中药材农药残留检测技术现状与前景

中药材种植已成为发展特色农业的支柱产业,但农药滥用导致的农药残留问题已成为影响中药材质量的重要因素之一。如何高效、快速地检测中药材中的农药残留是一个亟待解决的问题。因此,基于以上背景本文对现行的农药残留检测方法,如色谱检测法、酶抑制率法、酶联免疫分析法、侧向免疫层析法以及一些新型免疫传感器检测方法等进行了系统的阐述并探讨了农药残留检测方法的发展前景。     

试论农药残留检测的前处理技术

近年来,有毒农药残留对人健康所造成的危害及对环境所造成的破坏已经引起了我们的高度关注,文章列举了几种最为普遍的前处理技术,以实现对农药残留的最终解决.     

蔬菜中有机氯农药残留测定前处理方法综述

随着近些年来我国经济社会的快速发展,人民的生活水平不断提高。因此对所食用的蔬菜安全性要求也在不断升高。农药残留一直以来是我国蔬菜食品安全研究的重点方向。通过多年的发展我国现阶段在农药残留测定方面已经有了很大的发展。在开展测定工作的过程中前处理方法是其中的重点内容。本文就蔬菜中有机氯农药残留测定的前处理方法进行研究。     

光谱技术在农药残留检测中的应用与展望

光谱技术以其操作简便、高效、非破坏、高精度等诸多优点,在农药残留检测中得到广泛应用,常用的光谱检测技术有红外光谱技术、拉曼光谱技术、高光谱图像技术和荧光光谱技术等。为此,综合分析了上述常用光谱技术在农药残留检测中的应用现状,探讨了应用中存在的问题,并对应用前景进行了展望。     

农药残留快速检测技术研究进展

农产品质量安全关系到人们群众的生命安全,关系到社会的稳定和可持续发展,处于十分重要的地位,受到全社会的高度关注。文章对当前农药残留快速检测技术进行了简单概述,分析了当前农药快速检测中存在的问题,旨在为农药残留检测及农产品监管提供参考。     

山西省农产品农药残留检测技术现状及发展趋势探讨

分析山西省农产品检测技术的现状,发现其存在的一些问题,就国内外农产品农药残留检测技术研究进展,对山西省未来的发展方向进行探讨。     

植物源性食品中有机磷农药残留检测技术研究进展

有机磷农药作为一类高效与广谱的杀虫剂和除草剂等正被广泛用于农作物病虫防治领域,但大量使用后对人、动物和环境产生的危害也不容忽视。建立有效、快速和灵敏的有机磷农药残留检测技术,成为当前研究者关注的课题。本文综述了植物源性食品中有机磷农药残留检测的研究进展,并对今后其检测技术进行了展望。     

中药材农药残留检测的研究进展

在查阅、收集国内中药材农药残留检测文献方法基础上,综述近几年中药材农药残留检测研究进展,旨在为进一步开展中药材农药残留检测和质量控制提供参考。     

农产品质量安全控制与农药残留检测技术研究

农产品是人们必不可少的食物来源.随着近年来人们健康意识的提升,农产品的质量安全已逐渐成为社会热点,特别是农产品的农药残留问题更是大众关注的焦点.本文首先介绍了农产品质量安全控制要点,然后对农产品的农药残留检测技术进行分析研究.     

“一步式”农药残留快速检测集成卡的制备及应用

有机磷（OP）和氨基甲酸酯（CM）类农药的过量使用严重威胁着人类的安全和健康,其检测受到复杂操作的限制。本研究利用数字化控制的喷墨打印技术,并基于胆碱酯酶抑制法,构建了OP和CM类农药广谱、快速一步法检测方法。实验结果表明,该检测卡检测快速、灵敏度高、稳定性好、重复性高,适合多种场合实时检测,在POC检测中表现出巨大的应用潜力。     

植保无人飞机施药技术研究进展

植保无人飞机是田间病虫害防治的有效方法。随着我国农业生产趋向机械化、智能化,植保无人飞机施药技术开始崛起。剖析国内外植保无人飞机在飞控技术、航路规划、旋翼下洗气流的研究、田间植保技术和安全施药技术规范方面的应用优势,梳理了植保无人飞机施药技术的研究进展。分析发展中面临的主要问题:拥有飞控研发能力的企业不多、航路规划的要求越来越高、旋翼下洗气流对雾滴运动规律研究不足、静电施药系统中核心技术理论研究不足等。同时归纳总结出植保无人飞机的复合控制方法、实时航路规划、在空间和时间维度下下洗气流的分布特征、多机合作等是未来几大发展趋势,为植保无人飞机的推广应用提供参考。     

