Influence of environmental and instrumental variables on the non-invasive prediction of Brix in pineapple using near infrared spectroscopy

The Brix content of pineapple fruit can be non-invasively predicted from the second derivative of near infrared reflectance spectra. Correlations obtained using a NIRSystems 6500 spectrophotometer through multiple linear regression and modified partial least squares analyses using a post-dispersive configuration were comparable with that from a pre-dispersive configuration in terms of accuracy (e.g. coefficient of determination, R2, 0.73; standard error of cross validation, SECV, 1.01°Brix). The effective depth of sample assessed was slightly greater using the post-dispersive technique (about 20 mm for pineapple fruit), as expected in relation to the higher incident light intensity, relative to the pre-dispersive configuration. The effect of such environmental variables as temperature, humidity and external light, and instrumental variables such as the number of scans averaged to form a spectrum, were considered with respect to the accuracy and precision of the measurement of absorbance at 876 nm, as a key term in the calibration for Brix, and predicted Brix. The application of post-dispersive near infrared technology to in-line assessment of intact fruit in a packing shed environment is discussed.

Non-invasive assessment of pineapple and mango fruit quality using near infra-red spectroscopy

The potential of near infra-red (NIR) spectroscopy for non-invasive measurement of fruit quality of pineapple (Ananas comosus var. Smooth Cayenne) and mango (Magnifera indica var. Kensington) fruit was assessed. A remote reflectance fibre optic probe, placed in contact with the fruit skin surface in a light-proof box, was used to deliver monochromatic light to the fruit, and to collect NIR reflectance spectra (760–2500 nm). The probe illuminated and collected reflected radiation from an area of about 16 cm2. The NIR spectral attributes were correlated with pineapple juice Brix and with mango flesh dry matter (DM) measured from fruit flesh directly underlying the scanned area. The highest correlations for both fruit were found using the second derivative of the spectra (d2 log 1/R) and an additive calibration equation. Multiple linear regression (MLR) on pineapple fruit spectra (n = 85) gave a calibration equation using d2 log 1/R at wavelengths of 866, 760, 1232 and 832 nm with a multiple coefficient of determination (R2) of 0.75, and a standard error of calibration (SEC) of 1.21 °Brix. Modified partial least squares (MPLS) regression analysis yielded a calibration equation with R2 = 0.91, SEC = 0.69, and a standard error of cross validation (SECV) of 1.09 oBrix. For mango, MLR gave a calibration equation using d2 log 1/R at 904, 872, 1660 and 1516 nm with R2 = 0.90, and SEC = 0.85% DM and a bias of 0.39. Using MPLS analysis, a calibration equation with R2 = 0.98, SEC = 0.54 and SECV = 1.19 was obtained. We conclude that NIR technology offers the potential to assess fruit sweetness in intact whole pineapple and DM in mango fruit, respectively, to within 1° Brix and 1% DM, and could be used for the grading of fruit in fruit packing sheds.

Assessment of quality defects in macadamia kernels using NIR spectroscopy

Spectral data were collected of intact and ground kernels using 3 instruments (using Si-PbS, Si, and InGaAs detectors), operating over different areas of the spectrum (between 400 and 2500 nm) and employing transmittance, interactance, and reflectance sample presentation strategies. Kernels were assessed on the basis of oil and water content, and with respect to the defect categories of insect damage, rancidity, discoloration, mould growth, germination, and decomposition. Predictive model performance statistics for oil content models were acceptable on all instruments (R2 > 0.98; RMSECV < 2.5%, which is similar to reference analysis error), although that for the instrument employing reflectance optics was inferior to models developed for the instruments employing transmission optics. The spectral positions for calibration coefficients were consistent with absorbance due to the third overtones of CH2 stretching. Calibration models for moisture content in ground samples were acceptable on all instruments (R2 > 0.97; RMSECV < 0.2%), whereas calibration models for intact kernels were relatively poor. Calibration coefficients were more highly weighted around 1360, 740 and 840 nm, consistent with absorbance due to overtones of O-H stretching and combination. Intact kernels with brown centres or rancidity could be discriminated from each other and from sound kernels using principal component analysis. Part kernels affected by insect damage, discoloration, mould growth, germination, and decomposition could be discriminated from sound kernels. However, discrimination among these defect categories was not distinct and could not be validated on an independent set. It is concluded that there is good potential for a low cost Si photodiode array instrument to be employed to identify some quality defects of intact macadamia kernels and to quantify oil and moisture content of kernels in the process laboratory and for oil content in-line. Further work is required to examine the robustness of predictive models across different populations, including growing districts, cultivars and times of harvest.

