Investigation of soil surface organic and inorganic carbon contents in a low-intensity farming system using laboratory visible and near-infrared spectroscopy

ABSTRACT

In some regions of Italy, low-intensity farming systems, together with variable climate conditions, have lowered soil organic carbon (SOC) content and soil quality attributes. This work aims to investigate on some aspects of (1) total organic carbon (TOC) prediction using Vis-NIR reflectance spectroscopy in combination with partial least squares regression (PLSR); (2) the most appropriate pre-processing techniques of Vis-NIR absorbance spectra; (3) the composition of organic carbon using variable importance of prediction (VIP). The study area was an olive grove, located at Montecorvino Rovella (Salerno, southwestern Italy), characterized by a calcaric soil (Leptic Calcisols) and (Luvic Phaeozem), with a low content of TOC (mean 2.03 g kg^?1), caused by a low-intensity farming. Results of univariate PLSR analyses showed a good agreement between measured and predicted values both for TOC (R²: 0.66) and total carbonate content (R²: 0.93), when pH, electrical conductivity (EC) and absorbance spectra were used as predictors. The best results were obtained using as pre-treatments of the spectral data: 1) standard normal variate (SNV); 2) Savitzky-Golay algorithm; 3) first derivative. Variable Importance for Prediction (VIP) statistics showed to be a good tool to gain insights in TOC composition also when its content is low and influenced by carbonate.     

Estimating the fatty acid composition of the oil in intact-seed rapeseed (Brassica napus L.) by near-infrared reflectance spectroscopy

The objective of this work was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid method to estimate the fatty acid composition of the oil in intact-seed samples of rapeseed. A total of 549 samples (3 g intact seed) from selected mutant and breeding lines were scanned by NIRS, and 220 of them were selected and scanned again by using two different adapters, which reduced the sample size to 300 and 60 mg, respectively. Selected samples were analysed by gas liquid chromatography and calibration equations for individual fatty acids were developed. Calibrations for oleic, linoleic, linolenic, and erucic acid were highly accurate, with values of r² in cross validation from 0.95 to 0.98 (samples of 3 g), from 0.93 to 0.97 (300 mg), and from 0.84 to 0.96 (60 mg). Calibrations for palmitic and stearic acid were less accurate, with values of r² in cross validation always lower than 0.8, probably because of the narrow range available for these fatty acids. The accuracy of the calibration equations for eicosenoic acid was very low (r² = 0.69 in 3 g samples), although improved equations were developed (r² from 0.78 to 0.91) when the relationship between erucic and eicosenoic acid was taken into account. We conclude that NIRS is a powerful technique to estimate the fatty acid composition of the oil in rapeseed, provided that samples covering a wide range of fatty acid levels are available, with the advantage that such estimation is possible with few additional costs when NIRS is used for the determination of other seed quality traits. This revised version was published online in July 2006 with corrections to the Cover Date.     

远红外干燥箱的干燥均匀性研究

测定并分析了４种状况下远红外干燥箱体内各处温度、物料水分的差异。结果表明箱体内各点的温度和物为不分含量并不相同,循环风机工作或和排湿风机联合工作时均匀性较好。     

Durability of isocyanate resin adhesives for wood I: Thermal properties of isocyanate resin cured with water

The thermal properties of isocyanate (IC) resin cured with water were studied using dynamic mechanical analysis (DMA) and Fourier transform infrared spectroscopy. The thermal properties of cured phenol formaldehyde (PF) resin were also studied for comparison purposes. The DMA specimens were prepared using a unique technique. The relation between the mechanical and chemical changes of the resin during DMA was clarified. The cured PF resin had better thermal stability than the IC resin cured with water. The improvement of thermal stability in cured IC resin by heat treatment was considered to be less effective. The effect of the heating rate on the mechanical properties was also investigated. The apparent activation energy in the thermal degradation of cured IC resin was calculated based on the results obtained.Part of this paper was presented at the 47th Annual Meeting of the Japan Wood Research Society, Kochi, April 1997     

Variability for the fatty acid composition of the seed oil in a germplasm collection of the genus Brassica

A germplasm collection consisting of 1475 entries from 21 species of Brassica, including 36 lower taxa, was evaluated for the fatty acid composition of the seed oil. A total of 358 entries representing the taxonomic variability in the collection were selected and analysed by gas-liquid chromatography (GLC). The remaining 1117 entries were analysed by near-infrared reflectance spectroscopy (NIRS), after developing multi-species calibration equations. The results demonstrated that NIRS is an effective technique to assess variability for oleic, linoleic, linolenic and erucic acid in intact-seed samples of multiple Brassica species, provided that calibration equations be developed from sets containing large taxonomic and chemical variability. Some fatty acid ratios were used to estimate the efficiency of the different biosynthetic pathways. Two well-defined patterns were observed. The first one was characterised by high elongation efficiency and accumulation of high levels of erucic acid. The highest erucic acid content (>55% of the total fatty acids) was found in the cultivated species B. napus L., B. oleracea L., and B. rapa L., and in the wild species B. incana Tenore, B. rupestris Raf., and B. villosa Bivona-Bernardi, the three latter belonging to the B. oleracea group (n=9). The second pattern was characterised by high desaturation efficiency, resulting in the accumulation of high levels of the polyunsaturated linoleic and linolenic acid (up to more than 55%). The highest levels of these fatty acids were found in samples of B. elongata Ehrh., especially of the var. integrifolia Boiss. The utility of the reported variability for plant breeding is discussed.     

