Advances in coffee tissue culture and its practical applications

Genetic improvement of coffee, an important commercial crop, through classical breeding is slow and cumbersome. Biotechnology offers alternative strategies for generating new and improved coffee varieties, including those resistances to environmental extremes, pests, and diseases, low in caffeine, and with uniform fruit maturation. Large improvements in somatic embryogenesis, development of haploids, and scale-up of micropropagation have been accomplished in the last 5 yr. The recent identification of expressed sequence tags (EST) that are differentially expressed during the infestation of coffee plants by coffee leaf miners and the isolation and cloning of the promoter for the N-methyltransferase gene associated with caffeine production open up the possibility of producing varieties of coffee with new traits. This review provides a summary of in vitro biological advances and directions as to how they could be applied to improve the production and quality of coffee.     

Optical properties of mice's stool in 550 to 1000 nm wavelength range

The aim of this work was to measure optical properties of stool of mice to provide this relevant wavelength‐dependent behavior for optical imaging modalities such as fluorescent molecular tomography and near‐infrared optical tomography. BALB/c nude female mice were studied and optical properties of the stool were determined by employing the inverse adding‐doubling approach. The animals were kept on chlorophyll‐free diet. Nine stool samples were measured. The wavelength‐dependent behavior of absorption and scattering in 550 to 1000 nm range is presented. The reduced scattering spectrum is fitted to the Mie scattering approximation in the near‐infrared (NIR) wavelength range and to the Mie + Rayleigh approximation in visible/NIR range with the fitting coefficients presented. The study revealed that the absorption spectrum of stool can lead to crosstalk with the spectrum of hemoglobin in the NIR range.      

Validation of a Remote Sensing Model to Identify Simulium damnosum s.l. Breeding Sites in Sub-Saharan Africa

Background

Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites.

Methodology/Principal Findings

Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature.

Conclusions/Significance

This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement.     

近红外光谱技术在烟草行业中的应用进展

介绍了近红外光谱分析技术在烟草常规化学成分分析、烟气分析、卷烟配方设计、不同产地模式识别和真假烟鉴别等方面的应用,认为近红外光谱分析技术在烟草行业中正扮演着越来越重要的角色,而且具有十分广阔的应用前景.     

Measurement of hemoglobin in whole blood using a partial least squares regression model with selected second derivative near infrared transmission spectral signals

In this work, we propose a signal selection procedure for determination of hemoglobin (Hb) concentration in whole blood using near infrared (NIR) transmission spectral signals. A dataset of 190 whole blood NIR transmission spectra with reference Hb concentrations was used to evaluate the method. Spectral signals were selected based on the squared correlation coefficient (R(2)) between the signal and the Hb concentration. An improved uninformative variable elimination (UVE) procedure was performed to remove redundant signals from the primary selected signal set. A partial least squares (PLS) regression model was built with the final selected signals and the corresponding Hb concentrations. The results indicate that the proposed method is effective at increasing the predictive power of the NIR-PLS spectral model for determining Hb concentration in whole blood samples.     

Feasibility study on the potential of visible and near infrared reflectance spectroscopy to measure alpaca fibre characteristics

Visible (Vis) and near infrared (NIR) reflectance spectroscopy is a rapid and non-destructive technique that has found many applications in assessing the quality of agricultural commodities, including wool. In this study, Vis and NIR spectroscopy combined with multivariate data analysis was investigated regarding its feasibility in predicting a range of fibre characteristics in raw alpaca wool samples. Mid-side samples (n = 149) were taken from alpacas from a range of colours and ages at shearing time over 4 years (2000 to 2004) and subsequently analysed for fibre characteristics such as mean fibre diameter (MFD) and standard deviation (and coefficient of variation), spin fineness, curvature degree (and standard deviation), comfort factor, medullation percentage (by weight and number in white samples only) using traditional reference laboratory testing methods. Samples were scanned in a large cuvette using a FOSS NIRSystems 6500 monochromator instrument in reflectance mode in the Vis and NIR regions (400 to 2500 nm). Partial least squares (PLS) regression was used to develop a number of calibration models between the spectral and reference data. Mathematical pre-treatment of the spectra (second derivative) as well as various combinations of wavelength range were used in model development. The best calibration model was found when using the NIR region (1100 to 2500 nm) for the prediction of MFD, which had a coefficient of determination in cross-validation (R2) of 0.88 with a root mean square standard error of cross validation (RMSECV) of 2.62 μm. The results show the NIR technique to have promise as a semi-quantitative method for screening purposes. The lack of grease in alpaca wool samples suggests that the technique might find ready application as a rapid measurement technique for preliminary classing of shorn fleeces or, if used directly on the animal, the technology might offer an objective tool to assist in the selection of animals in breeding programmes or shows.     

