甜菜种子活力的测定——基于近红外高光谱技术

为保证田间甜菜种子的出苗率和生产潜力,需要在种植前对种子进行活力检测,挑选出活力高的甜菜种子进行推广种植。利用高温处理法对甜菜种子进行老化处理,再基于标准正态变换(SNV)、去趋势校正(DET)、Savitzky-Golay平滑处理(SG)、一阶差分(1D)和二阶差分(2D)5种近红外高光谱预处理方法,构建种子活力智能检测模型得出预测的种子发芽率,再利用老化处理后的甜菜种子进行发芽实验得出实际的发芽率。研究发现,甜菜种子经过一阶差分预处理建立的智能检测模型预测性能最好,其预测准确率达到91.92%。将未处理的甜菜种子的实际发芽率与一阶差分预处理法建立的智能模型预测结果进行对比,发现模型的预测准确率为88.2%。近红外高光谱技术是一种快速、无损的作物种子活力测定的新方法。     

A data transfer method for improving seed identification of maize (Zea mays) haploid breeding based on genetic similarity

Maize haploid breeding technology is able to identify haploid seeds non‐destructively, rapidly and at low cost with the help of Near‐infrared (NIR) spectral analysis. However, due to the hybridization of numerous parents and the low production rate of haploid, the haploid data collection becomes a burden for engineering this technology. Biologically, there are considerable similarities between the progeny of the same female parent and different male parents. Based on this advantage, similar spectral data can be transferred when the NIR technology is employed. A revised method of Transfer adaptive boost (TrAdaBoost) is proposed to improve identifying for the backpropagation neural network (BPNN) classifier. To avoid the negative transfer, a screening thresh is used to select out similar data, and the amount of these data are limited to join current training. The results show that the identification performances are improved significantly when the data amount is small. This method shows a high ability to make the seed identification more convenient for engineering maize haploid breeding.     

人工神经网络与近红外光谱分析

介绍了人工神经网络的原理、结构、算法和研究进展,以及该方法在近红外光谱分析中的重要地位和应用。     

Investigating the effects of simulated transport vibration on tomato tissue damage based on vis/NIR spectroscopy

Visible and near infrared (vis/NIR) spectroscopy combined with chemometrics were investigated to evaluate the effects of simulated transport vibration levels on damage of tomato fruit. A total of 280 tomato samples were randomly divided into 5 groups; each group was subjected to vibration at different acceleration levels. A total of 230 samples (46 from each group) were selected as a calibration set; whereas 50 samples (10 from each group) were selected as a prediction set. Raw spectra, differentiation (the first derivative) spectra, extended multiplicative scatter correction (EMSC) processed spectra and standard normal variant combined with detrending (SNV–DT) processed spectra were used for calibration models. SNV–DT processed spectra had the best performance using for partial least squares (PLS) analysis. The PLS analysis was implemented to calibrate models with different wavelength bands including visible, short-wave near infrared (SWNIR) and long-wave near infrared (LWNIR) regions. The best PLS model was obtained in the vis/NIR (600–1600 nm) region. Using a grid search technique and radial basis function (RBF) kernel, four least squares support vector machine (LS–SVM) models with different latent variables (7, 8, 9, and 10 LVs) were compared. The optimal model was obtained with 9 LVs and the correlation coefficient (r), root mean square error of prediction (RMSEP) and bias for the best prediction by LS–SVM were 0.984, 0.137 and 0.003, respectively. The results showed that vis/NIR spectroscopy could be applied as a reliable and rapid method for predicting the effect of vibration levels on tissue damage of tomato fruit.     

