Pub Date : 2021-04-22DOI: 10.1177/0967033520982361
E. Bobasa, M. Netzel, D. Cozzolino, A. Phan, Y. Sultanbawa
Recent research has shown the potential of portable and handheld NIR instruments to monitor and measure the composition of fruits and vegetables. Current research has also shown the possibility of using portable instruments as tools to monitor composition along the entire food value chain. The objective of this study was to evaluate two sample presentation methods (dry powder and fruit puree) to measure total soluble solids (TSS) and moisture (M) in wild harvested Kakadu plum (KP) (Terminalia ferdinandiana, Combretaceae). Kakadu plum is an endemic plant of Australia that contains high concentrations of vitamin C, ellagic acid as well as other bioactive compounds. These properties make this plant of high economic and social importance for the Aboriginal communities of Australia. Fruit samples were wild harvested in January 2020 from locations in the Kimberley region (Western Australia, Australia) and analysed using both reference and NIR spectroscopic methods. The SECV and RPD values in cross validation were 0.65% (RPD: 2.2) and 0.22% (RPD: 4.2) to predict M and TSS in the KP dry powder samples. The SECV and RPD values obtained in cross validation for the KP fruit puree samples were 0.56% (RPD: 2.8) and 0.24% (RPD: 3.8) for M and TSS, respectively. The results of this study demonstrated the ability of NIR spectroscopy to measure M and TSS in wild harvest fruit. These findings can be also utilised by the Aboriginal communities to develop a grading/sorting system to rapidly screen and evaluate relevant chemical parameters associated with fruit quality and safety.
{"title":"Measurement of total soluble solids and moisture in puree and dry powder of Kakadu plum (Terminalia ferdinandiana) samples using hand-held near infrared spectroscopy","authors":"E. Bobasa, M. Netzel, D. Cozzolino, A. Phan, Y. Sultanbawa","doi":"10.1177/0967033520982361","DOIUrl":"https://doi.org/10.1177/0967033520982361","url":null,"abstract":"Recent research has shown the potential of portable and handheld NIR instruments to monitor and measure the composition of fruits and vegetables. Current research has also shown the possibility of using portable instruments as tools to monitor composition along the entire food value chain. The objective of this study was to evaluate two sample presentation methods (dry powder and fruit puree) to measure total soluble solids (TSS) and moisture (M) in wild harvested Kakadu plum (KP) (Terminalia ferdinandiana, Combretaceae). Kakadu plum is an endemic plant of Australia that contains high concentrations of vitamin C, ellagic acid as well as other bioactive compounds. These properties make this plant of high economic and social importance for the Aboriginal communities of Australia. Fruit samples were wild harvested in January 2020 from locations in the Kimberley region (Western Australia, Australia) and analysed using both reference and NIR spectroscopic methods. The SECV and RPD values in cross validation were 0.65% (RPD: 2.2) and 0.22% (RPD: 4.2) to predict M and TSS in the KP dry powder samples. The SECV and RPD values obtained in cross validation for the KP fruit puree samples were 0.56% (RPD: 2.8) and 0.24% (RPD: 3.8) for M and TSS, respectively. The results of this study demonstrated the ability of NIR spectroscopy to measure M and TSS in wild harvest fruit. These findings can be also utilised by the Aboriginal communities to develop a grading/sorting system to rapidly screen and evaluate relevant chemical parameters associated with fruit quality and safety.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"201 - 206"},"PeriodicalIF":1.8,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0967033520982361","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44738945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-22DOI: 10.1177/09670335211008257
Wanhong Lu, R. Arnold, Chubiao Wang, Yan Lin, Jianzhong Luo, R. Meder, Yan Yang
Understanding the rules of genetic recombination in controlled pollination directly related to the selection of parental genotypes and the utilization of heterosis, and genotype identification is a primary study of the genetic rules. The aims of this study were to investigate the ability of near infrared (NIR) spectroscopy to accurately and efficiently discriminate pure species and hybrids within the genus of Eucalyptus, to evaluate the transmission of genetic pedigree in control pollination, and reveal the genetic variation within the genotypes studied. NIR spectra were collected both from fresh leaves and dried, milled leaves of seedlings from pure species E. urophylla and E. grandis, and their F1 hybrids. Principal component analysis (PCA) scores plots of NIR spectra from fresh leaves and dry, milled powder from pure species showed clear segregation, although the species clusters were scattered, suggesting different base genetics and high genetic variation within families of the two pure species. Classification using soft independent modelling of class analogy of the NIR spectra of dried leaves was