Forensic visualization of foreign matter in human tissue by near-infrared spectral imaging: methodology and data mining strategies.

BACKGROUND: Rapidity of data acquisition, high image fidelity and large field of view are of tremendous value when looking for chemical contaminants or for the proverbial "needle in the haystack" - in this case foreign inclusions in histologic sections of biopsy or autopsy tissues. Near infrared chemical imaging is one of three chemical imaging techniques (NIR, MIR and Raman) based on vibrational spectroscopy, and provides distinct technical advantages for this application. METHODS: We have chosen to utilize and evaluate near infrared (NIR) imaging for studies of foreign materials in tissue because the experimental configuration is relatively simple, data collection is rapid, and large sample areas can be screened with high image fidelity and spatial resolution. RESULTS: We have shown that NIR imaging can readily find and identify silicone gel inclusions in biological tissue samples. Additionally, preliminary results indicate that spectral signatures in the data set are also potentially sensitive to structural changes in the surrounding tissue that may be induced by the foreign body. CONCLUSIONS: NIR chemical imaging is a powerful, non-destructive tool for localization and identifying foreign contaminants in biological tissue. Preliminary results indicate that NIR imaging is also sensitive enough to differentiate tissue types (perhaps based on collagen structural differences), and provide data on the spatial localization of these components.     

Identification of seed sources and parents of Pinus sylvestris L. using visible–near infrared reflectance spectra and multivariate analysis

The potential of visible (VIS) and near infrared (NIR) spectroscopy for identifying seed sources and parents of Pinus sylvestris L. was studied. Seeds of a single family (clones AC1005 × BD1178) collected from three localities in Sweden—Sävar (north), Röskär (central) and Degeberga (south)—and seeds from four maternal (clone no. BD1032, AC1014, BD1178 and AC1005) and four paternal (Y3020, BD1178, AC1014 and BD1032) parents were used to evaluate the method. VIS and NIR reflectance spectra were recorded on individual seeds using a NIRSystems Model 6500 spectrometer from 400 to 2,498 nm with a resolution of 2 nm. The VIS + NIR spectroscopic data were pre-treated with multiplicative signal correction, and analysed by soft independent modelling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA). The computed models were later applied to classify samples in the external test sets. The results show that seed sources were identified with 100% classification accuracy using PLS-DA models in the VIS + NIR, VIS and NIR regions. The average classification accuracy for maternal parents ranged from 92% to 96%, while paternal parents were identified with 91.2–96% accuracies. The classification accuracy using the SIMCA approach was relatively low for seed sources as well as maternal and paternal parents. It can be concluded that VIS + NIR spectroscopy could be employed as a rapid and non-destructive method for monitoring putative seed sources. The result underscores the prospect of the technique for characterizing seeds based on genotype, thereby serving as a tool in tree improvement and breeding.     

Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis. Published: October 6, 2005 The views presented in this article do not necessarily reflect those of the Food and Drug Administration.     

