摘要
针对传统食用菌栽培依赖人工经验、环境控制粗放、病虫害防控滞后等问题,设计了一种基于多源感知与智能决策的食用菌工厂化生产全流程智能控制系统。该系统深度融合了多光谱成像、机器视觉、环境传感、物联网与人工智能技术,可对食用菌生长阶段进行精准识别与参数优化,实现生长环境的精准、快速调节与闭环控制,显著提升病害防控能力与产品质量稳定性。结果表明,该系统使食用菌产量提高了20.7%,生长周期变异系数降低了64.5%,单位产量能耗降低了24.4%,人工干预频次减少了77.7%,采摘识别准确率>98%,大幅减少了资源浪费,降低了人工干预强度,为食用菌工厂化、智能化、标准化生产提供了可靠的技术支撑。
To address issues such as reliance on manual experience,coarse environmental control,and delayed pest and disease prevention in traditional edible fungi cultivation,an intelligent control system for the whole process of industrialized edible fungi production based on multi-source sensing and intelligent decision-making has been designed.This system deeply integrates multispectral imaging,machine vision,environmental sensing,Internet of Things,and artificial intelligence technologies,enabling precise identification of edible fungi growth stages and parameter optimization.It achieves precise,rapid adjustment and closed-loop control of the growth environment,significantly enhancing disease prevention capabilities and product quality stability.The results indicate that the system has increased edible fungi yield by 20.7%,reduced the coefficient of variation in the growth cycle by 64.5%,decreased energy consumption per unit yield by 24.4%,and minimized manual intervention frequency by 77.7%.The picking identification accuracy exceeds 98%.These improvements substantially reduce resource waste and lower the intensity of manual intervention,providing reliable technical support for the industrialized,intelligent,and standardized production of edible fungi.
作者
卜钧琰
刘涛
BU Junyan;LIU Tao(College of Horticulture and Landscape Architecture,Yangzhou University,Yangzhou,Jiangsu 225009,China;Taizhou Technician College,Taizhou,Jiangsu 225300,China)
出处
《自动化应用》
2025年第15期27-31,36,共6页
Automation Application
关键词
食用菌
工厂化生产
全流程
智能控制系统
多光谱成像
机器视觉
环境调控
预测模型
edible fungi
industrialized production
whole process
intelligent control system
multispectral imaging
machine vision
environmental regulation
predictive model