significantly better than using spectra acquired on fresh leaves, meaning the water content had an effect on the analysis. The projections and orthogonal distance between hybrids and parents, as calculated using PCA models, demonstrated the visualized spectral distance between each hybrid and the parents was very different. Clouds of individuals within a hybrid clusters varied from tightly packed to scattered, which reflected the genetic additive effects inherited from female and male parents were different, and their genetic variation was also different after genetic recombination. The varying response values for partial least squares discriminant analysis prediction verified the conclusions shown by projections and orthogonal distance. The results of this study demonstrate the potential of using NIR spectroscopy to rapidly discriminate taxon. The application of NIR spectroscopy to non-destructively confirm taxonomic identity will greatly facilitate the evaluation of the genetic basis and genetic variation available within breeding populations and for accessing the levels of contamination by non-target pollen in control pollination.
{"title":"Defining Eucalyptus urophylla with its hybrid and the rules of genetic recombination using near infrared spectroscopy","authors":"Wanhong Lu, R. Arnold, Chubiao Wang, Yan Lin, Jianzhong Luo, R. Meder, Yan Yang","doi":"10.1177/09670335211008257","DOIUrl":"https://doi.org/10.1177/09670335211008257","url":null,"abstract":"Understanding the rules of genetic recombination in controlled pollination directly related to the selection of parental genotypes and the utilization of heterosis, and genotype identification is a primary study of the genetic rules. The aims of this study were to investigate the ability of near infrared (NIR) spectroscopy to accurately and efficiently discriminate pure species and hybrids within the genus of Eucalyptus, to evaluate the transmission of genetic pedigree in control pollination, and reveal the genetic variation within the genotypes studied. NIR spectra were collected both from fresh leaves and dried, milled leaves of seedlings from pure species E. urophylla and E. grandis, and their F1 hybrids. Principal component analysis (PCA) scores plots of NIR spectra from fresh leaves and dry, milled powder from pure species showed clear segregation, although the species clusters were scattered, suggesting different base genetics and high genetic variation within families of the two pure species. Classification using soft independent modelling of class analogy of the NIR spectra of dried leaves was significantly better than using spectra acquired on fresh leaves, meaning the water content had an effect on the analysis. The projections and orthogonal distance between hybrids and parents, as calculated using PCA models, demonstrated the visualized spectral distance between each hybrid and the parents was very different. Clouds of individuals within a hybrid clusters varied from tightly packed to scattered, which reflected the genetic additive effects inherited from female and male parents were different, and their genetic variation was also different after genetic recombination. The varying response values for partial least squares discriminant analysis prediction verified the conclusions shown by projections and orthogonal distance. The results of this study demonstrate the potential of using NIR spectroscopy to rapidly discriminate taxon. The application of NIR spectroscopy to non-destructively confirm taxonomic identity will greatly facilitate the evaluation of the genetic basis and genetic variation available within breeding populations and for accessing the levels of contamination by non-target pollen in control pollination.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"236 - 244"},"PeriodicalIF":1.8,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/09670335211008257","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46673783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-19DOI: 10.1177/0967033521999115
H. Shinzawa, Ryota Watanabe, S. Yamane, Maito Koga, Hideaki Hagihara, Junji Mizukado
This paper describes the first in-depth attempt to characterize thermally induced aging of polypropylene (PP) samples by near infrared (NIR) spectroscopy. Significant levels of variation in NIR bands associated with short (amorphous-dominated) and long (crystalline-dominated) helices was readily captured when PP samples were subjected to thermal aging treatment. Partial least squares (PLS) regression models derived from the NIR spectra indicated significant level of correlation between the actual and predicted elongations of the samples. Analysis of PLS scores and two-dimensional (2D) correlation spectra derived from the aged PP samples revealed inner working mechanism of the regression model. Namely, the aging treatment essentially induces compositional change in crystalline and amorphous structures of the PP samples, which eventually affect the variation of the PLS scores. Thus, by utilizing the scores, it becomes possible to predict the change in the elongation property of the aged PP sample.