Near infrared spectroscopy as a tool for the determination of eumelanin in human hair

Eumelanins are brown-black pigments present in the hair and in the epidermis which are acknowledged as protection factors against cell damage caused by ultraviolet radiation. The quantity of eumelanin present in hair has recently been put forward as a means of identifying subjects with a higher risk of skin tumours. For epidemiological studies, chromatographic methods of determining pyrrole-2,3,5-tricarboxylic acid (PTCA; the principal marker of eumelanin) are long, laborious and unsuitable for screening large populations. We suggest near infrared (NIR) spectroscopy as an alternative method of analysing eumelanin in hair samples. PCTA was determined on 93 samples of hair by means of oxidizing with hydrogen peroxide in a basic environment followed by chromatographic separation. The same 93 samples were then subjected to NIR spectrophotometric analysis. The spectra were obtained in reflectance mode on hair samples which had not undergone any preliminary treatment, but had simply been pressed and placed on the measuring window of the spectrophotometer. The PTCA values obtained by means of HPLC were correlated with the near infrared spectrum of the respective samples. A correlation between the PTCA values obtained by means of HPLC and the PTCA values obtained from an analysis of the spectra was obtained using the principal component regression (PCR) algorithm. The correlation obtained has a coefficient of regression (R(2)) of 0.89 and a standard error of prediction (SEP) of 13.8 for a mean value of 108.6 ng PTCA/mg hair. Some considerations about the accuracy of the obtained correlation and the main sources of error are made and some validation results are shown.     

Quantitation of drug content in a low dosage formulation by transmission near infrared spectroscopy

A transmission near infrared (NIR) spectroscopic method has been developed for the nondestructive determination of drug content in tablets with less than 1% weight of active ingredient per weight of formulation (m/m) drug content. Tablets were manufactured with drug concentrations of ∼0.5%, 0.7%, and 1.0% (m/m) and ranging in drug content from 0.71 to 2.51 mg per tablet. Transmission NIR spectra were obtained for 110 tablets that constituted the training set for the calibration model developed with partial least squares regression. The reference method for the calibration model was a validated UV spectrophotometric method. Several data preprocessing methods were used to reduce the effect of scattering on the NIR spectra and base the calibration model on spectral changes related to the drug concentration changes. The final calibration model included the spectral range from 11 216 to 8662 cm⁻¹ the standard normal variate (SNV), and first derivative spectral pretreatments. This model was used to predict an independent set of 48 tablets with a root mean standard error of prediction (RMSEP) of 0.14 mg, and a bias of only −0.05 mg per tablet. The study showed that transmission NIR spectroscopy is a viable alternative for nondestructive testing of low drug content tablets, available for the analysis of large numbers of tablets during process development and as a tool to detect drug agglomeration and evaluate process improvement efforts. Published: March 24, 2006     

In vivo investigation of progressive alterations in rat mammary gland tumors by near-infrared spectroscopy

We have investigated mammary gland tissues of female rats treated with 7,12-dimethylbenz[a]anthracene in sesame oil by a near infrared (NIR) spectroscopy finding that the DNA and water contents in the cancerous tissues were larger than those in the normal tissues but that the lipid content in the former was less than that in the latter. With protein contents, however, little difference was observed between the two. Thus, we used a lipid band around 1725 nm (the first overtone of n-alkane) and a protein band around 2054 nm (a combination band of amide A and amide II of polypeptides) for a quantitative evaluation of malignant changes in the mammary gland tissues. The lipid/protein band intensity ratios were calculated from the spectra of the mammary glands in the control animals and those of the noncancerous and cancerous sites in the treated animals. The lipid/protein ratios in the control animals, in the noncancerous sites, and in the cancerous sites were 1.452 +/- 0.221 (n = 5), 0.728 +/- 0.069 (n = 5), and 0.362 +/- 0.060 (n = 5), respectively. These values were significantly different from each other (P < 0.001). The lipid changes observed by near-infrared (NIR) spectroscopy were confirmed by the results obtained from chemical methods for the evaluation of lipid levels in the same samples. Thus, our NIR spectroscopic method would be able not only to discriminate between cancerous and normal tissues but also to distinguish animals with cancers from normal animals. In addition, as the cancer grew, the lipid band intensity decreased, this band was shifted to higher wavelengths, and collagen peaks appeared in the tissues. These findings were supported by histological examinations of the cancerous and normal tissues. The present study indicates that NIR spectroscopy has high specificity and sensitivity in discriminating cancerous tissues from normal mammary glands in animals and it may offer potential for noninvasive, in vivo diagnosis of female breast cancer in the near future.     