美洲黑杨与大青杨杂种叶片气孔导度的红外热像测量方法研究

为了研究红外热像技术在测量叶片气孔导度的应用上的可行性,以美洲黑杨与大青杨杂种(Populus deltoids Bartr.×Populus ussuriensis Kom.)为材料,在正常灌溉和干旱胁迫的对比下,利用红外热像仪考察了叶片的气孔导度Gs的日变化,根据叶片能量平衡方程分析了气孔导度与温度之间的关系,并采用便携式光合测量系统验证了红外热像测量气孔导度的准确性。结果表明：在2种水分处理条件下,叶片的气孔导度值均呈双峰曲线,峰值出现在10:00和14:00,正常灌溉和干旱条件下的峰值分别为120 mmol/(m2?s)、70 mmol/(m2?s)和80 mmol/(m2?s)、40 mmol/(m2?s);气孔导度与温度的响应呈反比趋势;气孔导度的模型计算值与实际测量值之间的关系呈线性相关,正常灌溉和干旱状态下的相关系数分别为0.8678、0.8347;气孔导度相关指数IG和水分胁迫指数CWSI分别与测量得到的气孔导度呈正比、反比的趋势。总之,与传统的利用便携式光合仪测定气孔导度相比,利用红外热像技术测量更便捷、准确,且适用性更加广泛,本研究为今后利用红外热像测量气孔导度奠定了理论基础。     

苹果表面缺陷红外热成像检测装置及处理方法

红外热成像技术是一种可用于农产品检测的新型无损检测技术。简介了红外热成像原理及该技术用于苹果表面缺陷检测的方法。实验装置以IR790为核心,将苹果表面温场转换为热图像显示,经计算机处理与分析,最终得到苹果缺陷信息。     

地黄真空红外辐射干燥模型

利用设计的真空红外辐射干燥箱,对中药材地黄进行了真空红外干燥研究.通过对试验值进行求对数并线性回归,确定了地黄的薄层真空红外干燥模型的形式为Modified Page方程,该模型与辐射板温度和干燥室压力有关,并得到了各参数的表达式和数值.试验值和模型预测值比较说明,该模型能很好地描述和预测地黄真空红外干燥的水分比变化规律.     

EMC单片机技术在粮仓库门控制系统中的应用

介绍了一种基于EMC单片机的粮仓库门自动控制系统.该系统分为红外遥控和接收两部分,其中红外遥控部分通过EM78P153控制红外无线遥控器发射指令信号,而红外接收部分通过接收模块接收到信号后由EM78P447来控制粮仓库门的开、关、停、限位和夜间自动点灯.系统结构简单,功能齐全,具有低成本、低功耗和可靠性高等特点.     

傅立叶变换近红外光谱法检测白酒总酸和总酯

该文研究白酒总酸和总酯的快速检测技术,通过解析不同白酒样品的近红外光谱图,对光谱数据进行不同的处理,结果表明：用一阶导数预处理光谱,谱区选择6102～5446 cm^-1,利用人工神经网络与傅立叶变换近红外光谱相结合,采用内部交叉验证法建立模型,效果较好。其中,总酸模型的决定系数为96.73%,内部交叉验证均方根差为0.048 g/L;总酯模型的决定系数为99.58%,内部交叉验证均方根差为0.085 g/L;进一步对总酸和总酯的模型进行验证和评价,结果表明总酸模型验证集的相关系数为99.2%,预测标准偏差为0.074 g/L;总酯模型验证集的相关为99.7%,预测标准偏差为0.134 g/L,表明建立的模型可靠,预测效果好,能满足白酒生产中总酸和总酯的快速检测要求。     

Thermal Infrared Radiation for Assessing Crop Water Stress in Wheat

Field studies on differentially irrigated wheat ( Triticum aestivum L.) crops were conducted at Pantnagar for two years to evaluate the use of thermal infrared radiation to detect crop water stress. Data show that the stress-degree-day index (mid day canopy-air temperature difference) is influenced by environmental variability other than soil moisture. Improvement in the stress-degree-day (SDD) index was achieved by including the measurements of vapor pressure deficit and approach was termed as plant water stress index (PWSI). Observations indicated that daily variation in SDD values due to meteorological changes was removed through PWSI. Better correlation was found between soil-induced leaf water potential and plant water stress index than between total leaf water potential and plant water stress index. It is concluded that remote sensing of thermal infrared radiation offers a promising technique which can be incorporated into irrigation management programme.