{"title":"Aging of polypropylene probed by near infrared spectroscopy","authors":"H. Shinzawa, Ryota Watanabe, S. Yamane, Maito Koga, Hideaki Hagihara, Junji Mizukado","doi":"10.1177/0967033521999115","DOIUrl":"https://doi.org/10.1177/0967033521999115","url":null,"abstract":"This paper describes the first in-depth attempt to characterize thermally induced aging of polypropylene (PP) samples by near infrared (NIR) spectroscopy. Significant levels of variation in NIR bands associated with short (amorphous-dominated) and long (crystalline-dominated) helices was readily captured when PP samples were subjected to thermal aging treatment. Partial least squares (PLS) regression models derived from the NIR spectra indicated significant level of correlation between the actual and predicted elongations of the samples. Analysis of PLS scores and two-dimensional (2D) correlation spectra derived from the aged PP samples revealed inner working mechanism of the regression model. Namely, the aging treatment essentially induces compositional change in crystalline and amorphous structures of the PP samples, which eventually affect the variation of the PLS scores. Thus, by utilizing the scores, it becomes possible to predict the change in the elongation property of the aged PP sample.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"259 - 268"},"PeriodicalIF":1.8,"publicationDate":"2021-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0967033521999115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44179597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-17DOI: 10.1177/09670335211007673
Hamzad Fahmi Ahmad Jani, R. Meder, H. A. Hamid, S. M. Razali, K. Yusoff
Knowledge of soil physical and chemical properties is vital to the optimal growing performance of agricultural crops, including plantation forest trees. Near infrared (NIR) spectroscopy has been shown to be a tool that enables rapid and low-cost assessment of soils, however its use in forest plantations has been slow to develop. This study shows the development of calibrations for total organic carbon, total nitrogen and soil pH using a handheld NIR spectrometer for soils at three sites in Sabah, Malaysia. Soil samples were collected, dried, milled and scanned after which they were analysed using standard chemical methods to obtain total organic carbon (TOC) and total nitrogen (TN). Partial least squares regression was used to develop calibrations between reference data and NIR spectra and validated using an independent sample set. The calibration of soil pH is made using a subset of samples across A- and B-horizons for samples from two of the three sites. The most effective spectral pre-treatment was the standard normal variate for TOC and TN while the Savitzky-Golay first derivative was the best pre-treatment for predicting soil pH. Principal component analysis was performed on the raw NIR spectra of all samples to confirm that the samples from different sites were able to be used in a single regression analysis. Kennard-Stone selection was used to create calibration sets and validation sets from the combined spectra from all sites and both soil horizons. Calibrations were also developed independently on the A- and B-horizon samples, but there were insufficient sample numbers to utilize an independent validation set. The coefficients of determination for the validation set (r2p) were 0.77 and 53 for TOC and TN respectively while the root mean square error of prediction (RMSEP) was 0.44 g 100 g−1 for TOC and 0.051 g 100 g−1 for TN. In addition, it showcases the application of these calibrations to provide spatial assessment of two differing micro-sites within a single Eucalyptus pellita progeny breeding trial. Combined with the potential to monitor foliar nutrients, the ability to obtain high spatial details of soil composition will assist tree plantation growers and also other agricultural producers, such as oil palm plantation managers, to better manage their soil and fertiliser regimes.
