A calibration method of detecting soil water content based on the information-sharing in wireless sensor network

In agricultural production, there is contradiction between the cost and accuracy of detection during the course of acquiring soil water content (θ) online. This conflict is one of the core issues of automatic water-saving irrigation technology in agriculture. At the same time, capacitive soil moisture sensor (CSMS) has received considerable attention, for it can acquire θ with low cost and high precision, and meet the application requirements of wireless sensor network (WSN). But CSMS is vulnerable to the soil temperature (T_s) and salinity (S_s) in the measurement process. Therefore, this study took EC-5 sensor for example to establish water detection calibration models of soil temperature and salinity for single sensor, using Least Squares Support Vector Machines on MatLAB (LS-SVMlab) as the tool. On this basis, we explored the spatial variability of T_s and S_s, and then a method, which could be used to calibrate the output signals of sensors in multi-point network, was proposed based on the information-sharing (T_s or S_s) technology of WSN. Through laboratory experiment, we effectively reduced the impact of soil temperature and salinity on the single sensor. In example analysis, we investigated the detection precision and costs under different information-sharing radiuses (r). And the results indicated that the method we proposed based on the information-sharing technology of WSN could successfully calibrate the influence of soil temperature and salinity on sensors in multi-point network, and it was an efficacious approach to determine the balance between the calibration accuracy of moisture sensor and the investment of agricultural production. For example, while the calibration precision of soil temperature and salinity is respectively 1%, the costs can be reduced by 30%.     

Estimating reference evapotranspiration with atmometers in a semiarid environment

Reference evapotranspiration (ET₀) estimations require accurate measurements of meteorological variables (solar radiation, air temperature, wind speed, and relative humidity) which are not available in many countries of the world. Alternative approaches are the use of Class A pan evaporimeters and atmometers, which have several advantages compared to meteorological stations: they are simple, inexpensive and provide a visual interpretation of ET₀. The objectives of the study were to compare the evaporation from atmometers (ET_gage) with the evapotranspiration estimated by the FAO-56 Penman-Monteith equation (ET_0PM) and to evaluate the variability between three modified atmometers of a commercial model. Comparison between daily ET_gage measured by the atmometer and ET_0PM showed a good correlation. However, ET_gage underestimated ET_0PM by approximately 9%. Differences between ET_gage and ET_0PM ranged from −2.4 to 2.2 mm d⁻¹ while the mean bias error was −0.41 mm d⁻¹. Underestimations occurred more frequently on days with low maximum temperatures and high wind speeds. On the contrary, atmometer overestimations occurred on days with high maximum temperatures and low wind speeds. Estimates of ET₀ using the atmometer appeared to be more accurate under non-windy conditions and moderate temperatures as well as under windy conditions and high temperatures. Atmometers 2 and 3 overestimated the evaporated water by atmometer 1 with a maximum variability of cumulative water losses of 4.5%. A temperature-based calibration was performed to improve the atmometer accuracy, using maximum temperature as an independent variable, with good results.     

轮胎试验台六分力解算、标定与优化分析

轮胎试验台的力与力矩测试精度直接影响到轮胎数据的准确性,应用多体动力学理论对所研发的平板式六自由度低速轮胎试验台进行研究,分析了该试验台姿态控制的机理,推导出试验台轮胎六分力解算公式,并用abaqus有限元软件验证其准确性。然后对设计加工出的试验台进行标定,结果表明:3个方向的力吻合较好,但是力矩并不特别理想。经合理分析假设,试验台6个电缸铰支的硬点实际安装中存在空间的偏差,对其进行辨识优化分析,结果表明:优化后三方向的力及力矩与标定值吻合的精度符合要求,力的精度高于0.75%,力矩精度可达1%左右,证明了铰支安装偏差的假设是合理的,也体现出该轮胎试验台在测试精度上的优势。     

利用近红外透射光谱技术测定小麦籽粒硬度的研究

以2001和2002年度583份小麦样品为材料，用近红外透射光谱仪（NITS）对小麦籽粒硬度进行分析，比较了偏最小二乘法和多元线性回归两种算法和未经导数处理、一阶导数处理、二阶导数处理3种光谱变量转换方式的分析结果。表明，两种算法中偏最小二乘法优于多元线性回归算法，3种处理方式中一阶导数处理效果最好，其定标集和预测     

Enhancing the Simplified Surface Energy Balance (SSEB) approach for estimating landscape ET: Validation with the METRIC model

Evapotranspiration (ET) can be derived from satellite data using surface energy balance principles. METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) is one of the most widely used models available in the literature to estimate ET from satellite imagery. The Simplified Surface Energy Balance (SSEB) model is much easier and less expensive to implement. The main purpose of this research was to present an enhanced version of the Simplified Surface Energy Balance (SSEB) model and to evaluate its performance using the established METRIC model. In this study, SSEB and METRIC ET fractions were compared using 7 Landsat images acquired for south central Idaho during the 2003 growing season. The enhanced SSEB model compared well with the METRIC model output exhibiting an r² improvement from 0.83 to 0.90 in less complex topography (elevation less than 2000 m) and with an improvement of r² from 0.27 to 0.38 in more complex (mountain) areas with elevation greater than 2000 m. Independent evaluation showed that both models exhibited higher variation in complex topographic regions, although more with SSEB than with METRIC. The higher ET fraction variation in the complex mountainous regions highlighted the difficulty of capturing the radiation and heat transfer physics on steep slopes having variable aspect with the simple index model, and the need to conduct more research. However, the temporal consistency of the results suggests that the SSEB model can be used on a wide range of elevation (more successfully up 2000 m) to detect anomalies in space and time for water resources management and monitoring such as for drought early warning systems in data scarce regions. SSEB has a potential for operational agro-hydrologic applications to estimate ET with inputs of surface temperature, NDVI, DEM and reference ET.     

