中国农业农村信息网_AI种稻 永丰村 300亩稻田“算”出丰收

集。
换而言之,永丰村人早就入局了智慧农业:先修良田、配农机、铺好感知网络、跑通数字化台账,再往上叠加AI决策层。村干部、种植户、农技员早就习惯用手机看田块数据、远程调度,“东坡巡田”小程序有现成的用户基
,农户接受门槛低,天然适合做AI种稻试点。
也正因此,马均团队选择先控制成本、小范围验证,目前仅完成300亩试点。杨志远透露,专用AI模型“高质量数据‘喂’得越多,模型迭代进化越快,用户用起来越精准”。
“我们的


本文转载自:中国农业农村信息网
原文链接:http://www.agri.cn/zx/xxlb/sc/202609/t20260911_8870726.htm

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:14

一部手机管农田,科技创新守护“耕地大熊猫”——中国环境网

5%、增产5.48%—14.2%,技术已推广至29个北大荒农场和7个市县合作社。
在辽河源生态农业研究站,科研人员依托等高种植、生物埂、生态缓冲带、粮豆轮作和有机肥还田等技术,搭建起立体水土防护体系。经过治理,跑水、跑土、
关任务、7个示范区相关技术的大模型,农事决策准确率达95%以上。面向农户“不会用、不敢用”的痛点,普惠式“AI+农业”App“佳家农”让一部手机成为新农具:零成本服务佳木斯地区超4.9万农户,覆盖耕地超100万亩;经试点和


本文转载自:中国环境网
原文链接:https://www.cenews.com.cn/news.html?aid=1816221

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:13

(四川农村日报)永丰村AI智慧稻田开镰-四川农业大学新闻网

谷,平均产量为858.8公斤/亩,比对照组增产 18.1%。”9 月 14日,在眉山市东坡区太和镇永丰村,首次应用水稻专属AI大模型管理的300亩试点田迎来测产收割,收割机“轰隆隆”碾过金色稻浪,一串串测产数据显示:不同水稻品种
种植模式下的稻田,均喜迎丰收。
现场欢呼声中,试点田的种植负责人赵友勇反而显得平静:“今年种植过程和收成,都经AI算过,心中有数。”
一份“算”出来的丰收
原来,这300亩试点田,是四川省水稻新品种新技术中试研


本文转载自:四川农业大学
原文链接:https://news.sicau.edu.cn/info/1133/115667.htm

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:13

“供销优农”水稻全产业链智能体正式发布—新闻—科学网

研究中心联合肇庆市供销合作联社共同研发的“供销优农”水稻全产业链智能体(Agent)正式发布。
“一呼百应·AI农医生”100站启动现场。华农供图,下同
记者了解到,该智能体聚焦水稻生产全过程智能化服务,是华农推动人
融合创新,服务地方产业发展的又一实践成果。
“供销优农”水稻全产业链智能体围绕水稻生产全过程需求,贯通种植决策、病虫害识别、农事管理、供需对接等关键环节,构建“问诊-开方-配药-作业”的数智化服务闭环。农户


本文转载自:科学网
原文链接:https://news.sciencenet.cn/htmlnews/2026/10/573213.shtm

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:12

Agri-SCHOLAR: Simulation-Grounded In-Season Rolling Advisories for Agricultural Crops Using LLM-Bounded Optimization

region’s standard packages of practice and satisfactorily addresses the limitations of existing agricultural advisories.
Keywords Personalized in-season advisories · Multi-agent LLM systems · Agricultural advisory · Crop simulation · Simulation-grounded reasoning · Sustainable agriculture · AI for social good
1 Introduction
Agricultural advisories in much of the developing world are still produced by small teams of agronomists who issue broad guidance across large, dispersed regions. This approach does not scale, as even farms in the same advisory zone differ in soil, cultivar, sowing