土壤物理和化学性质的知识对于农业作物（包括人工林树木）的最佳生长性能至关重要。近红外光谱已被证明是一种能够快速、低成本评估土壤的工具，但其在森林种植园中的应用进展缓慢。这项研究显示了使用手持近红外光谱仪对马来西亚沙巴三个地点的土壤进行总有机碳、总氮和土壤pH校准的进展。收集、干燥、研磨和扫描土壤样本，然后使用标准化学方法对其进行分析，以获得总有机碳（TOC）和总氮（TN）。偏最小二乘回归用于在参考数据和近红外光谱之间进行校准，并使用独立样本集进行验证。土壤pH值的校准是使用三个地点中两个地点的a层和B层样本的子集进行的。最有效的光谱预处理是TOC和TN的标准正态变量，而Savitzky Golay一阶导数是预测土壤pH的最佳预处理。对所有样品的原始近红外光谱进行主成分分析，以确认来自不同地点的样品能够用于单次回归分析。Kennard-Stone选择用于根据所有场地和两个土层的组合光谱创建校准集和验证集。校准也在A层和B层样本上独立开发，但样本数量不足，无法使用独立的验证集。TOC和TN的验证集决定系数（r2p）分别为0.77和53，而预测均方根误差（RMSEP）为0.44 g 100 g−1表示TOC和0.051 g 100 g−1的TN。此外，它还展示了这些校准的应用，以在单一的白皮桉后代育种试验中提供两个不同微位点的空间评估。结合监测叶面养分的潜力，获得土壤成分的高空间细节的能力将有助于植树造林种植者和其他农业生产者，如油棕种植园管理者，更好地管理他们的土壤和肥料制度。
{"title":"Near infrared spectroscopy of plantation forest soil nutrients in Sabah, Malaysia, and the potential for microsite assessment","authors":"Hamzad Fahmi Ahmad Jani, R. Meder, H. A. Hamid, S. M. Razali, K. Yusoff","doi":"10.1177/09670335211007673","DOIUrl":"https://doi.org/10.1177/09670335211007673","url":null,"abstract":"Knowledge of soil physical and chemical properties is vital to the optimal growing performance of agricultural crops, including plantation forest trees. Near infrared (NIR) spectroscopy has been shown to be a tool that enables rapid and low-cost assessment of soils, however its use in forest plantations has been slow to develop. This study shows the development of calibrations for total organic carbon, total nitrogen and soil pH using a handheld NIR spectrometer for soils at three sites in Sabah, Malaysia. Soil samples were collected, dried, milled and scanned after which they were analysed using standard chemical methods to obtain total organic carbon (TOC) and total nitrogen (TN). Partial least squares regression was used to develop calibrations between reference data and NIR spectra and validated using an independent sample set. The calibration of soil pH is made using a subset of samples across A- and B-horizons for samples from two of the three sites. The most effective spectral pre-treatment was the standard normal variate for TOC and TN while the Savitzky-Golay first derivative was the best pre-treatment for predicting soil pH. Principal component analysis was performed on the raw NIR spectra of all samples to confirm that the samples from different sites were able to be used in a single regression analysis. Kennard-Stone selection was used to create calibration sets and validation sets from the combined spectra from all sites and both soil horizons. Calibrations were also developed independently on the A- and B-horizon samples, but there were insufficient sample numbers to utilize an independent validation set. The coefficients of determination for the validation set (r2p) were 0.77 and 53 for TOC and TN respectively while the root mean square error of prediction (RMSEP) was 0.44 g 100 g−1 for TOC and 0.051 g 100 g−1 for TN. In addition, it showcases the application of these calibrations to provide spatial assessment of two differing micro-sites within a single Eucalyptus pellita progeny breeding trial. Combined with the potential to monitor foliar nutrients, the ability to obtain high spatial details of soil composition will assist tree plantation growers and also other agricultural producers, such as oil palm plantation managers, to better manage their soil and fertiliser regimes.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"148 - 157"},"PeriodicalIF":1.8,"publicationDate":"2021-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/09670335211007673","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43081120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-15DOI: 10.1177/0967033520982366
Zhaoqiong Jiang, Yiping Du, F. Cheng, Feiyu Zhang, Wuye Yang, Yinran Xiong
The objective of this study was to develop a multiple linear regression (MLR) model using near infrared (NIR) spectroscopy combined with chemometric techniques for soluble solids content (SSC) in pomegranate samples at different storage periods. A total of 135 NIR diffuse reflectance spectra with the wavelength range of 950-1650 nm were acquired from pomegranate arils. Based upon sampling error profile analysis, outlier diagnosis was conducted to improve the stability of the model, and four outliers were removed. Several pretreatment and variable selection methods were compared using partial least squares (PLS) regression models. The overall results demonstrated that the pretreatment using the first derivative (1D) was very effective and the variable selection method of stability competitive adaptive re-weighted sampling (SCARS) was powerful for extracting feature variables. The equilibrium performance of 1D-SCARS-PLS regression model over ten repeats was similar to 1D-PLS regression model, so that the advantage of wavelength selection was inconspicuous in PLS regression model. However, the number of variables selected by 1D-SCARS was less than 9, which was enough to establish a simple MLR model. The performance of MLR model for SSC of pomegranate arils based on 1D-SCARS achieved a root-mean-square error of calibration of 0.29% and prediction of 0.31%. This strategy combining variable selection method with MLR may have a broad prospect in the application of NIR spectroscopy due to its simplicity and robustness.
