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.

Near infrared reflectance as a rapid and inexpensive surrogate measure for fatty acid composition and oil content in peanuts (Arachis hypogaea L.)

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.

Effect of microwave radiation on seed mortality of rubber vine (Cryptostegia grandiflora R.Br.), parthenium (Parthenium hysterophorous L.) and bellyache bush (Jatropha gossypiifolia L.)

A trial was undertaken to evaluate the effect of microwaves on seed mortality of three weed species. Seeds of rubber vine (Cryptostegia grandiflora R.Br.), parthenium (Parthenium hysterophorous L.) and bellyache bush (Jatropha gossypiifolia L.) were buried at six depths (0, 2.5, 5, 10, 20 and 40 cm) in coarse sand maintained at one of two moisture levels, oven dry or wet (field capacity), and then subjected to one of five microwave radiation durations of (0, 2, 4, 8 and 16 min). Significant interactions between soil moisture level, microwave radiation duration, seed burial depth and species were detected for mortality of seeds of all three species. Maximum seed mortality of rubber vine (88%), parthenium (67%) and bellyache bush (94%) occurred in wet soil irradiated for 16 min. Maximum seed mortality of rubber vine and bellyache bush seeds occurred in seeds buried at 2.5 cm depth whereas that of parthenium occurred in seeds buried at 10 cm depth. Maximum soil temperatures of 114.1 and 87.5°C in dry and wet soil respectively occurred at 2.5 cm depth following 16 min irradiation. Irrespective of the greater soil temperatures recorded in dry soil, irradiating seeds in wet soil generally increased seed mortality 2.9-fold compared with dry soil. Moisture content of wet soil averaged 5.7% compared with 0.1% for dry soil. Results suggest that microwave radiation has the potential to kill seeds located in the soil seed bank. However, many factors, including weed species susceptibility, determine the effectiveness of microwave radiation on buried seeds. Microwave radiation may be an alternative to conventional methods at rapidly depleting soil seed banks in the field, particularly in relatively wet soils that contain long lived weed seeds.

Ultraviolet radiation effects on fruit surface respiration and chlorophyll fluorescence

High-value fruit crops are exposed to a range of environmental conditions that can reduce fruit quality. Solar injury (SI) or sunburn is a common disorder in tropical, sub-tropical, and temperate climates and is related to: 1) high fruit surface temperature; 2) high visible light intensity; and, 3) ultraviolet radiation (UV). Positional changes in fruit that are caused by increased weight or abrupt changes that result from summer pruning, limb breakage, or other damage to the canopy can expose fruit to high solar radiation levels, increased fruit surface temperatures, and increased UV exposure that are higher than the conditions to which they are adapted. In our studies, we examined the effects of high fruit surface temperature, saturating photosynthetically-active radiation (PAR), and short-term UV exposure on chlorophyll fluorescence, respiration, and photosynthesis of fruit peel tissues from tropical and temperate fruit in a simulation of these acute environmental changes. All tropical fruits (citrus, macadamia, avocado, pineapple, and custard apple) and the apple cultivars 'Gala', 'Gold Rush', and 'Granny Smith' increased dark respiration (A0) when exposed to UV, suggesting that UV repair mechanisms were induced. The maximum quantum efficiency of photosystem II (Fv/Fm) and the quantum efficiency of photosystem II (ΦII) were unaffected, indicating no adverse effects on photosystem II (PSII). In contrast, 'Braeburn' apple had a reduced Fv/Fm with no increase in A0 on all sampling dates. There was a consistent pattern in all studies. When Fv/Fm was unaffected by UV treatment, A0 increased significantly. Conversely, when Fv/Fm was reduced by UV treatment, then A0 was unaffected. The pattern suggests that when UV repair mechanisms are effective, PSII is adequately protected, and that this protection occurs at the cost of higher respiration. However, when the UV repair mechanisms are ineffective, not only is PSII damaged, but there is additional short-term damage to the repair mechanisms, indicated by a lack of respiration to provide energy.

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.

