Estimating Hydrogen Cyanide in Forage Sorghum (Sorghum bicolor) by Near-Infrared Spectroscopy

Hydrogen cyanide (HCN) is a toxic chemical that can potentially cause mild to severe reactions in animals when grazing forage sorghum. Developing technologies to monitor the level of HCN in the growing crop would benefit graziers, so that they can move cattle into paddocks with acceptable levels of HCN. In this study, we developed near-infrared spectroscopy (MRS) calibrations to estimate HCN in forage sorghum and hay. The full spectral NIRS range (400-2498 nm) was used as well as specific spectral ranges within the full spectral range, i.e., visible (400-750 nm), shortwave (800-1100 nm) and near-infrared (NIR) (1100-2498 nm). Using the full spectrum approach and partial least-squares (PLS), the calibration produced a coefficient of determination (R-2) = 0.838 and standard error of cross-validation (SECV) = 0.040%, while the validation set had a R-2 = 0.824 with a low standard error of prediction (SEP = 0.047%). When using a multiple linear regression (MLR) approach, the best model (NIR spectra) produced a R-2 = 0.847 and standard error of calibration (SEC) = 0.050% and a R-2 = 0.829 and SEP = 0.057% for the validation set. The MLR models built from these spectral regions all used nine wavelengths. Two specific wavelengths 2034 and 2458 nm were of interest, with the former associated with C=O carbonyl stretch and the latter associated with C-N-C stretching. The most accurate PLS and MLR models produced a ratio of standard error of prediction to standard deviation of 3.4 and 3.0, respectively, suggesting that the calibrations could be used for screening breeding material. The results indicated that it should be feasible to develop calibrations using PLS or MLR models for a number of users, including breeding programs to screen for genotypes with low HCN, as well as graziers to monitor crop status to help with grazing efficiency.

The utility of near infrared spectroscopy for age estimation of deepwater sharks

Reliable age information is vital for effective fisheries management, yet age determinations are absent for many deepwater sharks as they cannot be aged using traditional methods of growth bands counts. An alternative approach to ageing using near infrared spectroscopy (NIRS) was investigated using dorsal fin spines, vertebrae and fin clips of three species of deepwater sharks. Ages were successfully estimated for the two dogfish, Squalus megalops and Squalus montalbani, and NIRS spectra were correlated with body size in the catshark, Asymbolus pallidus. Correlations between estimated-ages of the dogfish dorsal fin spines and their NIRS spectra were good, with S. megalops R2=0.82 and S. montalbani R2=0.73. NIRS spectra from S. megalops vertebrae and fin clips that have no visible growth bands were correlated with estimated-ages, with R2=0.89 and 0.76, respectively. NIRS has the capacity to non-lethally estimate ages from fin spines and fin clips, and thus could significantly reduce the numbers of sharks that need to be lethally sampled for ageing studies. The detection of ageing materials by NIRS in poorly calcified deepwater shark vertebrae could potentially enable ageing of this group of sharks that are vulnerable to exploitation.

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.

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.

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.

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.

Near infrared spectroscopy as a rapid non-invasive tool for agricultural and industrial process management with special reference to avocado and sandalwood industries

Near infrared spectroscopy (NIRS) can play a vital role as a cost effective, rapid, non-invasive, reproducible diagnostic tool for many environmental management, agricultural and industrial waste water monitoring applications. In this paper we highlight the ability of NIRS technology to be used as a diagnostic tool in agricultural and environmental applications through the successful assessment of Fourier Transform NIRS to predict α santalol in sandalwood chip samples, and maturity of ‘Hass’ avocado fruit based on dry matter content. Presented at the Third International Conference on Challenges in Environmental Science & Engineering, CESE-2010. 26 September – 1 October 2010, The Sebel, Cairns, Queensland, Australia.

Simultaneous prediction of acidity parameters (pH and titratable acidity) in Kefir using near infrared reflectance spectroscopy.

Acidity in terms of pH and titratable acids influences the texture and flavour of fermented dairy products, such as Kefir. However, the methods for determining pH and titratable acidity (TA) are time consuming. Near infrared (NIR) spectroscopy is a non-destructive method, which simultaneously predicts multiple traits from a single scan and can be used to predict pH and TA. The best pH NIR calibration model was obtained with no spectral pre-treatment applied, whereas smoothing was found to be the best pre-treatment to develop the TA calibration model. Using cross-validation, the prediction results were found acceptable for both pH and TA. With external validation, similar results were found for pH and TA, and both models were found to be acceptable for screening purposes.