{"title":"A simple multiple linear regression model in near infrared spectroscopy for soluble solids content of pomegranate arils based on stability competitive adaptive re-weighted sampling","authors":"Zhaoqiong Jiang, Yiping Du, F. Cheng, Feiyu Zhang, Wuye Yang, Yinran Xiong","doi":"10.1177/0967033520982366","DOIUrl":"https://doi.org/10.1177/0967033520982366","url":null,"abstract":"The objective of this study was to develop a multiple linear regression (MLR) model using near infrared (NIR) spectroscopy combined with chemometric techniques for soluble solids content (SSC) in pomegranate samples at different storage periods. A total of 135 NIR diffuse reflectance spectra with the wavelength range of 950-1650 nm were acquired from pomegranate arils. Based upon sampling error profile analysis, outlier diagnosis was conducted to improve the stability of the model, and four outliers were removed. Several pretreatment and variable selection methods were compared using partial least squares (PLS) regression models. The overall results demonstrated that the pretreatment using the first derivative (1D) was very effective and the variable selection method of stability competitive adaptive re-weighted sampling (SCARS) was powerful for extracting feature variables. The equilibrium performance of 1D-SCARS-PLS regression model over ten repeats was similar to 1D-PLS regression model, so that the advantage of wavelength selection was inconspicuous in PLS regression model. However, the number of variables selected by 1D-SCARS was less than 9, which was enough to establish a simple MLR model. The performance of MLR model for SSC of pomegranate arils based on 1D-SCARS achieved a root-mean-square error of calibration of 0.29% and prediction of 0.31%. This strategy combining variable selection method with MLR may have a broad prospect in the application of NIR spectroscopy due to its simplicity and robustness.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"140 - 147"},"PeriodicalIF":1.8,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0967033520982366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42444228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-15DOI: 10.1177/0967033521999745
Yue Ma, Yichao Xu, Hui Yan, Guozheng Zhang
The gender identification of silkworm pupae is a critical step in the sericulture industry's breeding process. In this study, a low cost, short-wavelength (815-1075 nm) near infrared (NIR) spectrometer combined with multivariate spectra evaluation methods was used to establish calibration models for the on-line identification of female and male pupae of eight silkworm varieties. The diffuse reflection short-wavelength spectra were recorded, and then principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares discriminant analysis (PLSDA) were tested for calibration model development. The PCA and LDA results showed, that spectral differences between the female and male silkworm pupae existed, however, the two evaluation techniques could not separate the female and male silkworm pupae with the required accuracy. The PLSDA calibration models, on the other hand, could separate the pupae according to their gender with the necessary prediction accuracy of >98%. Thus, it has been proved, that a low-cost, short-wavelength range NIR spectrometer in combination with a PLSDA calibration routine can be successfully applied for the reliable on-line identification of female and male silkworm pupae.
