Odour, dust and non-methane volatile organic-compound emissions from tunnel-ventilated layer-chicken sheds: a case study of two farms

An observational study was undertaken to measure odour and dust (PM10 and PM2.5) emission rates and identify non-methane volatile organic compounds (NMVOCs) and odorants in the exhaust air from two tunnel-ventilated layer-chicken sheds that were configured with multi-tiered cages and manure belts. The study sites were located in south-eastern Queensland and the West Gippsland region of Victoria, Australia. Samples were collected in summer and winter on sequential days across the manure-belt cleaning cycle. Odour emissions ranged from 58 to 512 ou/s per 1000 birds (0.03-0.27 ou/s.kg) and dust emission rates ranged 0.014-0.184 mg/s per 1000 birds for PM10 and 0.001-0.190 mg/s per 1000 birds for PM2.5. Twenty NMVOCs were identified, including three that were also identified as odorants using thermal desorption-gas chromatography-mass spectrometry/olfactometry analysis. Odour emission rates were observed to vary with the amount of manure accumulation on the manure belts, being lowest 2-4 days after removing manure. Odour emission rates were also observed to vary with diurnal and seasonal changes in ventilation rate. Dust emissions were observed to increase with ventilation rate but not with manure accumulation. Some NMVOCs were identified at both farms and in different seasons whereas others were observed only at one farm or in one season, indicating that odorant composition was influenced by farm-specific practices and season.

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.

Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments

Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r2 relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r2 = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg)1) in Horsham with an r2 = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.

Soil sorption-desorption of phosphorus from piggery effluent compared with inorganic sources

The leaching of phosphorus (P) within soils can be a limiting consideration for the sustainable operation of intensive livestock enterprises. Sorption curves are widely used to assist estimation of P retention, though the effect of effluent constituents on their accuracy is not well understood. We conducted a series of P-sorption-desorption batch experiments with an Oxic Haplustalf (soil 1), Haplusterts (soils 2 and 3), and a Natrustalf (soil 4). Phosphorus sources included effluent, orthophosphate-P in a matrix replicating the effluent's salt constituents (the reference solution), and an orthophosphate-P solution. Treated soils were incubated for up to 193 days before sequential desorption extraction. Effluent constituents, probably the organic or particulate components, temporarily increased the vulnerability of sorbed-P to desorption. The increase in vulnerability was removed by 2-113 days of incubation (25 degrees C). Despite vigorous extraction for 20 consecutive days, some P sorbed as part of the treatments of soils 1 and 2 was not desorbed. The increased vulnerability due to effluent constituents lasted a maximum of about one cropping season and, for all other treatments, adsorption curves overestimated vulnerability to desorption. Therefore, adsorption curves provide a conservative estimate of vulnerability to desorption where effluent is used in continued crop production in these soils.

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.

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.

Thermal requirements, field mortality and population phenology modelling of Paropsis atomaria Olivier, an emergent pest in subtropical hardwood plantations

Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.

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.