Microwave l-band (1730 MHz) accurately estimates the relative water content in poplar leaves. A comparison with a near infrared water index (R1300/R1450)

In this study the estimation of reflectivity at 1730 MHz (l-band), measured with a microwave digital cordless telephony (DCT) patch antenna, is presented as an easy-to-handle and non-destructive new method to assess the relative water content (RWC) of poplar leaves and filter discs at different levels of dehydration. The accuracy of this new method has been contrasted with the R₁₃₀₀/R₁₄₅₀ index, determined by a portable near infrared (NIR) spectrometer. The close correlations found between RWC and the reflectivity at a frequency of 1730 MHz, both for filters and leaves, indicate that microwave determinations are rather independent of the physical properties of the material analysed. On the contrary, the differences found between poplar leaves and leaf filters in the relationships established between RWC and the R₁₃₀₀/R₁₄₅₀ index demonstrate a strong influence of the properties of the material in NIR reflectance measurements, specifically as they relate to changes in leaf thickness during dehydration. It should be noted that the amount of energy received by the leaf for the microwave technique (0.1 mW) was much lower than that received for the measuring of the R₁₃₀₀/R₁₄₅₀ index (2.5 W). Moreover, R-square coefficients were higher for microwaves than for the R₁₃₀₀/R₁₄₅₀ index. The use of a technologically simple, low cost and portable device, based on a microwave DCT patch antenna, could yield a solid support for the development of a commercial apparatus enabling the determination of plant water status under field conditions.     

近红外光谱技术及其在农产品品质分析中的应用

近红外光谱技术是一种高效、快速的现代分析技术,已在很多领域得到广泛应用。文章对近红外光谱分析的技术原理、技术方法、技术特点作了简要介绍,并对其在农产品品质分析中的应用现状和应用前景进行了综述。     

腰果酚基乙酸酯增塑剂的合成及其增塑聚氯乙烯性能

为了进一步利用农林剩余物资源替代石化原料,该研究以腰果酚为原料,通过对其酚羟基进行酯化改性,制备腰果酚基乙酸酯(cardanol acetate,CA)增塑剂。采用核磁共振氢谱(1H nuclear magnetic resonance,1H NMR)和核磁共振碳谱(13C nuclear magnetic resonance,13C NMR)对产物的结构进行表征。通过动态力学性能(dynamic thermo mechanical analysis,DMA),拉伸性能测试,热重分析(thermogravimetric analysis,TGA),以及与聚氯乙烯(polyvinyl chloride,PVC)共混样品的傅里叶红外分析(fourier transform infrared spectroscopy,FT-IR)等方法,评价腰果酚基乙酸酯作为辅助增塑剂应用于软质聚氯乙烯的增塑效果,并与商业增塑剂对苯二甲二辛酯(bis(2-ethylhexyl)benzene-1,4-dicarboxylate,DOTP)进行对比。研究结果表明,m(DOTP)∶m(CA)=4∶6为较佳配伍比例,共混体系的玻璃化转变温度由41.52℃降低至35.93℃,断裂伸长率由244.75%增加到了302.13%,热稳定性及相容性均得到有效改善,因此腰果酚基乙酸酯可用作聚氯乙烯的优良辅助增塑剂。研究结果为腰果酚在增塑剂领域的应用提供了参考。     

小麦种子发芽率近红外定量分析模型的优化

The backward interval partial least squares (BiPLS) and the synergy interval partial least squares (SiPLS) were applied to select the characteristic spectral regions representing the germination rate of 84 wheat seeds and build the near infrared (NIR) quantitative analysis model of wheat seed germination rate.Results from comparison showed that the models built by two variable selection methods had better predictive ability than full-spectral partial least squares(PLS) model.The optimal model was obtained by SiPLS with the calibration and prediction correlation coefficient(R) at 0.902 and 0.967 respectively, and ratio of performance to standard deviate (RPD) at 3.75.Based on this, the physical chemistry significance of characteristic spectral regions was analyzed.The characteristic spectral of wheat seed germination rate contained characteristic peaks of water, protein, starch, fiber, which were the internal nutrients of the seed that influence the germination ability, thus explaining the mechanism of measuring wheat seed germination rate using NIR to a certain extent.     

pH对针铁矿表面磷酸盐吸附的化学形态的影响

Chemical forms of the phosphate adsorbed on goethite surfaces and characteristics of the coordinate groups which exchange with P on goethite surfaces in solutions with different pll values were investigated.Results showed that the chemical forms of P on goethite surfaces changed from the dominance of monodentate corrdination to that of bidentate one with increasing pH of the solution.By influencing types of phosphate ions in solutions,pH affected the chemical forms of P on goethite surfaces,The amount of OH^- displaced by phosphae on goethite surfaces was the most at pH 7.0,the second at pH 9.0,and the least at pH 4.5.     