Relative contributions of light interception and radiation use efficiency to the reduction of maize productivity under cold temperatures

Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PARc) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PARc explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PARc, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

The limit to wheat water-use efficiency in eastern Australia. I. Gradients in the radiation environment and atmospheric demand

In the wheatbelt of eastern Australia, rainfall shifts from winter dominated in the south (South Australia, Victoria) to summer dominated in the north (northern New South Wales, southern Queensland). The seasonality of rainfall, together with frost risk, drives the choice of cultivar and sowing date, resulting in a flowering time between October in the south and August in the north. In eastern Australia, crops are therefore exposed to contrasting climatic conditions during the critical period around flowering, which may affect yield potential, and the efficiency in the use of water (WUE) and radiation (RUE). In this work we analysed empirical and simulated data, to identify key climatic drivers of potential water- and radiation-use efficiency, derive a simple climatic index of environmental potentiality, and provide an example of how a simple climatic index could be used to quantify the spatial and temporal variability in resource-use efficiency and potential yield in eastern Australia. Around anthesis, from Horsham to Emerald, median vapour pressure deficit (VPD) increased from 0.92 to 1.28 kPa, average temperature increased from 12.9 to 15.2°C, and the fraction of diffuse radiation (FDR) decreased from 0.61 to 0.41. These spatial gradients in climatic drivers accounted for significant gradients in modelled efficiencies: median transpiration WUE (WUEB/T) increased southwards at a rate of 2.6% per degree latitude and median RUE increased southwards at a rate of 1.1% per degree latitude. Modelled and empirical data confirmed previously established relationships between WUEB/T and VPD, and between RUE and photosynthetically active radiation (PAR) and FDR. Our analysis also revealed a non-causal inverse relationship between VPD and radiation-use efficiency, and a previously unnoticed causal positive relationship between FDR and water-use efficiency. Grain yield (range 1-7 t/ha) measured in field experiments across South Australia, New South Wales, and Queensland (n = 55) was unrelated to the photothermal quotient (Pq = PAR/T) around anthesis, but was significantly associated (r2 = 0.41, P < 0.0001) with newly developed climatic index: a normalised photothermal quotient (NPq = Pq . FDR/VPD). This highlights the importance of diffuse radiation and vapour pressure deficit as sources of variation in yield in eastern Australia. Specific experiments designed to uncouple VPD and FDR and more mechanistic crop models might be required to further disentangle the relationships between efficiencies and climate drivers.

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.

Development of near infrared analysis of faeces to estimate non-grass proportions in diets selected by cattle grazing tropical pastures

Grass (monocots) and non-grass (dicots) proportions in ruminant diets are important nutritionally because the non-grasses are usually higher in nutritive value, particularly protein, than the grasses, especially in tropical pastures. For ruminants grazing tropical pastures where the grasses are C-4 species and most non-grasses are C-3 species, the ratio of C-13/C-12 in diet and faeces, measured as delta C-13 parts per thousand, is proportional to dietary non-grass%. This paper describes the development of a faecal near infrared (NIR) spectroscopy calibration equation for predicting faecal delta C-13 from which dietary grass and non-grass proportions can be calculated. Calibration development used cattle faeces derived from diets containing only C-3 non-grass and C-4 grass components, and a series of expansion and validation steps was employed to develop robustness and predictive reliability. The final calibration equation contained 1637 samples and faecal delta C-13 range (parts per thousand) of [12.27]-[27.65]. Calibration statistics were: standard error of calibration (SEC) of 0.78, standard error of cross-validation (SECV) of 0.80, standard deviation (SD) of reference values of 3.11 and R-2 of 0.94. Validation statistics for the final calibration equation applied to 60 samples were: standard error of prediction (SEP) of 0.87, bias of -0.15, R-2 of 0.92 and RPD of 3.16. The calibration equation was also tested on faeces from diets containing C-4 non-grass species or temperate C-3 grass species. Faecal delta C-13 predictions indicated that the spectral basis of the calibration was not related to C-13/C-12 ratios per se but to consistent differences between grasses and non-grasses in chemical composition and that the differences were modified by photosynthetic pathway. Thus, although the calibration equation could not be used to make valid faecal delta C-13 predictions when the diet contained either C-3 grass or C-4 non-grass, it could be used to make useful estimates of dietary non-grass proportions. It could also be ut :sed to make useful estimates of non-grass in mixed C-3 grass/non-grass diets by applying a modified formula to calculate non-grass from predicted faecal delta C-13. The development of a robust faecal-NIR calibration equation for estimating non-grass proportions in the diets of grazing cattle demonstrated a novel and useful application of NIR spectroscopy in agriculture.

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Net radiation dynamics: performance of 20 daily net radiation models as related to model structure and intricacy in two climates.

We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.

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.