本文转载自:arXiv
原文链接:https://arxiv.org/pdf/2610.31003v1

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:12

[2610.31003] Agri-SCHOLAR: Simulation-Grounded In-Season Rolling Advisories for Agricultural Crops Using LLM-Bounded Optimization

ainst a multi-objective reward spanning yield, resource utilization, and economic feasibility. We conduct a detailed 11-year analysis of the maize crop in two selected locations of South Asia and show that Agri-SCHOLAR consistently outperforms the region’s standard packages of practice and satisfactorily addresses the limitations of existing agricultural advisories.
Subjects: Artificial Intelligence (cs.AI) ; Multiagent Systems (cs.MA)
Cite as: arXiv:2610.31003 [cs.AI]
(or arXiv:2610.31003v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2610.31003
From: Geetha Charan [view email]


本文转载自:arXiv
原文链接:https://arxiv.org/abs/2610.31003

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:11

Frontiers | Perception and adoption by cassava farmers of the PlantVillage Nuru application disseminated in the agricultural environment of Côte d’Ivoire: a case study in the departments of Dabou, Bouaké, and Man

atform and remain connected with other members of the community (agricultural experts, farmers, seed suppliers, etc.). The farmer is then presented with four main options. The first one (Proceed) enables him to analyze deeply the phytosanitary status of one plant. In this case, he is invited by the AI to expose six different leaves of the cassava plant (3 on the upper part and 3 on the lower part) to the smartphone’s camera, to obtain in vocal and written form, on the phone’s screen, the name of the disease concerned. The second option (scout) allows the farmer to inspect the field by diag


本文转载自:Frontiers
原文链接:https://www.frontiersin.org/journals/agronomy/articles/10.3389/fagro.2024.1433204/full

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:10

CSIRO, MLA and Google launch global AI challenge to transform pasture management – CSIRO

CSIRO, MLA and Google launch global AI challenge to transform pasture management
The Kaggle-hosted challenge aims to create AI models that support farmers to make smarter grazing decisions to improve productivity and environmental sustainability.
29 October 2025 News Release
Australia’s national science agency, CSIRO, in partnership with Meat & Livestock Australia (MLA) and Google Australia, has launched a global competition with a US$75,000 prize pool to advance the use of artificial intelligence (AI) in agriculture.
Hosted on
Kaggle, the challenge
seeks to improve the accuracy and efficien


本文转载自:CSIRO
原文链接:https://www.csiro.au/en/news/All/News/2025/October/Kaggle-competition

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:08

三农微评: AI“开药方”?农田经不起试错!

三农微评: AI“开药方”?农田经不起试错!
农民日报 | 2026-08-08 09:44
近日,安徽滁州的一位农户按照AI(人工智能)生成的飞防方案,为150亩芝麻施药,不料一夜之间芝麻苗全部枯萎。涉事平台回应称,其回答是根据网络公开信息整合生成的。该农户认为AI生成方案时未明确提醒,由此造成了无法挽回的损失。
一份看似专业的施药方案,暴露出AI进田仍有短板:即使能答对几次,也不等于次次靠谱。AI算得出用药量,却很难读懂千差万别的真实农情。


本文转载自:贵州网络广播电视台
原文链接:https://gzstv.com/a/81fc74e5927d40e59100f70e4d07a2ba

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:08

【言直在线】照着AI种地,150亩芝麻一夜绝收,这账该算谁头上?

【言直在线】照着AI种地,150亩芝麻一夜绝收,这账该算谁头上?
发布时间:2026年08月08日 09:36:00 来源:云南网
开栏的话
舆论喧嚣,我们笃定发声。即日起云南网推出全新视频评论栏目【言直在线】。
言直,是我们的底色,有话直说、敢讲真话、深挖真相;言值,是我们的标尺,拒绝浅层吐槽,每一次发声必有洞察、有干货、有分量。我们始终在场、在线、在思辨,以理性审视现实,以正直传递温度。
言之有物,直抵人心——【言直在线】,期待


本文转载自:云南网
原文链接:https://m.yunnan.cn/system/2026/08/08/034115337.shtml

本文由 XZ导师app 自动发布 | 发布时间:2026/10/24 13:28:07