Cu‐doped quantum dots: a new class of near‐infrared emitting fluorophores for bioanalysis and bioimaging

Transition metal ion‐doped quantum dots (QDs) exhibit unique optical and photophysical properties that offer significant advantages over undoped QDs, such as larger Stokes shift to avoid self‐absorption/energy transfer, longer excited‐state lifetimes, wider spectral window, and improved chemical and thermal stability. Among the doped QDs emitters, Cu is widely introduced into the doped QDs as novel, efficient, stable, and tunable optical materials that span a wide spectrum from blue to near‐infrared (NIR) light. Their unique physical and chemical characteristics enable the use of Cu‐doped QDs as NIR labels for bioanalysis and bioimaging. In this review, we discuss doping mechanisms and optical properties of Cu‐doped QDs that are capable of NIR emission. Applications of Cu‐doped QDs in in vitro biosensing and in in vivo bioimaging are highlighted. Moreover, a prospect of the future of Cu‐doped QDs for bioanalysis and bioimaging are also summarized.     

Lead sulfide near-infrared quantum dot bioconjugates for targeted molecular imaging

In this paper, we report the use of lead sulfide quantum dot (PbS QD) bioconjugates as near infrared (NIR) contrast agents for targeted molecular imaging with expanded emission wavelengths beyond 1000 nm. The red-shifted emission band, coupled with the small particle size, which will facilitate clearance, both afford PbS QDs unique properties for noninvasive, high resolution in vivo NIR imaging applications. We have performed imaging experiments at the molecular level using surface-modified PbS NIR QDs, together with our lab-built NIR imaging system. This novel instrumentation and fluorescent contrast agent have enabled us to study the relatively unexplored NIR biomedical imaging spectral region of 900-1200 nm. Preliminary experimental results indicate that PbS-QD/antibody bioconjugates are promising candidates for targeted NIR molecular imaging and future in vivo NIR tissue imaging applications.     

Exploring the Use of Near Infrared (NIR) Reflectance Spectroscopy to Predict Starch Pasting Properties in Whole Grain Barley

This study aimed to evaluate the ability of using near infrared reflectance (NIR) spectroscopy to predict parameters generated by the rapid visco analyser (RVA) in whole grain barley samples to further study starch pasting characteristics in a breeding program. A total of 130 whole grain barley samples from the University of Adelaide germplasm collection, harvested over three seasons (2009, 2010 and 2011) were analysed using both NIR and RVA instruments and calibrations developed using partial least squares (PLS) regression. The coefficient of determination in cross validation (R ²) and the standard error in cross validation (SECV) were 0.88 [SECV?=?477.5 (RVU?=?rapid visco units)] for peak viscosity (PV), 0.82 (SECV?=?635.5 RVU) for trough (THR), 0.92 (SECV?=?190.4 RVU) for breakdown (BKD), 0.61 (SECV?=?151.1 RVU) for setback (SET), 0.84 (SECV?=?698.0 RVU) for final viscosity (FV), 0.70 (SECV?=?0.54 s) for time to peak (TTP) and 0.36 (SECV?=?2.2 min) for pasting temperature (PT). We have demonstrated that NIR spectroscopy shows promise as a rapid, non-destructive method to measure PV in whole grain barley. In this context, NIR spectroscopy has the potential to significantly reduce analytical time and cost for screening novel lines for starch properties for pasting properties.     

New estimation method for fatty acid composition in oil using near infrared spectroscopy

The absorption bands of cis-unsaturation and the carbon chain length of the fatty acid moieties in oil appear in the near infrared (NIR) wavelength region, especially around 1600-1800 nm. Using this region, a new estimation method for fatty acid composition analysis is proposed. Because the differences of the original NIR spectra are miniscule even in this region, the second derivative NIR spectra were examined in order to estimate the fatty acid composition in oil exclusively from the spectral patterns obtained. The parameters for calculating the second derivative NIR spectra were examined to make the spectral difference clearer. In any parameter, the absorption band was shifted to the shorter wavelength region when the unsaturation in fatty acid moieties increased, and it was shifted to the longer wavelength region when the carbon chain length increased. When the parameters were correct, this NIR method can estimate the fatty acid composition roughly, but simply, easily, and sometimes nondestructively.     

