Real-Time Soil CO2 Respiration Rate Determination and the Comparison between the Infrared Gas Analyzer and Microrespirometer (MicroRes®) Methods

Soil carbon dioxide (CO₂) respiration is one of the important soil health parameters that provides a general assessment of soil microbial activity and soil quality. Soil respiration rates, however, have not been widely applied in soil testing protocols mainly because the traditional methods are either inconvenient, technically cumbersome or too expensive. Currently, only two methods are available for a true real-time soil respiration rate determination (<2 h): the infrared gas analyzer (IRGA) and the microrespirometer (MR or MicroRes^®) methods. We analyzed the real-time soil respiration rates of 20 soil samples from fifteen states after various periods of incubation using the IRGA method and the MR method. The measured soil respiration rates ranged from 0.4 µL CO₂/h/g to 9.0 µL CO₂/h/g. Both methods show precision in soil respiration determinations (CV = 12.7% and 11.9%, respectively). Comparison of the results between the IRGA and MR methods indicates high degrees of agreement (r² = 0.914). This study shows that the MR method is a simpler and more cost-effective alternative for real-time soil respiration rate determinations.     

Sorption,Release and Forms of Mercury in Contaminated Soils Stabilized with Water Treatment Residual Nanoparticles

This study was carried out to assess, for the first time, the effect of water treatment residual nanoparticles (nWTR) on mobility, fractionation and speciation of Hg in two arid zone soils. Nanoscale water treatment residual application markedly reduced cumulative Hg released from soils studied, with the effect increasing as the nWTR application rate increases. The power function kinetic model well described the desorption process from soils and soils with nWTR. Meanwhile, application of nWTR greatly increased the association of Hg with the residual fraction and increased the most stable Hg species (Hg (OH)₂ amor), which in turn enhanced Hg immobilization in the studied soils. Fourier transmission infrared spectroscopy analysis indicated the involvement of nWTR in the retention of Hg (II) and revealed that sorption occurred mainly through OH groups, which suggest inner‐sphere adsorption of Hg ions to surface functional groups on nWTR. These results demonstrated the feasibility of using a green and low‐cost nWTR as best management practice to retain and immobilize excess Hg in contaminated soils. Copyright © 2016 John Wiley & Sons, Ltd.     

Feeding quality assessment of fresh maize stover by means of near-infrared spectroscopy with a new sample presentation unit

Stover quality traits are important in breeding programmes of maize cultivars. However, conventional procedures for evaluation of stover quality are expensive and thus limit the full exploitation of the available genetic variability. Our objective was to assess the potential of near‐infrared spectroscopy (NIRS) with a new sample presentation unit to determine feeding quality of maize stover. The plant material comprised maize inbreds and hybrids. The sample presentation unit was equipped with a near‐infrared diode‐array spectrometer. Coefficient of determination in cross‐validation ranged between 0.77 and 0.94 for contents of dry matter, nitrogen, neutral detergent fibre and in vitro fermentability expressed as gas volume after 24h incubation time, but it was lower for ash content. It was concluded that NIRS with the new sample presentation unit was less accurate than laboratory NIRS to predict the standard reference methods. However, the new sample presentation unit might be used as a fast and efficient technique to perform large screenings of maize stover accessions in breeding programmes.     

The application of proximal visible and near-infrared spectroscopy to estimate soil organic matter on the Triffa Plain of Morocco

Soil organic matter (SOM) is a fundamental soil constituent. The estimation of this parameter in the laboratory using the classical method is complex time-consuming and requires the use of chemical reagents. The objectives of this study were to assess the accuracy of two laboratory measurement setups of the VIS-NIR spectroscopy in estimating SOM content and determine the important spectral bands in the SOM estimation model. A total of 115 soil samples were collected from the non-root zone (0–20 cm) of soil in the study area of the Triffa Plain and then analysed for SOM in the laboratory by the Walkley–Black method. The reflectance spectra of soil samples were measured by two protocols, Contact Probe (CP) and Pistol Grip (PG)) of the ASD spectroradiometer (350–2500 nm) in the laboratory. Partial least squares regression (PLSR) was used to develop the prediction models. The results of coefficient of determination (R²) and the root mean square error (RMSE) showed that the pistol grip offers reasonable accuracy with an R² = 0.93 and RMSE = 0.13 compared to the contact probe protocol with an R² = 0.85 and RMSE = 0.19. The near-Infrared range were more accurate than those in the visible range for predicting SOM using the both setups (CP and PG). The significant wavelengths contributing to the prediction of SOM for (PG) setup were at: 424, 597, 1432, 1484, 1830,1920, 2200, 2357 and 2430 nm, while were at 433, 587, 1380, 1431, 1929, 2200 and 2345 nm for (CP) setup.     