The Application of Near Infrared Spectroscopy for the Assessment of Avocado Quality Attributes, Infrared Spectroscopy. Chapter 14

Quality and safety evaluation of agricultural products has become an increasingly important consideration in market/commercial viability and systems for such evaluations are now demanded by customers, including distributors and retailers. Unfortunately, most horticultural products struggle with delivering adequate and consistent quality to the consumer. Removing inconsistencies and providing what the consumer expects is a key factor for retaining and expanding both domestic and international markets. Most commercial quality classification systems for fruit and vegetables are based on external features of the product, for example: shape, colour, size, weight and blemishes. However, the external appearance of most fruit is generally not an accurate guide to the internal or eating quality of the fruit. Internal quality of fruit is currently subjectively judged on attributes such as volatiles, firmness, and appearance. Destructive subjective measures such as internal flesh colour, or objective measures such as extraction of juice to measure sweetness (oBrix) or assessment of dry matter (DM) content are also used, although obviously not for every fruit – just a sample to represent the whole consignment. For avocado fruit, external colour is not a maturity characteristic, and its smell is too weak and appears later in its maturity stage (Gaete-Garreton et al., 2005). Since maturity is a major component of avocado quality and palatability, it is important to harvest mature fruit, so as to ensure that fruit will ripen properly and have acceptable eating quality. Currently, commercial avocado maturity estimation is based on destructive assessment of the %DM, and sometimes percent oil, both of which are highly correlated with maturity (Clark et al., 2003; Mizrach & Flitsanov, 1999). Avocados Australia Limited (AAL (2008)) recommend a minimum maturity standard for its growers of 23 %DM (greater than 10% oil content) for the ‘Hass’ cultivar, although consumer studies indicate a preference for at least 25 %DM (Harker et al., 2007).

Characterisation of grain quality in diverse sorghum germplasm using a Rapid Visco-Analyzer and near infrared reflectance spectroscopy

BACKGROUND: Twenty-two diverse sorghum landraces, classified as normal and opaque types obtained from Ethiopia, were characterised for grain quality parameters using near infra-red spectroscopy (NIRS), chemical and Rapid Visco-Analyzer (RVA) characteristics. RESULTS: Protein content ranged from 77 to 182 g kg-1, and starch content from 514 to 745 g kg(-1). The NIRS analysis indicated the pig faecal digestible energy range from 14.6 to 15.7MJ kg(-1) as fed, and the ileal digestible energy range from 11.3 to 13.9MJ kg(-1) as fed. The normal sorghums had higher digestible energy than the opaque sorghums, which exhibited lower RVA viscosities, and higher pasting temperatures and setback ratios. The RVA parameterswere positively correlated with the starch content and negatively correlated with the protein content. The normal and opaque types formed two distinct groups based on principal component and cluster analyses. CONCLUSION: The landraces were different for the various grain quality parameters with some landraces displaying unique RVA and NIRS profiles. This study will guide utilisation of the sorghum landraces in plant improvement programs, and provides a basis for further studies into how starch and other constituents behave in and affect the properties of these landraces. (C) 2011 Society of Chemical Industry

Infrared spectroscopy as a rapid tool to detect methylglyoxal and antibacterial activity in Australian honeys

Methylglyoxal (2-oxopropanal) is a compound known to contribute to the non-peroxide antimicrobial activity of honeys. The feasibility of using infrared spectroscopy as a predictive tool for honey antibacterial activity and methylglyoxal content was assessed. A linear relationship was found between methylglyoxal content (279–1755 mg/kg) in Leptospermum polygalifolium honeys and bacterial inhibition for Escherichiacoli (R2 = 0.80) and Staphylococcusaureus (R2 = 0.64). A good prediction of methylglyoxal (R2 0.75) content in honey was achieved using spectroscopic data from the mid infrared (MIR) range in combination with partial least squares regression. These results indicate that robust predictive equations could be developed using MIR for commercial application where the prediction of bacterial inhibition is needed to ‘value’ honeys with methylglyoxal contents in excess of 200 mg/kg.

A novel method for the age estimation of Saddletail snapper (Lutjanus malabaricus) using Fourier Transform-near infrared (FT-NIR) spectroscopy

Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

A novel use of near infrared spectroscopy: ageing deepwater sharks

To age sharks, the growth bands in the shark vertebrae (like the rings in a tree) or on the spines in front of each dorsal fin (which only some sharks have) are manually counted using a microscope. This is time-consuming and is only possible on dead animals. NIR spectroscopy is shown to be able to detect age in dorsal fin spines of sharks and hand-held NIR spectroscopy units could potentially be used for ageing of sharks in the field, at sea, using a hand-held unit to scan the fin spine on a live animal.

Revolutionising Fish Ageing: Using Near Infrared Spectroscopy to Age Fish

The project aimed to evaluate the innovative application of NIRS as a reliable, repeatable, and cost-effective method of ageing fish, using otoliths of Barramundi and Snapper as study species. Specific research questions included assessing how geographic and seasonal variation in otoliths affects NIRS predictive models of fish age, as well as how the NIR spectra of otoliths change in the short-term (i.e., <12 months) and long-term (i.e., historical otolith collections) and what effect this has on the predictive ability of NIRS models. The cost-effectiveness of using NIRS to supplement standard fish ageing methods was also evaluated using a hypothetical case study of Barramundi.