Influence of morphology on the near-infrared spectra of mycelial biomass and its implications in bioprocess monitoring

Bioprocesses that employ mycelial microorganisms are commercially important. The application of optical techniques for the measurement of biomass in such processes is limited by the morphological heterogeneity exhibited by the mycelial microorganism employed. We investigated the influence of morphology on the near-infrared (NIR) spectra of the biomass of Streptomyces fradiae, a filamentous microorganism, by studying the spectra of mycelial suspensions that were manipulated to generate a range of morphological forms. Computerized image analysis was used to characterize the morphological forms. Principal component analysis was used to assess the spectral variations and study correlations to the manipulated mycelial morphology. Although morphology was found to influence the near infrared transmittance spectra of biomass, the influence was less pronounced than in the visible region, the spectral information at longer wavelengths (1600-2350 nm) showing greater stability to morphological variations. Long-wave NIR spectral information is therefore likely to be more useful in estimating biomass in mycelial bioprocesses. Furthermore, the NIR reflectance spectra of dried biomass were found to show correlations to the morphological variations introduced, suggesting that NIR spectra may be useful in obtaining morphology related information.     

Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes

Key message

Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection to accelerate improvement in grain end-use quality traits of wheat.

Abstract

Grain end-use quality traits are among the most important in wheat breeding. These traits are difficult to breed for, as their assays require flour quantities only obtainable late in the breeding cycle, and are expensive. These traits are therefore an ideal target for genomic selection. However, large reference populations are required for accurate genomic predictions, which are challenging to assemble for these traits for the same reasons they are challenging to breed for. Here, we use predictions of end-use quality derived from near infrared (NIR) or nuclear magnetic resonance (NMR), that require very small amounts of flour, as well as end-use quality measured by industry standard assay in a subset of accessions, in a multi-trait approach for genomic prediction. The NIR and NMR predictions were derived for 19 end-use quality traits in 398 accessions, and were then assayed in 2420 diverse wheat accessions. The accessions were grown out in multiple locations and multiple years, and were genotyped for 51208 SNP. Incorporating NIR and NMR phenotypes in the multi-trait approach increased the accuracy of genomic prediction for most quality traits. The accuracy ranged from 0 to 0.47 before the addition of the NIR/NMR data, while after these data were added, it ranged from 0 to 0.69. Genomic predictions were reasonably robust across locations and years for most traits. Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection for grain end-use quality traits in wheat breeding.

     

近红外光谱技术在稻米特性检测中的应用(综述)

近红外光谱技术是一种新型的检测分析技术,广泛应用于农业、林业、工业、医药以及食品等多个行业领域。文章综述近红外光谱技术在稻米特性检测中的应用概况,包括对大米淀粉、蛋白质和脂肪酸等营养物质的测定,大米糊化特性、粘稠度和食味特性的分析,水稻生长过程中氮、磷、钾和其他营养元素含量的分析,育种研究与品种鉴别,病害、重金属等有害物质以及其他方面。同时,指出该技术在当前检测应用中存在的一些问题,并针对目前发展趋势展望该技术的前景。     

陇中黄土高原春小麦光谱反射特征

通过田间小区试验,测定了3个春小麦品种(高原602、陇春8139和定西24)在不同生育期和不同种植密度的光谱反射率及对应叶面积指数(LAI)和地上生物量,分析了其光谱反射的一般特征和红边参数特征以及光谱变量与LAI和地上生物量的相关性.结果表明:在整个波段内,春小麦冠层光谱表现为高原602＞陇春8139＞定西24,其叶片光谱表现为定西24＞陇春8139＞高原602;春小麦冠层光谱在可见光波段和中红外波段成熟期明显大于孕穗期,而叶片光谱在近红外波段孕穗期明显大于成熟期;随着种植密度的提高,在近红外波段冠层和叶片的光谱反射率逐渐增加;冠层光谱的红边均具有"双峰"现象,从孕穗期到成熟期,冠层红边位置呈现"蓝移"现象;LAI和地上生物量与冠层光谱变量之间存在较好的相关性.