{"title":"On-line identification of silkworm pupae gender by short-wavelength near infrared spectroscopy and pattern recognition technology","authors":"Yue Ma, Yichao Xu, Hui Yan, Guozheng Zhang","doi":"10.1177/0967033521999745","DOIUrl":"https://doi.org/10.1177/0967033521999745","url":null,"abstract":"The gender identification of silkworm pupae is a critical step in the sericulture industry's breeding process. In this study, a low cost, short-wavelength (815-1075 nm) near infrared (NIR) spectrometer combined with multivariate spectra evaluation methods was used to establish calibration models for the on-line identification of female and male pupae of eight silkworm varieties. The diffuse reflection short-wavelength spectra were recorded, and then principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares discriminant analysis (PLSDA) were tested for calibration model development. The PCA and LDA results showed, that spectral differences between the female and male silkworm pupae existed, however, the two evaluation techniques could not separate the female and male silkworm pupae with the required accuracy. The PLSDA calibration models, on the other hand, could separate the pupae according to their gender with the necessary prediction accuracy of >98%. Thus, it has been proved, that a low-cost, short-wavelength range NIR spectrometer in combination with a PLSDA calibration routine can be successfully applied for the reliable on-line identification of female and male silkworm pupae.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"207 - 215"},"PeriodicalIF":1.8,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0967033521999745","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46940568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-15DOI: 10.1177/0967033521999118
S. Shukla, S. Shashikala, M. Sujatha
Near infrared (NIR) spectroscopy is developing as an advanced and non-invasive tool in the wood, wood products and forestry sectors. It may be applied as a rapid and cost effective technique for assessment of different wood quality parameters of timber species. In the present study, NIR spectra of heartwood samples of Tectona grandis (teak) were collected before measuring fibre morphological parameters (fibre length, fibre diameter and fibre lumen diameter)and main chemical constituents (cellulose, hemicellulose, lignin and extractives) using maceration and wet chemistry methods respectively. Multivariate partial least squares (PLS) regression was applied to develop the calibration models between measured values of wood parameters and NIR spectral data. Pre-processing of NIR spectra demonstrated better predictions based on higher values of correlation coefficient for estimation (R2), validation (Rcv 2 ), ratio of performance to deviation (RPD), and lower values of root mean square errors of estimation (RMSEE), cross-validation (RMSECV) and number of latent variable (rank). Internal cross-validation was used to find the optimum rank. Robust calibrations models with high R2 (>0.87), low errors and high RPD values (> 2.93) were observed from PLS analysis for fibre morphological parameters and main chemical constituents of teak. These linear models may be applied for rapid and cost effective estimation of different fibre parameters and chemical constituents in routine testing and evaluation procedures for teak.
{"title":"Non-destructive estimation of fibre morphological parameters and chemical constituents of Tectona grandis L.f. wood by near infrared spectroscopy","authors":"S. Shukla, S. Shashikala, M. Sujatha","doi":"10.1177/0967033521999118","DOIUrl":"https://doi.org/10.1177/0967033521999118","url":null,"abstract":"Near infrared (NIR) spectroscopy is developing as an advanced and non-invasive tool in the wood, wood products and forestry sectors. It may be applied as a rapid and cost effective technique for assessment of different wood quality parameters of timber species. In the present study, NIR spectra of heartwood samples of Tectona grandis (teak) were collected before measuring fibre morphological parameters (fibre length, fibre diameter and fibre lumen diameter)and main chemical constituents (cellulose, hemicellulose, lignin and extractives) using maceration and wet chemistry methods respectively. Multivariate partial least squares (PLS) regression was applied to develop the calibration models between measured values of wood parameters and NIR spectral data. Pre-processing of NIR spectra demonstrated better predictions based on higher values of correlation coefficient for estimation (R2), validation (Rcv 2 ), ratio of performance to deviation (RPD), and lower values of root mean square errors of estimation (RMSEE), cross-validation (RMSECV) and number of latent variable (rank). Internal cross-validation was used to find the optimum rank. Robust calibrations models with high R2 (>0.87), low errors and high RPD values (> 2.93) were observed from PLS analysis for fibre morphological parameters and main chemical constituents of teak. These linear models may be applied for rapid and cost effective estimation of different fibre parameters and chemical constituents in routine testing and evaluation procedures for teak.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"168 - 178"},"PeriodicalIF":1.8,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0967033521999118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46141594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-13DOI: 10.1177/09670335211006614