茶树植保机械及减量施药技术研究进展

农药防治是茶树病虫害综合防治的重要组成部分,其在病虫害突发或爆发时具有快速高效的防治优势.茶树叶片表面具有亲水性,常量施药会造成茶叶农残超标、生态环境破坏等问题,实现茶树减量施药是减少茶叶农残的有效手段.系统综述了茶树生物特性、茶树病虫害预测诊断及防治方法、茶树植保机械及施药技术,强调提高茶树低容量喷雾的农药有效利用率...     

污灌区有机氯农药的土—气交换行为与影响因素分析

以我国东北典型污灌区为研究区域,获取相关数据及模型参数,并应用逸度方法探讨了有机氯农药的土-气交换行为及其分馏效应。研究结果表明,在土壤有机质含量一定的情况下,日均温度最大时有机氯农药六六六(HCHs)和滴滴涕(DDTs)之间土-气分配系数(KSA)的差异比日均温度最小时高出一个数量级,HCHs比DDTs更容易挥发重新释放进入环境中而进行二次分配,土壤有机质质量分数每提高1%而引起的KSA值的变化率不同,且这种变化会随着有机质质量分数的提高而趋于平稳;辛醇-气分配系数(KOA)与土-气交换逸度分数ff呈负相关关系,当土壤有机质质量分数为1%、2%和3%时,其相关系数分别为-0.743(P0.05)、-0.763(P0.05)、-0.776(P0.05);应用土-气浓度比(Cs/a),进一步判定土壤浓度和大气浓度在其他参数不变的情况下,将会对HCHs及DDTs的土-气交换行为产生影响;HCHs与DDTs的初次分馏及二次分馏效应进一步说明土壤性质及其自身的理化性质均会对分馏效应产生影响。     

Effect of plastic mulch on water flow and herbicide transport in soil cultivated with pineapple crop: A modeling study

In Hawaii, pineapple is typically grown in raised beds covered with impervious plastic mulch. Field measurements of a commonly used herbicide (bromacil) mass beneath mulch-covered pineapple beds and inter-bed open areas revealed that open areas contained a mass of bromacil about 3.5 times greater than was originally applied, based on label instructions, to the entire field. The broadcast bromacil ended up in the inter-bed open areas through water runoff from the plastic mulch covering the pineapple beds. The objective of this study was to evaluate the impact of surficial management on water dynamics and bromacil concentration in the soil on a pineapple plantation using the one- (1D) and two-dimensional (2D) flow and transport models. Flow and transport processes were simulated in a 2D vertical cross-section perpendicular to the plant rows. The 1D simulation was limited to the open inter-bed areas. Several simulation scenarios were proposed to evaluate the effect of plastic mulch on bromacil transport in soil. In our simplified approach, the water and solute boundary fluxes for the non-covered areas were increased to simulate the water and solute contribution from the plastic mulch surface. The simulation results were compared with field observations of soil water potentials and resident bromacil concentration profiles. The field and laboratory-measured hydraulic and transport parameters were used for all simulation scenarios. Reasonably good agreement between the model-predicted and observed soil water potentials and bromacil concentration profiles was obtained. Biased 1D and 2D results were predicted when the water runoff from plastic mulch was neglected. The 1D approach to quantify bromacil transport beneath the inter-bed open areas seemed to be sufficient in case the water runoff from the mulch was taken into account.     

A simplified modelling approach for pesticide transport in a tile-drained field: The PESTDRAIN model

The paper presents a simplified model called PESTDRAIN. It simulates pesticide transport in a subsurface tile-drained field. It computes surface runoff and tile-drainage flow rates, along with the associated pesticide concentrations, with a variable event-driven time step. PESTDRAIN consists of three coupled modules: SIDRA, SIRUP and SILASOL. SIDRA and SIRUP are the water flow simulation modules in the saturated and unsaturated zones, respectively. SIDRA follows a simplified physically based approach while SIRUP follows a conceptual capacitive approach. SILASOL is the solute transport module for both the saturated and unsaturated zones and is based on transfer functions. It includes simple representations of adsorption and degradation of pesticides.PESTDRAIN was tested on field data sets collected for three drainage seasons at the La Jaillière experimental site in north-western France, for the wheat herbicides isoproturon (IPU) and diflufenican (DFF). After model calibration, relative errors for drainage and surface runoff flows over the season were 14% and 4%, respectively, and the Nash-Sutcliffe efficiency coefficient (N_eff) value for drainage discharge was 0.58. A fair reproduction of a high temporal resolution IPU concentration data set in drainage discharge was also obtained (N_eff=0.28). For the validation data sets, PESTDRAIN was able to simulate accurately drainage discharge with Nash-Sutcliffe efficiency coefficients of 0.57 and 0.69. The global N_eff was 0.44 for all flow-weighted average weekly concentrations in drainage. Relative errors for the pesticide losses were 2.5% and 35% (IPU), and 60% (DFF). For surface runoff the results were not as accurate, but they remained correct in terms of time location and order of magnitude. Although further validation is necessary with more field data, PESTDRAIN appears as a promising tool for agricultural water management.     