Mapping species differences for adventitious rooting in a Corymbia torelliana x Corymbia citriodora subspecies variegata hybrid

Quantitative trait loci (QTL) detection was carried out for adventitious rooting and associated propagation traits in a second-generation outbred Corymbia torelliana x Corymbia citriodora subspecies variegata hybrid family (n=186). The parental species of this cross are divergent in their capacity to develop roots adventitiously on stem cuttings and their propensity to form lignotubers. For the ten traits studied, there was one or two QTL detected, with some QTL explaining large amounts of phenotypic variation (e.g. 66% for one QTL for percentage rooting), suggesting that major effects influence rooting in this cross. Collocation of QTL for many strongly genetically correlated rooting traits to a single region on linkage group 12 suggested pleiotropy. A three locus model was most parsimonious for linkage group 12, however, as differences in QTL position and lower genetic correlations suggested separate loci for each of the traits of shoot production and root initiation. Species differences were thought to be the major source of phenotypic variation for some rooting rate and root quality traits because of the major QTL effects and up to 59-fold larger homospecific deviations (attributed to species differences) relative to heterospecific deviations (attributed to standing variation within species) evident at some QTL for these traits. A large homospecific/heterospecific ratio at major QTL suggested that the gene action evident in one cross may be indicative of gene action more broadly in hybrids between these species for some traits.

Near infrared spectroscopy as a rapid tool to measure volatile aroma compounds in Riesling wine: Possibilities and limits

Volatile chemical compounds responsible for the aroma of wine are derived from a number of different biochemical and chemical pathways. These chemical compounds are formed during grape berry metabolism, crushing of the berries, fermentation processes (i.e. yeast and malolactic bacteria) and also from the ageing and storage of wine. Not surprisingly, there are a large number of chemical classes of compounds found in wine which are present at varying concentrations (ng L-1 to mg L-1), exhibit differing potencies, and have a broad range of volatilities and boiling points. The aim of this work was to investigate the potential use of near infrared (NIR) spectroscopy combined with chemometrics as a rapid and low-cost technique to measure volatile compounds in Riesling wines. Samples of commercial Riesling wine were analyzed using an NIR instrument and volatile compounds by gas chromatography (GC) coupled with selected ion monitoring mass spectrometry. Correlation between the NIR and GC data were developed using partial least-squares (PLS) regression with full cross validation (leave one out). Coefficients of determination in cross validation (R 2) and the standard error in cross validation (SECV) were 0.74 (SECV: 313.6 μg L−1) for esters, 0.90 (SECV: 20.9 μg L−1) for monoterpenes and 0.80 (SECV: 1658 ?g L-1) for short-chain fatty acids. This study has shown that volatile chemical compounds present in wine can be measured by NIR spectroscopy. Further development with larger data sets will be required to test the predictive ability of the NIR calibration models developed.

Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

Diet quality and liveweight gain of steers grazing Leucaena-grass pasture estimated with faecal near infrared reflectance spectroscopy (F.NIRS)

Three drafts of Bos indicus cross steers (initially 178-216 kg) grazed Leucaena-grass pasture [Leucaena leucocephala subspecies glabrata cv. Cunningham with green panic (Panicum maximum cv. trichoglume)] from late winter through to autumn during three consecutive years in the Burnett region of south-east Queensland. Measured daily weight gain (DWGActual) of the steers was generally 0.7-1.1 kg/day during the summer months. Estimated intakes of metabolisable energy and dry matter (DM) were calculated from feeding standards as the intakes required by the steers to grow at the DWGActual. Diet attributes were predicted from near infrared reflectance spectroscopy spectra of faeces (F.NIRS) using established calibration equations appropriate for northern Australian forages. Inclusion of some additional reference samples from cattle consuming Leucaena diets into F.NIRS calibrations based on grass and herbaceous legume-grass pastures improved prediction of the proportion of Leucaena in the diet. Mahalanobis distance values supported the hypothesis that the F.NIRS predictions of diet crude protein concentration and DM digestibility (DMD) were acceptable. F.NIRS indicated that the percentage of Leucaena in the diet varied widely (10-99%). Diet crude protein concentration and DMD were usually high, averaging 12.4 and 62%, respectively, and were related asymptotically to the percentage of Leucaena in the diet (R2 = 0.48 and 0.33, respectively). F.NIRS calibrations for DWG were not satisfactory to predict this variable from an individual faecal sample since the s.e. of prediction were 0.33-0.40 kg/day. Cumulative steer liveweight (LW) predicted from F.NIRS DWG calibrations, which had been previously developed with tropical grass and grass-herbaceous legume pastures, greatly overestimated the measured steer LW; therefore, these calibrations were not useful. Cumulative steer LW predicted from a modified F.NIRS DWG calibration, which included data from the present study, was strongly correlated (R2 = 0.95) with steer LW but overestimated LW by 19-31 kg after 8 months. Additional reference data are needed to develop robust F.NIRS calibrations to encompass the diversity of Leucaena pastures of northern Australia. In conclusion, the experiment demonstrated that F.NIRS could improve understanding of diet quality and nutrient intake of cattle grazing Leucaena-grass pasture, and the relationships between nutrient supply and cattle growth.