圆柱螺纹牙型非接触检测失真校正

在对圆柱螺纹进行非接触检测时,螺纹牙型会产生失真现象,为此提出图像校正的方法。从螺纹牙型失真的几何原理出发,建立相应的螺纹数学模型,对采集的螺纹图像进行校正,获得真实的螺纹牙型,并通过软件仿真和试验验证了该模型的正确性。同时表明图像校正的方法提高了圆柱螺纹非接触检测的精度、效率。     

近红外透射光谱技术测定黍稷蛋白含量的研究(英文)

[目的]探索快速测定完整黍稷籽粒蛋白含量的方法。[方法]采用近红外光谱分析技术建立数学模型并进行预测,比较原始透射光谱经导数处理结合不同回归算法对模型的影响。[结果]分别经一阶和二阶导数处理后利用偏小二乘法和改进的偏小二乘法,4 种方法的分析效果相近,最优的是一阶导数结合改进的偏最小二乘回归法,黍稷蛋白定标模型的定标相关系数(RSQ)为0.880 6,定标标准误差(SEC)为0.342 4,交互定标标准误差(SECV)为 0.375 1,外部预测标准误差(SEP)为 0.454。[结论]以完整黍稷籽粒为样品所建立的蛋白 NITS 模型,可以用于黍稷蛋白含量的快速检测。     

基于物联网的日光温室环境监测在线校准

[目的]温室环境条件特别是温度对于作物生长和发育具有十分显著的影响。日光温室调控的主要环境因子之一是温度。然而,自然环境下的光照对温度产生作用,影响空气温度的监测精度。大多温度传感要求将传感器置于避光处,然而实际应用中难以保证。[方法]采用机器学习中的支持向量机算法(SVM),对日光温室内的温度智能监测算法进行了研究,根据光照情况对实时监测的温度数据进行校准。[结果]通过与实验测量的数据进行对比分析,结果表明,所提出的监测方法可以较为准确地实时监测空气温度,从而无需使用隔热材料或者遮阳处理,就可以基于监测的数据更精确地对相应的环境因素进行调节。[结论]基于该方法,可采用常用的工业设备实现温室大棚内实时温度数据的监测,既可以节约设备和人力成本,又可以为温室控制提供准确的数据。     

Modeling height-diameter relationship for artificial monoculture Metasequoia glyptostroboides in sub-tropic coastal megacity Shanghai,China

Tree height is a key variable in forest monitoring studies and for forest management. However, tree height measurement is time consuming, and the recommended procedure is to use estimates from tree height (H) - diameter at breast height (DBH) models. Increasingly, H-DBH models are being developed for urban forests, providing tools to forest management and ecosystem services estimation. Here, we compared model forms and approaches for predicting H as a function of DBH and additional stand level covariates variables. Four model forms were evaluated: (i) basic models (which only used DBH as predictor variable); (ii) generalized models (which used DBH and other predictor variables based on the best basic model); (iii) a mixed-effects model based on the best basic model; and (iv) a mixed-effects model based on the generalized model. Several sampling designs aimed at minimizing height measurement were tested in terms of accuracy and applicability. Taking predicted accuracy and investigation cost into account, we recommend generalized non-linear mixed-effects model (NLME) when there were two or less tree height measurements taken in a given stand. The basic NLME model could be calibrated when there were 3 or more tree height measurements, depending on the required level of accuracy and investigation cost. Additionally, we first reported that soil pH as a covariate variable in H-DBH model and our generalized NLME model implied that the difference in the H-DBH relationship caused by pH varies among different stands. This finding may be attributable to differing biological properties of the similar alkaline tolerance species.     

近红外光谱法非破坏性测定绿豆籽粒粗蛋白质含量的研究

为了找到一种快速、简单的测定绿豆品质的方法,利用瑞典波通(Perten)公司生产的DA7200二极管阵列近红外光谱仪,以来自我国绿豆主产区的77份绿豆资源为试验材料,对样品进行光谱扫描,并测定了直链淀粉含量的参比数据。结果表明:定标集和检验集样品的蛋白质含量预测值与化学测定值之间均呈极显著的正相关,相关系数分别为0.977 2和0.963 1;所建定标模型具有较高的预测精度。本研究利用近红外光谱仪对完整绿豆粗蛋白质的分析,可直接用于育种材料选择以及突变体筛选和种质资源的评价等研究。