基于改进YOLO v7的生猪群体体温热红外自动检测方法

针对当前生猪规模化养殖过程中基于热红外技术的生猪体温测量效率低的问题,提出了一种基于改进YOLO v7的生猪群体体温检测方法。改进YOLO v7算法在Head层引入VoV-GSCSP结构,降低网络结构复杂度;使用内容感知特征重组(Content-aware reassembly of features,CARAFE)替换模型原始上采样算子,提高特征图放大后的品质,强化生猪头部区域有效特征;引入感受野增强模块（Receptive field enhancement module,RFE）,增强特征金字塔对生猪头部特征的提取能力。本文改进YOLO v7算法对于生猪头部的检测精确率为87.9%,召回率为92.5%,平均精度均值（Mean average precision,mAP）为94.7%。与原始YOLO v7相比,精确率提高3.6个百分点,召回率提高7.0个百分点,mAP提高3.6个百分点。该方法首先自动检测生猪头部区域,再利用头部最大温度与耳根温度的高相关性,最终自动获取生猪体温。温度提取平均绝对误差仅为0.16℃,检测速度为222f/s,实现了生猪群体体温的实时精准检测。综合上述试验结果表明,该方法能够自动定位生猪群体的头部区域,满足生猪群体体温测定的高效和高精度要求,为群养生猪体温自动检测提供了有效的技术支撑。     

花生油中黄曲霉毒素B1含量的荧光光谱表征

花生油在生产过程中极易受到黄曲霉毒素B1(Aflatoxin B1, AFB1)的污染。针对AFB1的传统检测方法操作繁琐、时效性差等问题,利用荧光光谱技术快速检测花生油中AFB1含量。首先通过三维荧光光谱确定最佳激发波长,使用K-means和自组织映射(Self organizing map, SOM)聚类算法对花生油中AFB1含量进行超标与否的定性鉴别,准确率均达95%以上;其次使用2种预处理算法和2种降维算法,选出竞争自适应重加权采样(Competitive adaptive reweighted sampling, CARS)为最佳的波长选择方法;随后将回声状态网络(Echo state network, ESN)用于AFB1的定量建模,同时与其他模型作比较,结果显示CARS-ESN模型获得了最佳AFB1含量预测效果;最后将麻雀搜索算法(Sparrow search algorithm, SSA)用于对ESN参数进行寻优,最终预测集决定系数达0.984,均方根误差达2.13μg/kg。结果表明了荧光光谱技术结合ESN预测花生油中AFB1含量的可行性,为在线检测食用油中真菌毒素含...     

Fractionation of soil humic acids by preparative polyacrylamide gel electrophoresis in the presence of concentrated urea

To separate soil humic acids (HAs) into their constituents and characterize them, polyacrylamide gel electrophoresis (PAGE) was carried out in the presence of 7 M urea using a preparative electrophoresis system. Two types of soil HAs were fractionated into nine fractions by PAGE. The dark-colored constituents were recovered from the electrophoretic fractions by precipitation on acidification, and the brown-colored constituents dissolved in the acidic solution of fast-moving fractions were recovered by adsorption onto DAX-8 resin. High-performance size-exclusion chromatography (HPSEC) confirmed that the constituents of the HAs were separated based on their molecular size by PAGE. The dark-colored constituents exhibited higher degrees of humification than did the corresponding unfractionated HAs, except for the constituents remaining in the electrophoretic gels at the end of electrophoresis. Diffuse reflectance infrared spectroscopy revealed that the chemical properties of the dark-colored constituents changed regularly: the content of carboxyl groups decreased and the proportions of proteinous, aliphatic and polysaccharide moieties increased with increasing molecular size. The humification degrees of the constituents adsorbed onto DAX-8 resin were considerably lower than those of the corresponding unfractionated HAs. The chemical properties of the DAX-8-adsorbed constituents were different from those of the dark-colored constituents. Observation of electrophoretic fractions under blue light (470 nm) and HPSEC with fluorescence detection at an excitation wavelength of 460 nm and an emission wavelength of 520 nm showed that green fluorescent substances were largely concentrated in the smallest molecular size fractions and were partitioned into both the dark-colored precipitates and DAX-8-adsorbed fractions. The proportion of organic carbon recovered by precipitation and adsorption onto DAX-8 resin was 45–63%, indicating that substantial parts of the HA constituents were missing. The unrecovered constituents were considered to be acid-soluble, nearly colorless substances. The dissociation of the acid-soluble constituents from the acid-insoluble dark-colored constituents during the preparative PAGE of soil HAs was ascribed to disruption of hydrogen bonding and hydrophobic interactions caused by concentrated urea.     