Johannes Richter, A. Kessler, T. Weber, H. Heissler, Michaela Gerstenlauer, M. Wüst, R. Stamminger
Near infrared (NIR) measurements have been used for several years to examine the processes taking place in the dishwasher during dishwashing. It is possible to differentiate between the soil components butterfat, oatmeal and egg-yolk and to determine their concentration in the dishwashing liquor quantitatively. Consequently, time-consuming dishwashing tests can be avoided by weighing the dishes. However, this method is also based on a small number of NIR measurements which are carried out intrusively during the dishwashing process, i.e. outside the dishwasher. These few NIR measurements make it difficult to investigate the dynamics of a dishwashing process. In this study, the development, testing and usage of a new online tracking measuring system is presented. The latter was used to perform 38 dishwashing processes, each containing 51 NIR spectra, to develop a calibration model using the partial least squares regression method with cross-validation. This new online tracking measuring system, based on the calibration, can determine the concentrations of three different soil components in the dishwashing liquor during automatic dishwashing. By recording the 51 spectra, it is possible to display a tracking curve for each soil component, i.e. the concentration courses of the dishwashing process over time. This results in a significantly better time resolution and it was possible to investigate the first dynamic part of the tracking curve, i.e. the beginning of the dishwashing process. This could lead to the opportunity to change the state of the dishwasher depending on the concentrations detected in the first step and, secondly, to a more environmentally friendly and cost-reducing dishwashing process.
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Pub Date : 2021-04-13DOI: 10.1177/09670335211007575
A. E. Ehounou, D. Cornet, L. Desfontaines, Carine Marie-Magdeleine, E. Malédon, E. Nudol, G. Beurier, L. Rouan, P. Brat, M. Léchaudel, C. Noûs, A. N’guetta, A. Kouakou, G. Arnau
Despite the importance of yam (Dioscorea spp.) tuber quality traits, and more precisely texture attributes, high-throughput screening methods for varietal selection are still lacking. This study sets out to define the profile of good quality pounded yam and provide screening tools based on predictive models using near infrared reflectance spectroscopy. Seventy-four out of 216 studied samples proved to be moldable, i.e. suitable for pounded yam. While samples with low dry matter (<25%), high sugar (>4%) and high protein (>6%) contents, low hardness (<5 N), high springiness (>0.5) and high cohesiveness (>0.5) grouped mostly non-moldable genotypes, the opposite was not true. This outline definition of a desirable chemotype may allow breeders to choose screening thresholds to support their choice. Moreover, traditional near infrared reflectance spectroscopy quantitative prediction models provided good prediction for chemical aspects (R2 > 0.85 for dry matter, starch, protein and sugar content), but not for texture attributes (R2 < 0.58). Conversely, convolutional neural network classification models enabled good qualitative prediction for all texture parameters but hardness (i.e. an accuracy of 80, 95, 100 and 55%, respectively, for moldability, cohesiveness, springiness and hardness). This study demonstrated the usefulness of near infrared reflectance spectroscopy as a high-throughput way of phenotyping pounded yam quality. Altogether, these results allow for an efficient screening toolbox for quality traits in yams.
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Pub Date : 2021-04-12DOI: 10.1177/09670335211007971
A. Alwi, R. Meder, Y. Japarudin, H. A. Hamid, R. Sanusi, K. Yusoff
Eucalyptus pellita F. Muell. has become an important tree species in the forest plantations of SE Asia, and in Malaysian Borneo in particular, to replace thousands of hectares of Acacia mangium Willd. which has suffered significant loss caused by Ceratocystis manginecans infection in Sabah, Malaysia. Since its first introduction at a commercial scale in 2012, E. pellita has been planted in many areas in the region. The species replacement requires new silvicultural practices to induce the adaptability of E. pellita to grow in the region and this includes relevant research to optimise such regimes as planting distance, pruning, weeding practices and nutrition regimes. In this present study, the nutritional status of the foliage was investigated with the aim to develop near infrared spectroscopic calibrations that can be used to monitor and quantify nutrient status, particularly total foliar nitrogen (N) and phosphorus (P) in the field. Spectra acquired on fresh foliage in situ on the tree could be used to predict N and P with accuracy suitable for operational decision-making regards fertiliser application. If greater accuracy is required, spectra acquired on dry, milled foliage could be used to predict N and P within a relative error of 10% (R2c, r2CV, RMSEP, RPD = 0.77, 0.71, 0.02 g 100 g-1, 1.9 for foliar P and = 0.90, 0.88, 0.21 g 100 g-1, 3.0 for foliar N on dry, milled foliage). The ultimate application of this is in situ nutrient monitoring, particularly to aid longitudinal studies in fertiliser trial plots and forest operations, as the non-destructive nature of NIR spectroscopy would enable regular monitoring of individual leaves over time without the need to destructively sample them. This would aid the temporal and spatial analysis of field data.