Near-infrared spectroscopy for analysis of chemical and microbiological properties of forest soil organic horizons in a heavy-metal-polluted area

In industrial areas, heavy metals may accumulate in forest soil organic horizons, affecting soil microorganisms and causing changes in the chemical composition of the accumulated organic matter. The objectives of this study were to test the ability of near-infrared spectroscopy (NIRS) to detect heavy metal effects on the chemical composition of forest soil O horizons and to test whether NIRS may be used to quantitatively determine total and exchangeable concentrations of Zn and Pb (Zn_t, Pb_t, Zn_ex, Pb_ex) and other chemical and microbial properties in forest soil O horizons polluted with heavy metals. The samples of O horizons (n = 79) were analyzed for organic C (C_org), total N and S (N_t, S_t), Zn_t, Pb_t, Zn_ex, Pb_ex, basal respiration (BR), microbial biomass (C_mic) and C_mic-to-C_org ratio. Spectra of the samples were recorded in the Vis-NIR range (400–2,500 nm). To detect heavy-metal-induced changes in the chemical composition of O horizons principal components (PC1–PC7) based on the spectral data were regressed against Zn_t + Pb_t values. A modified partial least squares method was used to develop calibration models for prediction of various chemical and microbial properties of the samples from their spectra. Regression analysis revealed a significant relationship between PC3 and PC5 (r = −0.27 and −0.34, respectively) and Zn_t + Pb_t values, indicating an effect of heavy metal pollution on the spectral properties of the O horizons and thus on their chemical composition. For quantitative estimations, the best calibration model was obtained for C_org-to-N_t ratio (r = 0.98). The models for C_org, N_t, and microbial properties were satisfactory but less accurate. NIRS failed to accurately predict S_t, C_org-to-S_t, Zn_t, Pb_t, Zn_ex, and Pb_ex.     

Empirical predictions of plant material C and N mineralization patterns from near infrared spectroscopy, stepwise chemical digestion and C/N ratios

Prediction of carbon (C) and nitrogen (N) mineralization patterns of plant litter is desirable for both agronomic and environmental reasons. Near infrared reflectance (NIR) spectroscopy has recently been introduced in decomposition studies to characterize biochemical composition. The purpose of the current study was to use empirical techniques to predict C and N mineralization patterns of a wide range of plant materials incubated under controlled temperature and moisture conditions. We hypothesized that the richness of information in the NIR spectra would considerably improve predictions compared to traditional stepwise chemical digestion (SCD) or C/N ratios. Initially, we fitted a number of empirical functions to the observed C and N mineralization patterns. The best functions fitted with R²=0.990 and 0.949 to C and N, respectively. The fractions of C and N mineralized at different points in time were then either predicted directly with regression functions or indirectly by prediction of the parameters of the empirical functions fitted to incubation data. In both cases, partial least squares (PLS) regressions were used and predictions were validated by cross-validations. We found that the NIR spectra (best R²=0.925) were able to predict C mineralization patterns marginally better than the SCD fractions (best R²=0.911), but considerably better than the C/N ratios (best R²=0.851). In contrast, N mineralization was better predicted by SCD fractions (best R²=0.533) than the C/N ratio (best R²=0.497), which was better than NIR predictions (best R²=0.446). Although the predictions with the NIR spectra were only slightly better for C and worse for N mineralization compared to SCD fractions, NIR spectroscopy still holds advantages, as it is a much less laborious and cheaper analytical method. Furthermore, exploration of the applications of NIR spectroscopy in decomposition studies has only just begun, and offers new ways to gain insights into the decomposition process.     

Soil Properties Degradation Assessment Using Infrared Scanning Technique of Soils （Case Study： Eastern of Congo）

Recently, near infrared reflectance （NIR） and mid-infrared （MIR） spectroscopy techniques are increasingly introduced as convenient and simple non-destructive techniques for quantifying several soil properties. This study uses MIR method to predict pH, soil organic C, total N, AI, Ca, Mg and K, CEC and soil texture for soil samples collected in Sud-Kivu, Congo. A total of 536 composite soil samples were taken from two locations （Burhale and Luhihi） at two depths （0-20 cm and 20-40 cm） using a spatially-stratified random sampling design within an area of 200 km2. Differences in characteristics were evaluated between the two locations, land use （cultivated vs. non-cultivated land） with soil depths. A random subset of the samples （10%） were analyzed using standard wet chemistry methods, and calibration models developed by MIR data to estimate soil properties for the full soil sample set. Partial least squares regression （PLS） method gave acceptable coefficients of determination between 0.71 and 0.93 for all parameters. Soil organic matter levels were higher in cultivated plots in Luhihi （3.9% C） than in Burhale （3.0% C）, suggesting lower levels of soil fertility in the later area. This indicates high levels of acidity, which are likely to limit crop production in the area. Phosphorus deficiency is acute in Burhale （2.4 mg P/kg） but less in Luhihi （5.4 mg P/kg）. In both locations, low levels of Ca and Mg indicate that soils may be susceptible to deficiencies in both elements.These findings provide new opportunities for monitoring soil quality in the region which can benefit multiple actors and scientists involved in the agricultural and environmental sectors.     

延边地区农民旅游市场现状特征分析

基于城乡比较、远近比较及民族比较的视角，利用实地调查数据及文献数据分析得出延边地区农民旅游市场的特征。城乡居民旅游差异较大，远郊及近郊农民的差异主要表现在出游组织方式、出游距离、旅游目的地选择、消费额等4个方面，民族差异性主要表现为旅游交通工具的选择、旅游时间长度、旅游消费额度等3个方面。     

原子吸收光谱法测定青蒿中金属元素含量

使用HNO3-HClO4体系消解样品,采用火焰原子吸收光谱法测定5种不同来源青蒿(Artemisia annua L.)中的Mg、Fe、Mn、Cu和Zn含量.结果表明,青蒿中5种金属元素的含量大小依次为Mg＞Fe＞Zn＞Mn＞Cu,该法加标回收率在98.00％～104.00％,相对标准偏差(n=3)为0.51％～2.86％.该法快速、简便、灵敏、准确,可用于青蒿中金属元素的分析.