摘要
农作物的苗期生长是一个复杂的生理生化及代谢过程,苗期的生长发育直接影响到作物的生物产量、经济产量、营养品质及其安全性。农作物苗期长势监测对于作物肥水管理、病虫害防治具有指导作用,是精细农业和数字农业的关键技术之一。该文从农作物苗期生长形态检测、营养组分检测和病虫害诊断3个方面,详细阐述了各种无损检测技术,如机器视觉技术、激光漫反射技术、荧光测量技术和反射光谱分析技术等在作物苗期长势监测中的应用进展。国内外学者对上述技术进行了较深入的理论方法研究,部分技术已在实践中得到广泛应用,但目前作物无损检测技术大多强调单一信息的获取及分析,随着数字农业和智慧农业的发展,未来将更加强调多源、多尺度数据的获取及形态、养分、病虫害综合信息的提取。作物苗期长势的监测数据将与精准农业的联系更加紧密,为农事操作提供传感信息,形成智能化的农业施工、调优栽培与管理决策系统。
Crop seedling growth is a complex physiological and biochemical metabolic process,seedling growth have direct influence on crop biomass production,economic output,nutritional quality,and safety.The monitoring of growing status in crop seedlings have guidance for crop fertilizer,water management,pest and disease control,therefore it′s the key point of precision agriculture and digital agriculture.In this study,the progress of growing status monitoring technologies in crop seedlings were deeply reviewed from three aspects,which included crop morphology,nutrimental component testing,pest and disease diagnosis.The applications of various non-destructive monitoring technologies for crop seedling,such as machine vision,transmission optical detection,reflectance spectroscopy,and fluorescence measurement,were described in details.Furthermore,its current problems and developments in future were also discussed.Many experts from broad and abroad who study the non-destructive testing techniques for crop had more in-depth research and application,but currently the main emphasis of a single information access and analysis,the future will be more emphasis on multi-source,multi-scale data acquisition and morphology,nutrients,integrated pest access to information,information integration and comprehensive evaluation of crop growing seedlings will be research priorities.Seedling growing crop monitoring and precision agriculture data will be more linked to the farming operation to provide sensor information,the formation of intelligent agricultural construction,tuning,cultivation,management decision-making system.
出处
《农业工程》
2011年第4期19-25,共7页
AGRICULTURAL ENGINEERING
基金
北京市优秀人才培养资助项目(项目编号:2011D002020000008)
北京市农林科学院科技创新能力建设专项(项目编号:KJCX201104010)
北京市农林科学院青年科研基金资助项目(项目编号:QN201107)
