摘要
为实现作物生长信息的低成本、实时、无损监测,本研究基于光谱分析技术,选择395 nm和800 nm 2个波段,根据光学系统原理和小型化需求,进行基于智能移动设备的低功耗微型作物光谱反射率测量仪研发,包括封装壳体、光学系统和硬件电路设计及控制系统App开发;并使用积分球和ASD Fieldspec 4 Hi-Res地物光谱仪对测量仪4个通道(395 nm和800 nm太阳光接收通道和作物反射光接收通道)的测量值进行标定,并以反射率为20%、40%、60%、100%的4块标准灰度板为测量对象检验测量仪的准确性。结果表明:4个通道标定方程的决定系数均在0.9980以上,395 nm和800 nm反射率的均方根误差分别为1.46%和1.07%,平均绝对误差分别为1.17%和0.82%;4块标准反射率灰度板在395 nm和800 nm 2个波段测得反射率的相对误差分别小于2.0%和3.6%,变异系数分别在1.36%~4.17%和0.78%~2.36%。该测量仪体积32 cm^(3),质量仅20 g,且具有低成本、高精度、易操作、可升级等特性,可实现基于智能移动设备的作物生长实时监测。
In order to achieve low-cost,real-time and non-destructive monitoring of crop growth information,based on spectral analysis technology,this study selected two bands,395 nm and 800 nm,and carried out the research and development of a low-power miniature crop spectral reflectance measuring instrument based on a smart mobile device according to the principle of the optical system and miniaturisation requirements,including the package housing,optical system and hardware circuit design and control system App development.Measurements of the four channels(395 nm and 800 nm sunlight receiving channels and crop reflected light receiving channels)of the meter were calibrated using an integrating sphere and a spectrometer(ASD),and the accuracy of the meter was checked using four grey scale panels with standard reflectance(20%,40%,60%,100%).The results showed that the coefficients of determination of the calibration equations of the four channels were above 0.9980,the root mean square errors of 395 nm and 800 nm reflectance were 1.46%and 1.07%,and the average absolute errors were 1.17%and 0.82%,respectively.The relative errors of the reflectance measured by the four standard reflectance greyscale panels in the 395 nm and 800 nm bands were less than 2.0%and 3.6%,respectively,and the coefficients of variation were in the ranges of 1.36%-4.17%and 0.78%-2.36%,respectively.With a volume of 32 cm^(3) and a weight of only 20 g,the instrument is low-cost,high-precision,easy-to-operate,and scalable,which can realize real-time crop growth monitoring based on smart mobile devices.
作者
吴金恺
刘乃森
曹静
胡佳楠
潘嫄嫄
毕然
郭靖宇
王许淇
霍丹琪
张文宇
WU Jin-kai;LIU Nai-sen;CAO Jing;HU Jia-nan;PAN Yuan-yuan;BI Ran;GUO Jing-yu;WANG Xu-qi;HUO Dan-qi;ZHANG Wen-yu(School of Agricultural Engineering,Jiangsu University,Zhenjiang 212013,China;Jiangsu Academy of Agricultural Sciences Wuxi Branch,Wuxi 214174,China;Huaiyin Normal University/Collaborative Innovation Center of Regional Modern Agriculture&Environmental Protection Co-constructed by the Province and Ministry/Jiangsu Key Laboratory for Eco-Agricultural Biotechnology around Hongze Lake/Jiangsu Engineering Research Center for Cyanophytes Forecast and Ecological Restoration of Hongze Lake,Huaian 223300,China)
出处
《江苏农业学报》
CSCD
北大核心
2024年第3期469-477,共9页
Jiangsu Journal of Agricultural Sciences
基金
国家重点研发计划项目(2022YFD2001005、2022YFD2001001)
江苏省重点研发计划项目(BE2023323)
江苏省农业科技自主创新基金项目[CX(21)2008]
无锡市财政项目(33212303)。
关键词
生长监测
智能测量仪
微型化
智能手机
光谱反射率
growth monitoring
smart meter
miniaturization
smart phone
spectral reflectance