Quantitative assessment of total phenol contents of European oak (Quercus petraea and Quercus robur) by diffuse reflectance NIR spectroscopy on solid wood surfaces

Near infrared spectroscopy (NIRS) combined with multivariate analysis techniques was applied to assess phenol content of European oak. NIRS data were firstly collected directly from solid heartwood surfaces: in doing so, the spectra were recorded separately from the longitudinal radial and the transverse section surfaces by diffuse reflectance. The spectral data were then pretreated by several pre-processing procedures, such as multiplicative scatter correction, first derivative, second derivative and standard normal variate. The tannin contents of sawmill collected from the longitudinal radial and transverse section surfaces were determined by quantitative extraction with water/methanol (1:4, by vol). Then, total phenol contents in tannin extracts were measured by the Folin-Ciocalteu method. The NIR data were correlated against the Folin-Ciocalteu results. Calibration models built with partial least squares regression displayed strong correlation - as expressed by high determination correlation coefficient (r2) and high ratio of performance to deviation (RPD) - between measured and predicted total phenols content, and weak calibration and prediction errors (RMSEC, RMSEP). The best calibration was provided with second derivative spectra (r2 value of 0.93 for the longitudinal radial plane and of 0.91 for the transverse section plane). This study illustrates that the NIRS technique when used in conjunction with multivariate analysis could provide reliable, quick and non-destructive assessment of European oak heartwood extractives.

Potential of VIS-NIR Spectroscopy to predict perceived ‘muddy’ taint in australian farmed barramundi

Sensory analysis of food involves the measurement, interpretation and understanding of human responses to the properties of food perceived by the senses such as sight, smell, and taste (Cozzolino et al. 2005). It is important to have a quantitative means for assessing sensory properties in a reasonable way, to enable the food industry to rapidly respond to the changing demands of both consumers and the market. Aroma and flavour are among the most important properties for the consumer, and numerous studies have been performed in attempts to find correlations between sensory qualities and objective instrumental measurements. Rapid instrumental methods such as near infrared spectroscopy (NIR) might be advantageous to predict quality of different foods and agricultural products due to the speed of analysis, minimum sample preparation and low cost. The advantages of such technologies is not only to assess chemical structures but also to build an spectrum, characteristic of the sample, which behaves as a “finger print” of the sample.

The determination of essential oils in Sandalwood via NIR Spectroscopy

Sandalwood oil is widely used in the medicinal, cosmetic and aromatherapy industries. The oil is distilled from the heartwood of the sandalwood tree Santalum - a genus of hemi-parasitic tree species occurring throughout South and Southeast Asia, Australia and the Pacific. With international concern on the sustainability Sandalwood oil (Fox, 2000), the quality of oil entering the market is being compromised either through extraction from underdeveloped heartwoods or through adulteration with lower grade Sandalwood oils or synthetic substitutes (Howes et al. 2004). Although no standard method exists to assess the quality of Sandalwood oil, the International Organisation for Standardisation recommends GCMS analysis of santalol oil content. NIR spectroscopy has had a demonstrated success for other essential oils (Schulz et al. 2004, Steur et al. 2001). In addition, NIR spectroscopy has also been applied as both a qualitative and quantitative analytical tool in the forestry industry (Steur et al. 2001). This project aimed to assess the ability of NIR spectroscopy as a non-invasive, rapid and cheap analytical alternative to GCMS for Santalol determination.

Exploring the potential of VIS-NIR spectroscopy to predict sensory properties of foods

Sensory analysis of food involves the measurement, interpretation and understanding of human responses to the properties of food perceived by the senses such as sight, smell, and taste (Cozzolino et al. 2005). It is important to have a quantitative means for assessing sensory properties in a reasonable way, to enable the food industry to rapidly respond to the changing demands of both consumers and the market. Aroma and flavour are among the most important properties for the consumer and numerous studies have been performed in attempts to find correlations between sensory qualities and objective instrumental measurements. Rapid, non-destructive instrumental methods such as near infrared spectroscopy (NIR) might be advantageous to predict quality of food and agricultural products due to the speed of analysis, minimum sample preparation and low cost. The advantages of such technologies are not only to assess chemical structures but also to build a spectrum, characteristic of the sample, which behaves as a “finger print”.

