6 resultados para Reflectance
em eResearch Archive - Queensland Department of Agriculture
Resumo:
The fatty acid composition of ground nuts (Arachis hypogaea L.) commonly known as peanuts, is an important consideration when a new variety is being released. The composition impacts on nutrition and, importantly, self-life of peanut products. To select for suitable breeding material, it was necessary to develop a rapid, non-derstructive and cost-efficient method. Near infrared spectroscopy was chosen as that methodology. Calibrations were developed for two major fatty-acid components, oleic and linoleic acids and two minor components, palmitic and stearic acids, as well as total oil content. Partial least squares models indicated a high level of precision with a squared multiple correlation coefficient of greater than 0.90 for each constitutent. Standard errors for prediction for oleic, linoleic, palmitic, stearic acids and total oil content were 6.4%, 4.5%, 0.8%, 0.9% and 1.3% respectively. The results demonstrated that reasonable calibrations could be developed to predict oil composition and content of peanuts for a breeding programme.
Resumo:
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.
Resumo:
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.
Resumo:
We tested the capacity of several published multispectral indices to estimate the nitrogen nutrition of wheat canopies grown under different levels of water supply and plant density and derived a simple canopy reflectance index that is greatly independent of those factors. Planar domain geometry was used to account for mixed signals from the canopy and soil when the ground cover was low. A nitrogen stress index was developed, which adjusts shoot %N for plant biomass and area, thereby accounting for environmental conditions that affect growth, such as crop water status. The canopy chlorophyll content index (CCCi) and the modified spectral ratio planar index (mSRPi) could explain 68 and 69% of the observed variability in the nitrogen nutrition of the crop as early as Zadoks 33, irrespective of water status or ground cover. The CCCi was derived from the combination of 3 wavebands 670, 720 and 790 nm, and the mSRPi from 445, 705 and 750 nm, together with broader bands in the NIR and RED. The potential for their spatial application over large fields/paddocks is discussed.
Resumo:
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.
Resumo:
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