, various kinds of data have been collected continuously from farm to table using Information and Communications Technologies (ICTs) such as advanced sensors and semi-real-time field monitoring devices. In addition, laboratory experiments were conducted to characterize ecophysiological traits (e.g., respiration rates and climacteric ripening process) of fresh mango fruit. We have applied machine learning methods in order to evaluate the effects of production environments including irrigation regimes on the yield and quality of fresh mango fruit (Fukuda et al., 2013) as well as the effects of distribution environments such as storage temperature on the dynamics of the fruit quality during transportation (Fukuda et al., 2014). Process-based fruit quality prediction models are being tested for predicting the quality changes of mango fruits according to their physiological activities such as postharvest ripening and respiration. By integrating these models, a comprehensive fruit quality prediction system will be established, which can contribute to improved production systems for high quality fresh mango fruit and advanced distribution systems allowing for a long supply chain from Thailand to Japan with minimum quality loss. This special issue was organized after the special session “Sensors and Monitoring in Environmental and Agricultural Sciences” at the 9th International Conference on Intelligent Robotics and Applications (ICIRA2016). The opening paper, “Random forests as a tool for analyzing partial drought stress based on CO2 concentrations in the rootzone of longan trees” (Fukuda et al., 2018) reports how an advanced machine learning, namely random forests (Breiman, 2001), can be applied for estimating CO2 concentrations in the rootzone based on ambient climate data and soil moisture content under different irrigation regimes (i.e., full irrigation and partial root-zone drying). The model performance was found to be moderate. Response curves and variable importance computed from random forests were used as a tool of knowledge extraction. Variable importance indicated the significance of soil moisture content for the CO2 estimation in the rootzone, while response curves indicated ecophysiological responses of longan trees under a given condition and irrigation treatment. Such an approach can be used as a first examination to find an input-output relationship in observed data and the interpretation","PeriodicalId":11762,"journal":{"name":"Environmental Control in Biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Control in Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2525/ECB.56.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

able development goals (SDGs) of the United Nations (2016). These comprehensive goals cover all possible topics toward sustainable development. Agriculture is a human activity which heavily relies on natural resources for food production, and thus directly and indirectly impacts natural systems. Considering the balance between environment and natural resources management including agriculture, the water-energy-food (WEF) nexus (Flammini et al., 2014) has emerged as a key approach towards SDGs. Self-evidently, human beings depend on WEF, and conserving them under the pressure of population growth and climate change is an important challenge. Worldwide, agricultural water use accounts for 70% of total water use, and more than 90% in the least developed countries (WWAP, 2012). It is expected to increase because of population growth and changing food demands. Water use for agriculture is in competition with domestic and industrial sectors. Climate change may further foster such conflicts, resulting in overexploitation of both surface water and groundwater resources. Therefore, agricultural water use and distribution need to be efficiently managed considering local conditions. Energy is another important factor for agriculture, covering the entire chain from production, harvesting, processing, distribution and consumption. Pressurized irrigation systems (e.g. drip and sprinkler irrigation) are important tools for water saving and increasing production but consumes significant amounts of energy. Fuels are used for processing, storage and transportation of fresh agricultural products to achieve a long shelf life during a supply chain. Advanced storage and transportation allow for supplying quality products to distant markets. A comprehensive research framework, adopting the WEF nexus approach, is needed for research and developed for an improved food system (e.g., from field to fork) from a viewpoint of sustainable development. In 2013, the research consortium established a project aiming at the development of intensive production system with improved distribution