Review: Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores

Near infrared (NIR) spectroscopy, usually in reflectance mode, has been applied to the analysis of faeces to measure the concentrations of constituents such as total N, fibre, tannins and delta C-13. In addition, an unusual and exciting application of faecal NIR [F.NIR] analyses is to directly predict attributes of the diet of herbivores such as crude protein and fibre contents, proportions of plant species and morphological components, diet digestibility and voluntary DM intake. This is an unusual application of NIR spectroscopy insofar as the spectral measurements are made, not on the material of interest [i.e. the diet), but on a derived material (i.e. faeces). Predictions of diet attributes from faecal spectra clearly depend on there being sufficient NIR spectral information in the diet residues present in faeces to describe the diet, although endogenous components of faeces such as undigested debris of micro-organisms from the rumen and Large intestine and secretions into the gastrointestinal tract wilt also contribute spectral information. Spectra of forage and of faeces derived from the forage are generally similar and the observed differences are principally in the spectral regions associated with constituents of forages known to be of low, or of high, digestibility. Some diet components (for example, ureal which are likely to be entirely digested apparently cannot be predicted from faecal NIR spectra because they cannot contribute to faecal spectra except through modifying the microbial and endogenous components. The errors and robustness of F.NIR calibrations to predict the crude protein concentration and digestibility of the diet of herbivores are generally comparable with those to directly predict the same attributes in forage from NIR spectra of the forage. Some attributes of the animal, such as species, gender, pregnancy status and parasite burden have been successfully discriminated into classes based on their faecal NIR spectra. Such discrimination was likely associated with differences in the diet selected and/or differences in the metabolites excreted in the faeces. NIR spectroscopy of faeces has usually involved scanning dried and ground samples in monochromators in the 400-2500nm or 1100-2500nm ranges. Results satisfactory for the purpose have also been reported for dried and ground faeces scanned using a diode array instrument in the 800-1700nm range and for wet faeces and slurries of excreta scanned with monochromators. Chemometric analysis of faecal spectra has generally used the approaches established for forage analysis. The capacity to predict many attributes of the diet, and some aspects of animal physiology, from NIR spectra of faeces is particularly useful to study the quality and quantity of the diet selected by both domestic and feral grazing herbivores and to enhance production and management of both herbivores and their grazing environment.

Cynodon transvaalensis x Cynodon dactylon Hybrid Green Couch Grass, Hybrid Bermuda Grass 'MS-Supreme'

Ploidy: triploid interspecific hybrid (3n = 27 chromosomes). Plant: habit prostrate, creeping, type mat-forming, height very short, longevity perennial, spreading laterally by stolons and rhizomes. Stolon: compound nodes with up to 3 leaves, internode length very short, internode thickness very thin, colour grey-brown (RHS N199A) when exposed to sunlight. Culms: length very short. Leaf blade: shape linear-triangular, length short, width narrow, colour dark green (RHS 137B). Ligule: dense row of short white hairs. Inflorescence: digitate with 3(-4) very short spicate racemes, peduncle very short. (All RHS colour chart numbers refer to 2001 edition.) PBR Certificate Number 2641, Application Number 2002/305, granted 24 February 2005.

Cynodon transvaalensis x Cynodon dactylon, Hybrid Green Couch Grass, Hybrid Bermuda Grass 'TL2'

Spontaneous mutation: In 1996, vegetative material (later designated ‘TL2’) taken from a disease resistant mutant plant on the fifteenth green at Novotel Palm Cove resort course near Cairns was included an on-going program of selection and testing of promising ‘Tifgreen’ mutants by Tropical Lawns Pty Ltd. Selection criteria: healthy vigorous growth during the tropical wet season, dense fine-textured appearance under close mowing, and dark green leaves. In subsequent trials, ‘TL2’ was identified as the outstanding plant among selections of mutant ‘Tifgreen’ genotypes from other north Queensland sites in terms of colour, texture and density for greens use. Propagation: vegetative. Breeder: Terry Anderlini, Gordonvale, QLD. PBR Certificate Number 2639, Application Number 2002/268, granted 24 February 2005.

Cynodon transvaalensis x Cynodon dactylon, Hybrid Green Couch Grass, Hybrid Bermuda Grass 'P18'

‘P18’ was first produced in 1992 and is a mutant genotype obtained from a hybrid Bermudagrass line believed to be ‘Tifdwarf’, which was grown in a greenhouse owned by H&H Seed Company in Yuma, Arizona. ‘P18’ was selected for its extremely fine leaf texture, its high shoot density under close mowing, its rapid growth rate, and its uniform dark green colour, and was subsequently evaluated for these traits and characteristics. Propagation: vegetative. Breeder: Howard E. Kaewer, Eden Prairie, MN, USA. PBR Application Number 2007/179, Certificate Number 3567, granted 13 August 2007.