蓝桉。已成为东南亚，特别是马来西亚婆罗洲森林种植园的重要树种，以取代数千公顷的野生相思。在马来西亚沙巴遭受了因锰角鼻虫感染而造成的重大损失。自2012年首次以商业规模引进以来，该地区的许多地区都种植了佩利塔。物种替代需要新的造林措施来诱导褐藻在该地区生长的适应性，这包括优化种植距离、修剪、除草和营养制度等相关研究。在本研究中，研究了叶片的营养状况，目的是建立近红外光谱校准，可用于监测和量化田间营养状况，特别是叶片总氮(N)和总磷(P)。在树的新鲜叶片上获取的光谱可以准确地预测N和P，适合于施肥方面的操作决策。如果需要更高的精度，可以使用干燥、铣削叶片上获得的光谱来预测N和P，相对误差在10%以内(R2c、r2CV、RMSEP、RPD = 0.77、0.71、0.02 g 100 g- 1,1.9，干燥、铣削叶片上叶片N = 0.90、0.88、0.21 g 100 g- 1,3.0)。这种方法的最终应用是就地监测营养物质，特别是协助肥料试验田和森林作业的纵向研究，因为近红外光谱的非破坏性性质将使人们能够长期定期监测单个叶子，而无需破坏性地取样。这将有助于实地数据的时间和空间分析。
{"title":"Near infrared spectroscopy of Eucalyptus pellita for foliar nutrients and the potential for real-time monitoring of trees in fertiliser trial plots","authors":"A. Alwi, R. Meder, Y. Japarudin, H. A. Hamid, R. Sanusi, K. Yusoff","doi":"10.1177/09670335211007971","DOIUrl":"https://doi.org/10.1177/09670335211007971","url":null,"abstract":"Eucalyptus pellita F. Muell. has become an important tree species in the forest plantations of SE Asia, and in Malaysian Borneo in particular, to replace thousands of hectares of Acacia mangium Willd. which has suffered significant loss caused by Ceratocystis manginecans infection in Sabah, Malaysia. Since its first introduction at a commercial scale in 2012, E. pellita has been planted in many areas in the region. The species replacement requires new silvicultural practices to induce the adaptability of E. pellita to grow in the region and this includes relevant research to optimise such regimes as planting distance, pruning, weeding practices and nutrition regimes. In this present study, the nutritional status of the foliage was investigated with the aim to develop near infrared spectroscopic calibrations that can be used to monitor and quantify nutrient status, particularly total foliar nitrogen (N) and phosphorus (P) in the field. Spectra acquired on fresh foliage in situ on the tree could be used to predict N and P with accuracy suitable for operational decision-making regards fertiliser application. If greater accuracy is required, spectra acquired on dry, milled foliage could be used to predict N and P within a relative error of 10% (R2c, r2CV, RMSEP, RPD = 0.77, 0.71, 0.02 g 100 g-1, 1.9 for foliar P and = 0.90, 0.88, 0.21 g 100 g-1, 3.0 for foliar N on dry, milled foliage). The ultimate application of this is in situ nutrient monitoring, particularly to aid longitudinal studies in fertiliser trial plots and forest operations, as the non-destructive nature of NIR spectroscopy would enable regular monitoring of individual leaves over time without the need to destructively sample them. This would aid the temporal and spatial analysis of field data.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":"29 1","pages":"158 - 167"},"PeriodicalIF":1.8,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/09670335211007971","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42694655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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