玉米主要品质便携式检测装置设计与试验

我国玉米产量高,高效、便携、低成本的玉米成分检测技术及其装置对于玉米品质的检测至关重要,基于可见/近红外光谱技术,设计了一款玉米主要品质便携式检测装置。为探究所设计方案的可行性,自行搭建了可见/近红外光谱采集系统,对不同品种共72份玉米样本进行光谱采集,分别建立了玉米籽粒蛋白质、脂肪和淀粉含量的偏最小二乘（PLS）预测模型以及结合竞争性自适应重加权算法（CARS）的CARS-PLS预测模型。结果表明,CARS方法可以有效筛选出各组分的相关变量,提升模型效果,各组分质量分数的预测集均方根误差（RMSEP）均有所下降, 蛋白质质量分数的RMSEP由0.4866%降至0.4068%;脂肪质量分数的RMSEP由0.1549%降至0.0989%;淀粉质量分数的RMSEP由0.4714%降至0.4675%。预测集相关系数Rp均有所提高,蛋白质质量分数的Rp由0.9309提升至0.9603;脂肪质量分数的Rp由0.9497提升至0.9770;淀粉质量分数的Rp由0.9520提升至0.9605。基于CARS方法所筛选的各组分特征变量,选择了合适的近红外光谱传感器,在此基础上设计了检测装置的光谱采集单元、控制单元、显示单元、电源单元以及散热单元,并基于NodeMCU开发板和Arduino IDE开发工具,采用Arduino语言对装置控制程序进行开发,实现“一键式”快速检测。试验验证了该装置的检测精度和稳定性,结果表明,预测玉米籽粒蛋白质、脂肪和淀粉质量分数的相关系数分别为0.8431、0.8243、0.8154,预测均方根误差分别为0.3576%、0.2318%、0.2333%,相对分析误差分别为1.8577、1.7761、1.5735。对同一样本多次重复预测,各组分预测值的变异系数分别为0.235%、0.241%和0.028%。     

剔除土壤背景的棉花水分胁迫无人机热红外遥感诊断

剔除无人机热红外影像中的土壤背景是提高作物水分诊断精度的有效途径,但也是热红外图像处理的难点问题。本文以不同水分处理的花铃期棉花为研究对象,分别在09:00、13:00和17:00等3个时刻,连续5 d采集无人机高分辨率热红外影像,并采用二值化Ostu算法和Canny边缘检测算法对热红外图像进行掩膜处理,实现对土壤背景的剔除,然后分别计算二值化Ostu算法、Canny边缘检测算法和包含土壤背景下的3种棉花水分胁迫指数(Crop water stress index,CWSI),最后建立不同时刻下3种CWSI与棉花叶片气孔导度Gs的关系模型。研究结果表明,应用Canny边缘检测算法可有效剔除热红外影像中的土壤背景,剔除土壤背景后的温度直方图呈单峰的偏态分布;3种处理方法获得的作物水分胁迫指数CWSI中,Canny边缘检测算法的CWSI最小,二值化Ostu算法的CWSI较高,包含土壤背景的CWSI最大;采用Canny边缘检测算法剔除土壤背景后的CWSI与棉花叶片气孔导度Gs的决定系数R2达到0.84,Ostu算法的结果次之,包含土壤背景的最差。本研究可为无人机热红外遥感监测作物水分状况提供参考。     

红外光电开关在杨树对靶喷雾机中的应用

环境保护和可持续发展是21世纪农业发展优先考虑的问题,对作物的病虫害进行化学防治是植物保护的主要手段。截止目前,我国已有常用农药品种180种以上,但有关植保的研究大多集中在农药本身,对施药机械的研究开发进行得很少,这是我国农药应用效率不高的一个重要因素。由此而造成的环境污染也越来越严重,对农作物对靶喷药是植保机械的重要研究方向。为此,设计了远距离红外光电开关应用于杨树对靶喷雾中,实验结果达到了设计要求,减少了施药成本,降低了对环境的污染程度。