systems of fresh mango fruit (Mangifera indica L.) between Thailand and Japan. To this end, various kinds of data have been collected continuously from farm to table using Information and Communications Technologies (ICTs) such as advanced sensors and semi-real-time field monitoring devices. In addition, laboratory experiments were conducted to characterize ecophysiological traits (e.g., respiration rates and climacteric ripening process) of fresh mango fruit. We have applied machine learning methods in order to evaluate the effects of production environments including irrigation regimes on the yield and quality of fresh mango fruit (Fukuda et al., 2013) as well as the effects of distribution environments such as storage temperature on the dynamics of the fruit quality during transportation (Fukuda et al., 2014). Process-based fruit quality prediction models are being tested for predicting the quality changes of mango fruits according to their physiological activities such as postharvest ripening and respiration. By integrating these models, a comprehensive fruit quality prediction system will be established, which can contribute to improved production systems for high quality fresh mango fruit and advanced distribution systems allowing for a long supply chain from Thailand to Japan with minimum quality loss. This special issue was organized after the special session “Sensors and Monitoring in Environmental and Agricultural Sciences” at the 9th International Conference on Intelligent Robotics and Applications (ICIRA2016). The opening paper, “Random forests as a tool for analyzing partial drought stress based on CO2 concentrations in the rootzone of longan trees” (Fukuda et al., 2018) reports how an advanced machine learning, namely random forests (Breiman, 2001), can be applied for estimating CO2 concentrations in the rootzone based on ambient climate data and soil moisture content under different irrigation regimes (i.e., full irrigation and partial root-zone drying). The model performance was found to be moderate. Response curves and variable importance computed from random forests were used as a tool of knowledge extraction. Variable importance indicated the significance of soil moisture content for the CO2 estimation in the rootzone, while response curves indicated ecophysiological responses of longan trees under a given condition and irrigation treatment. Such an approach can be used as a first examination to find an input-output relationship in observed data and the interpretation
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种热带水果生产和销售的传感器与监测
联合国可持续发展目标(sdg)(2016年)。这些综合目标涵盖了可持续发展的所有可能主题。农业是一项严重依赖自然资源进行粮食生产的人类活动,因此直接和间接地影响着自然系统。考虑到环境和自然资源管理(包括农业)之间的平衡,水-能源-食物(WEF)关系(Flammini et al., 2014)已成为实现可持续发展目标的关键途径。不言而喻,人类依赖世界经济论坛,在人口增长和气候变化的压力下保护它们是一项重要挑战。在世界范围内,农业用水占总用水量的70%,在最不发达国家占90%以上(WWAP, 2012)。由于人口增长和粮食需求的变化,预计这一数字还会增加。农业用水与家庭和工业部门存在竞争关系。气候变化可能进一步助长这种冲突,导致对地表水和地下水资源的过度开采。因此,农业用水和分配需要因地制宜地进行有效管理。能源是农业的另一个重要因素,涵盖了从生产、收获、加工、分配到消费的整个链条。加压灌溉系统(如滴灌和喷灌)是节水和增产的重要工具,但也消耗大量能源。燃料用于新鲜农产品的加工、储存和运输,以在供应链中实现较长的保质期。先进的储存和运输可以为遥远的市场提供高质量的产品。从可持续发展的观点出发,需要一个采用世界经济论坛联系方法的综合研究框架来研究和开发一个改进的粮食系统(例如,从田地到餐桌)。2013年,该研究联盟建立了一个项目,旨在开发集约化生产系统,改善泰国和日本之间新鲜芒果(Mangifera indica L.)的分销系统。为此,利用先进的传感器和半实时现场监测设备等信息和通信技术(ict),从农场到餐桌,不断收集各种数据。此外,还进行了室内实验,以表征新鲜芒果果实的生态生理特征(如呼吸速率和更年期成熟过程)。我们已经应用了机器学习方法来评估生产环境的影响,包括灌溉制度对新鲜芒果果实的产量和质量的影响(Fukuda et al., 2013),以及运输过程中储存温度等分配环境对水果质量动态的影响(Fukuda et al., 2014)。基于过程的果实品质预测模型正被用于根据芒果果实采后成熟和呼吸等生理活动预测其品质变化。通过整合这些模型,将建立一个全面的水果质量预测系统,这将有助于改善高质量新鲜芒果的生产系统和先进的分销系统,从而实现从泰国到日本的长供应链,最大限度地减少质量损失。本特刊是在第九届智能机器人与应用国际会议(ICIRA2016)“环境与农业科学中的传感器与监测”特别会议之后组织的。论文“随机森林作为基于龙眼树根区CO2浓度分析部分干旱胁迫的工具”(Fukuda et al., 2018)报告了如何应用先进的机器学习,即随机森林(Breiman, 2001),根据不同灌溉制度(即完全灌溉和部分根区干燥)下的环境气候数据和土壤水分含量来估计根区CO2浓度。发现模型的性能是中等的。利用随机森林计算的响应曲线和变量重要性作为知识提取的工具。变量重要度表示土壤含水量对根区CO2估算的重要意义,响应曲线表示龙眼树在一定条件和灌溉处理下的生态生理响应。这种方法可以作为在观测数据和解释中找到输入-输出关系的第一次检查
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Environmental Control in Biology
Environmental Control in Biology Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
2.00
自引率
0.00%
发文量
25
期刊最新文献
Conjugation of Glucaric Acid in Comparison to Quinic Acid by Caffeic Acid Allows for Enhanced Metabolite Diversification in Bush Tea (<i>Athrixia phylicoides</i> DC.) Extracts Post UV Light Exposure Effect of Citric Acid on the Organogenesis of <i>Cymbidium floribundum</i> Development of a Male-Sterile Line of Eggplant Utilizing the Cytoplasm of <i>Solanum aethiopicum</i> Gilo Group Continuous Measurement of Greenhouse Ventilation Rate in Summer and Autumn via Heat and Water Vapor Balance Methods Postharvest Shelf-life Extension of Button Mushroom (Agaricus bisporus L.) by Aloe vera Gel Coating Enriched with Basil Essential Oil
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1