Data for Bio-Digital Convergence and Sustainable Artificial Intelligence: Evaluating the Tools of the Jach'a Qh’anax Model in the Andean-Amazonian and Mesoamerican Bioeconomy

This dataset and its complementary software tools form the empirical validation framework of the Jach'a Qh'anax Model Ecosystem. This project explores bio-digital convergence and the application of sustainable Artificial Intelligence (AI) within the bioeconomy of the Andean-Amazonian and Mesoamerican regions, specifically covering Bolivia, Mexico, Guatemala, Honduras, and El Salvador. The primary objective of the ecosystem is to mitigate technical information asymmetries and climate risks faced by traditional rural agricultural producers through decentralized climate sensors and mobile tools, while actively integrating indigenous and ancestral knowledge. The collected data evaluates technological adoption, algorithmic predictive accuracy, the substitution of traditional chemical inputs for bioeconomic practices, and the direct impact on household income stability and food security across 200 multi-country participants during the 2026 agricultural cycle.本数据集及其配套软件工具，构成了Jach'a Qh'anax模型生态系统（Jach'a Qh'anax Model Ecosystem）的实证验证框架。本项目聚焦安第斯-亚马逊与中美洲区域的生物经济领域，探索生物-数字融合技术与可持续人工智能（Artificial Intelligence，AI）的应用落地，覆盖国家具体包括玻利维亚、墨西哥、危地马拉、洪都拉斯以及萨尔瓦多。该生态系统的核心目标，是通过分布式气候传感器与移动应用工具，缓解传统农村农业生产者面临的技术信息不对称与气候风险问题，同时积极融合本土与原住民传统知识。本次采集的数据将针对2026年农业季的200名跨国参与主体，评估技术采用情况、算法预测精度、以生物经济实践替代传统化学投入品的效果，以及该方案对家庭收入稳定性与粮食安全的直接影响。