基于傅里叶变换近红外光谱的籽棉含水率无损检测

为了实现对籽棉含水率的快速、无损检测,该研究采用傅里叶变换近红外光谱技术建立籽棉含水率定量检测模型。首先探究了籽棉样本密度对于光谱曲线的影响,该研究发现样本密度大小对光谱曲线影响显著,密度越小光谱信号越强,当样品密度不低于0.088 6 g/cm³时,光谱曲线变化趋于平稳。通过采集籽棉样本在3 900～11 000 cm^-1波数范围的吸光度光谱数据,并应用了9种预处理方法对原始光谱数据进行处理。发现一阶导数结合消除趋势(first derivative-detrending,FD-DT)预处理方法在偏最小二乘回归(partial least squares regression,PLSR)模型建立时表现最佳。使用了竞争自适应重复加权法(competitive adaptive reweighted sampling,CARS)、信息增益法(information gain,IG)、连续投影法(successive projections algorithm,SPA)和相关系数(correlation coefficient,CC)等算法,来获...     

Use of near infrared spectroscopy to determine biological and chemical characteristics of organic layers under spruce and beech stands

The chemical composition of organic layers of forest soils shows a high spatial variability and fast methods may be required for its study at a landscape level. The objective was to assess the applicability of near infrared spectroscopy (NIRS) to measure several chemical and biological properties of organic layers in spruce, beech, and mixed spruce‐beech stands. Spectra in the VIS‐NIR region (400—2500 nm) were recorded for 406 samples representing Oi, Oe, and Oa layers of forest soils from Solling (Germany), 195 of them were used for calibration and 211 for validation. The calibration equations for each constituent were developed using the whole spectrum (0^th to 3^rd derivative). Humus samples were analyzed for contents of C and N and contents of P, S, Na, K, Ca, Mg, Mn, Fe, and Al after pressure digestion in HNO₃. Additionally, basal respiration and microbial C (C_mic) were measured. NIRS predicted well the contents of C, N, P, S, Ca, Na, K, Fe, and Al and C/N and C/P ratios: the regression coefficients (a) of a linear regression (measured against predicted values) ranged from 0.9 to 1.1, and the correlation coefficients (r) were greater or equal 0.9. C_mic (a = 0.87, r = 0.83) was predicted satisfactorily, whereas the prediction of the basal respiration (a = 0.74, r = 0.87) was less satisfactory. Due to liming of some of the plots NIRS failed to predict contents of Mg (a = 1.27, r = 0.68). For all chemical and biological characteristics the best prediction performances were achieved using the whole sample population. Splitting the samples into smaller groups according to a dominant tree species or an organic layer did not improve the predictions.<?show $6#>     

内型异莰烷基甲醇及其衍生物的NMR研究

利用1H NMR、13C NMR、DEPT等一维和1H-1H COSY、HSQC、HMBC及1H-1H NOESY等二维核磁共振波谱技术确定了6种内型异莰烷基甲醇及其衍生物的结构,并对其1H NMR和13C NMR信号进行了全归属,初步探讨了取代基对化学位移的影响.此6种化合物的核磁数据可作为该类化合物的参考.     

Classification approaches for sorting maize (Zea mays subsp. mays) haploids using single-kernel near-infrared spectroscopy

Doubled haploids (DHs) are an important breeding tool for creating maize inbred lines. One bottleneck in the DH process is the manual separation of haploids from among the much larger pool of hybrid siblings in a haploid induction cross. Here, we demonstrate the ability of single-kernel near-infrared reflectance spectroscopy (skNIR) to identify haploid kernels. The skNIR is a high-throughput device that acquires an NIR spectrum to predict individual kernel traits. We collected skNIR data from haploid and hybrid kernels in 15 haploid induction crosses and found significant differences in multiple traits such as percent oil, seed weight, or volume, within each cross. The two kernel classes were separated by their NIR profile using Partial Least Squares Linear Discriminant Analysis (PLS-LDA). A general classification model, in which all induction crosses were used in the discrimination model, and a specific model, in which only kernels within a specific induction cross, were compared. Specific models outperformed the general model and were able to enrich a haploid selection pool to above 50% haploids. Applications for the instrument are discussed.     

Identification of genetic variation in Brassica napus seeds for tocopherol content and composition using near‐infrared spectroscopy technique

Tocopherol is an essential fat‐soluble nutrient for humans. Increasing the tocopherol content in Brassica napus seeds can add value to rapeseed vegetable oil; this has become an important breeding target. However, there is no efficient and non‐destructive method for selecting rapeseed accessions with high tocopherol contents. Here, we report the first near‐infrared reflectance spectroscopy (NIRS)‐based technique for predicting rapeseed tocopherol content. Individual seed tocopherol compositions were estimated from 373 rapeseed genotypes of different origins. This method and chemical methods produced comparable predicted values of the tocopherol constituents in the seeds. Three equations were generated for the prediction of tocopherol content by using a modified partial least squares (MPLS) model. The total tocopherol content for the determination coefficient of cross‐validation (R²_cv) (0.74), determination coefficient (RSQ) (0.76) and one minus the ratio of unexplained variance to total variance (1‐VR) (0.65) values indicates a strong correlation between the calibration and validation sets. Overall, our model confirmed the NIRS method as feasible for predicting tocopherol content in rapeseed and as an efficient screening tool for future breeding programs.