Tricot 方法:公民科学支持下的分散式农场测试敏捷框架。回顾

IF 6.4 1区 农林科学 Q1 AGRONOMY
Kauê de Sousa, Jacob van Etten, Rhys Manners, Erna Abidin, Rekiya O. Abdulmalik, Bello Abolore, Kwabena Acheremu, Stephen Angudubo, Amilcar Aguilar, Elizabeth Arnaud, Adventina Babu, Mirna Barrios, Grecia Benavente, Ousmane Boukar, Jill E. Cairns, Edward Carey, Happy Daudi, Maryam Dawud, Gospel Edughaen, James Ellison, Williams Esuma, Sanusi Gaya Mohammed, Jeske van de Gevel, Marvin Gomez, Joost van Heerwaarden, Paula Iragaba, Edith Kadege, Teshale M. Assefa, Sylvia Kalemera, Fadhili Salum Kasubiri, Robert Kawuki, Yosef Gebrehawaryat Kidane, Michael Kilango, Heneriko Kulembeka, Adofo Kwadwo, Brandon Madriz, Ester Masumba, Julius Mbiu, Thiago Mendes, Anna Müller, Mukani Moyo, Kiddo Mtunda, Tawanda Muzhingi, Dean Muungani, Emmanuel T. Mwenda, Ganga Rao V. P. R. Nadigatla, Ann Ritah Nanyonjo, Sognigbé N’Danikou, Athanase Nduwumuremyi, Jean Claude Nshimiyimana, Ephraim Nuwamanya, Hyacinthe Nyirahabimana, Martina Occelli, Olamide Olaosebikan, Patrick Obia Ongom, Berta Ortiz-Crespo, Richard Oteng-Fripong, Alfred Ozimati, Durodola Owoade, Carlos F. Quiros, Juan Carlos Rosas, Placide Rukundo, Pieter Rutsaert, Milindi Sibomana, Neeraj Sharma, Nestory Shida, Jonathan Steinke, Reuben Ssali, Jose Gabriel Suchini, Béla Teeken, Theophilus Kwabla Tengey, Hale Ann Tufan, Silver Tumwegamire, Elyse Tuyishime, Jacob Ulzen, Muhammad Lawan Umar, Samuel Onwuka, Tessy Ugo Madu, Rachel C. Voss, Mary Yeye, Mainassara Zaman-Allah
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引用次数: 0

摘要

使作物品种与其目标使用环境和用户偏好相匹配,是许多服务于小农农业的植物育种计划所面临的挑战。在过去的四十年中,国际农业研究磋商组织和其他研究团队提出了许多参与式方法,试图通过具有较高外部有效性的试验,了解农民的优先事项/偏好以及作物品种在代表性种植环境中的田间表现。然而,这些方法都没有克服可扩展性、数据有效性和可靠性以及难以捕捉社会经济和环境异质性等挑战。在这些尝试的基础上,我们开发了一种新的数据生成方法,称为三元技术选择比较(Tricot)。Tricot 是一种由众包公民科学支持的分散式实验方法。在这篇文章中,我们将通过自己的研究成果和对成功应用 Tricot 方法的文献的回顾,回顾 Tricot 方法的发展、验证和演变。最初的研究结果表明,由农民主导的三坐标综合评估所包含的信息具有充分的有效性,并且可以通过大样本来实现可靠性。成本低于当前的参与式方法。将 Tricot 方法推广到大型农场测试网络中,成功登记了作物品种在代表性生长环境中表现的特定气候影响。最近,Tricot 在植物育种网络中的应用与决策相关,(i) 促进了植物育种品系的发展,认识到了社会经济的异质性,(ii) 确定了消费者的偏好和市场需求,产生了可供选择的育种设计优先事项。我们回顾了从 Tricot 应用中汲取的经验教训,这些应用促成了大规模的推广工作,应能加强作物改良的决策制定,并增加改良品种在小农农业中的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The tricot approach: an agile framework for decentralized on-farm testing supported by citizen science. A retrospective

The tricot approach: an agile framework for decentralized on-farm testing supported by citizen science. A retrospective

Matching crop varieties to their target use context and user preferences is a challenge faced by many plant breeding programs serving smallholder agriculture. Numerous participatory approaches proposed by CGIAR and other research teams over the last four decades have attempted to capture farmers’ priorities/preferences and crop variety field performance in representative growing environments through experimental trials with higher external validity. Yet none have overcome the challenges of scalability, data validity and reliability, and difficulties in capturing socio-economic and environmental heterogeneity. Building on the strengths of these attempts, we developed a new data-generation approach, called triadic comparison of technology options (tricot). Tricot is a decentralized experimental approach supported by crowdsourced citizen science. In this article, we review the development, validation, and evolution of the tricot approach, through our own research results and reviewing the literature in which tricot approaches have been successfully applied. The first results indicated that tricot-aggregated farmer-led assessments contained information with adequate validity and that reliability could be achieved with a large sample. Costs were lower than current participatory approaches. Scaling the tricot approach into a large on-farm testing network successfully registered specific climatic effects of crop variety performance in representative growing environments. Tricot’s recent application in plant breeding networks in relation to decision-making has (i) advanced plant breeding lines recognizing socio-economic heterogeneity, and (ii) identified consumers’ preferences and market demands, generating alternative breeding design priorities. We review lessons learned from tricot applications that have enabled a large scaling effort, which should lead to stronger decision-making in crop improvement and increased use of improved varieties in smallholder agriculture.

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来源期刊
Agronomy for Sustainable Development
Agronomy for Sustainable Development 农林科学-农艺学
CiteScore
10.70
自引率
8.20%
发文量
108
审稿时长
3 months
期刊介绍: Agronomy for Sustainable Development (ASD) is a peer-reviewed scientific journal of international scope, dedicated to publishing original research articles, review articles, and meta-analyses aimed at improving sustainability in agricultural and food systems. The journal serves as a bridge between agronomy, cropping, and farming system research and various other disciplines including ecology, genetics, economics, and social sciences. ASD encourages studies in agroecology, participatory research, and interdisciplinary approaches, with a focus on systems thinking applied at different scales from field to global levels. Research articles published in ASD should present significant scientific advancements compared to existing knowledge, within an international context. Review articles should critically evaluate emerging topics, and opinion papers may also be submitted as reviews. Meta-analysis articles should provide clear contributions to resolving widely debated scientific questions.
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