Environmental and cost efficiency of pesticide use in transgenic and conventional cotton production

This study focuses on the quantification of pesticide use efficiency for producers of transgenic cotton versus conventional cotton in order to test for the improvement promised by the genetically engineered crop. The environmental and cost efficiency of pesticide use is assessed by means of data envelopment analysis (DEA) and the external effects of pesticide are quantified by means of the pesticide leaching potential. To account for the fact that conditions other than the ‘treatment” (seed type) are not equal in farm surveys the study employs a second step Tobit regression. The data are from a survey of cotton growers in North Carolina, USA. Differences in environmental efficiency are found to be significant between herbicide tolerant and stacked gene (herbicide tolerant and insect resistant) cotton and between stacked gene and conventional cotton. In contrast, no statistically significant differences are found for efficiency of pest control cost. In the follow-up Tobit regression, differences in production environment and in farm, farmer and field characteristics are accounted for so that the contribution of seed type to efficiency can be observed. The regression results confirm the importance of stacked gene cotton for improving the environmental efficiency of pesticide use in cotton. In contrast, seed type was not significant in explaining differences in cost efficiency among North Carolina cotton growers. The new technology reduces pesticide application but these benefits are curbed by the high price of cotton seed (technology fee).     

光谱检测技术在种子质量检测中的应用

种子质量是影响作物产量关键因素之一,而传统种子质量检测方法难以满足其快速检测的要求,采用光谱检测技术可有效降低种子检验成本、提高检验效率.以玉米种子为研究对象,基于玉米种子光谱检测流程,阐述光谱检测技术在玉米种子活力、含水率与病害、品种与产地等方面的研究现状及现存问题.光谱检测技术已应用于玉米种子质量检测,预测模型的准...     

基于人工神经网络的田间秸秆覆盖率检测系统

以VC++为工具,田间实拍图像为研究对象,在分析田间秸秆和土壤纹理特征差别的基础上,设计了BP神经网络秸秆覆盖率检测系统.该系统采用了神经网络与纹理特征相结合的方法提取秸秆,并以纹理特征熵值为标准建立了网络输入层学习样本选取准则.人工模拟和田间试验表明,设计的BP神经网络秸秆覆盖率检测系统对田间秸秆的识别率达90%以上,秸秆覆盖率计算误差可控制在5%以内;与传统的拉绳法相比,检测效率提高50～120倍.     

Soybean yields and soil water status in Argentina: Simulation analysis

Recent changes in management of soybean production in Argentina may have large impacts on the soil water balance and on crop yield response. Changes in this system have included widespread adoption of a no-till management leaving crop residue on the soil surface, intensive cropping rotations (e.g. double cropping of wheat and soybean) so that the soil may not be fully recharged with water at the time of soybean sowing, and the occurrence of high water tables in a number of areas. The objective of this analysis was to assess the need to account for these factors in simulating soybean yields in Argentina. The influence of no-till management was simulated by simply decreasing the soil evaporation estimated for a bare soil by 70%. However, this alteration resulted in an over prediction in yield in many cases when it was assumed that the soil water content had been fully recharged at the initiation of the simulations. The difficulty with assuming a full soil water profile was confirmed when simulated yields were found to match well with observed yields when measured soil water content was used as an input to the model at the beginning of the soybean season. Finally, even with decreased soil evaporation there were still a few cases where simulated yield was less than observed yield. In these cases, a hypothetical water table, which relieved any drought stress once roots reached a depth of 1 m, resulted in yields that more closely matched observations. Overall, these results highlighted the need to estimate well both the influence of crop residue on soil evaporation and the soil water profile at sowing in simulating soybean yields in Argentina.