测控技术在温室环境因子控制中的应用

自动化技术、现代信息和测控技术在温室环境控制中的应用,使智能化温室在世界范围内引起了越来越广泛的关注,并在全世界范围内开始普及。本文列出了应用于温室环境控制的测控仪器和技术,由此可以看出智能化温室给设施农业的发展带来的深远意义。     

应用计算机技术的车用传感器检测系统设计

叙述了由计算机控制的车辆传感器检测系统整体设计思想,以及软、硬件和机械部件的实施方案。该系统用于车辆传感器出厂前的各项性能检验,能对车用传感器生产质量的保证提供有效的手段。     

基于宽度卷积神经网络的异常农情数据检测方法

【目的】为准确有效地检测农业物联网的感知数据异常,提出了基于宽度卷积神经网络的异常农情数据检测方法,为实现农业物联网数据高质量感知提供参考。【方法】首先将标准化后的农情数据编码为极坐标表示,通过滑动窗口机制划分子集,接着将每个子集数据重构为矩阵,最后设计并训练宽度卷积神经网络模型用于异常检测,采用养殖场环境监测数据进行试验。【结果】构建的滑动窗口机制可提升异常数据检测能力,缩短检测时间。所设计的宽度卷积神经网络对空气温湿度、土壤温湿度等数据中所存在的异常检测准确率均超过97.5%,优于SVM、RF和CNN模型1.69%、2.76%和3.05%;F1值均在0.985以上,优于SVM、RF和CNN模型0.009 3、0.014 9和0.016 3;且在处理波动性较大的空气、土壤温湿度数据时性能优势更为明显,准确率和F1值分别提高了3.61%～5.98%和0.018 8～0.031 0。此外,该方法模型检测耗时较短,仅为传统CNN模型的1/6～1/7,并且比SVM和RF模型使用更少的超参数。【结论】所建立的数据编码、子集划分和重构方法与宽度卷积神经网络模型对异常农情数据有较好的检测效果。     

无线传感器网络在林火监测中应用

将无线传感器网络结合加拿大林火天气指数（ FWI）系统对森林火灾进行预测和实时监测。使用大范围布置的温湿度传感器结合自动防火气象站组成无线传感器网络,对广大林区作细粒度的数据采集,进而准确计算FWI系统的6个指数,对火灾发生的潜在风险以及火灾的强度和规模做出预测和评估,并依据细小可燃物湿度码（ FFMC）调整传感器节点的数据采集频率,对林火进行实时监测和识别。测试结果表明本系统可以有效地节约能耗,缩短林火的发现时间。     

基于单片机的大棚温湿度检测系统的应用

该系统是一个专门为温室大棚温湿度控制而设计的智能系统。通过对系统的硬件部分和软件部分设计来达到监控要求。硬件部分实现了对温湿度传感器模块、A/D转换模块、显示模块、控制模块的设计;软件部分主要根据系统的设计思想设计出了主程序和子程序流程图,并通过汇编语言和C语言实现。通过实践证明,该系统具有性能好、操作方便等优点,实现了对温湿度的显示、调节、自动控制和手动控制。     

基于单片机控制的温室热水采暖系统设计

针对目前温室中人工控制热水采暖面临的问题,设计开发了基于单片机测控温室内温度的热水采暖系统。该系统以单片机AT89S52为核心,利用温度传感器DS18820、D／A转换器TLC5615、电动调节阀等实现对温室内多点位温度的测控。试验结果表明,该系统操控简单,能够精准调控温室内温度,并具有较高的稳定性。     

Design of a hyperspectral nitrogen sensing system for orange leaves

The orange (Citrus sinensis) is one of the most important agricultural crops in Florida. Heavy reliance on agricultural chemicals and low fertilizer use efficiencies in citrus production have raised environmental and economic concerns. In this study, a nitrogen sensor was developed to predict nitrogen concentrations in orange leaves. Four design criteria were chosen to maximize the sensing efficiency and reliability. They were: (1) coverage of the spectral N sensing range, (2) no moving parts, (3) single leaf detection, and (4) diffuse reflectance measurement. Based on chlorophyll and protein spectral absorption bands, the sensor's wavelength ranges were chosen to be 620–950 nm and 1400–2500 nm. A reflectance housing was designed to block environmental noise and to ensure single leaf measurement. A halogen light source, two detector arrays, two linear variable filters, and data acquisition cards with 16-bit analog-to-digital converters were used to collect data. The designed N sensor had a spectral resolution less than 30 nm. Test results showed that the nitrogen sensor had good linearity (r > 0.99) and stability. With averaged signal-to-noise ratio (SNR) of 299, the system was able to predict N content with a root mean square difference (RMSD) of l.69 g kg⁻¹ for the validation data set. Using the N sensor, unknown leaf samples could be classified into low, medium and high N levels with 70% accuracy.     

Pilot study to monitor body temperature of dairy cows with a rumen bolus

A bolus containing a mote (temperature sensor, processor and radio) was placed in the rumen of a fistulated cow to monitor body temperature. Rumen temperature was measured every minute and stored in the internal buffer of the mote. The measured temperature was also transmitted to a base station by the mote every minute. A relay mote mounted on the cows’ left front leg assisted transmission of the information from rumen to the base station. Cow behaviour affected the success rate of data transmission. The base station received more than 50% of the transmitted data when the cow was standing. Success rate was lower than 40% when the cow was lying down. Rumen temperature varied diurnally with night-time temperatures higher than day-time temperatures. Drinking events resulted in distinct decreases of the rumen temperature. It is concluded that for the application of internal sensor motes wireless communication through the body and living environment of the animal works but improvements are possible. Research should also focus on the interpretation of sensor data on mote level for optimizing data recording frequency and transmission of data to dairy management practice.     

Field performance of three real-time moisture sensors in sandy loam and clay loam soils

The study was conducted to evaluate HydraProbe (HyP), Campbell Time Domain Reflectometry (TDR) and Watermarks (WM) moisture sensors for their ability to estimate water content based on calibrated neutron probe (NP) measurements. The three sensors were in-situ tested under natural weather conditions over a 3-yr period in a sandy loam and clay loam soils planted to grass. The HyP, TDR and WM sensors were evaluated for their ability to estimate soil moisture contents by comparing their outputs with those of NP measurements. Results showed that HyP, TDR and WM provided different estimates of soil moisture contents in both soils. Nevertheless, our work suggests that soil moisture sensors including those used in this study can be made suitable for irrigation scheduling without in-situ calibrations by simply setting the upper and lower irrigation trigger limits for each sensor and each soil type. The upper trigger point occurs directly after irrigation event (near field capacity) and the lower trigger point is based on about 50% depletion of available water in the crop rootzone and is occurs prior to irrigation refill. This approach can significantly help irrigators to achieve their irrigation scheduling and productivity goals without consuming any time onsite or soil specific calibrations.     

西湖龙井茶生化成分与感官品质的相关性研究

[目的]为客观评价龙井茶的劣变提供依据。[方法]选择了几种典型具有代表性的包装材料进行了茶叶贮藏试验,采用多元线性回归研究了主要生化成分（含水量、茶多酚、氨基酸、水溶性浸出物、抗坏血酸和咖啡碱）与感官品质的相关性。[结果]抗坏血酸的氧化程度与龙井茶的感官品质劣变程度关系最为密切,达到了极显著相关性（0.997,P〈0.01）,并且两者存在显著的线性关系：即y（感官品质）=70.255＋93.776x（抗坏血酸含量）。[结论]可以由抗坏血酸的含量表征龙井茶品质劣变程度,相比带有主观因素的感官评价更精确。