QTLs for water absorption and flour yield identified in the doubled haploid wheat population Lang/QT8766

Two key quality traits in milling wheat are flour yield (FY) and water absorption (WA). Ideally, breeders would prefer to use markers to select promising lines rather than time consuming rheology tests. In this study, we measured FY and WA on a wheat mapping population (Lang/QT8766) of 162 individuals grown in two replicated field experiments at three locations over 2 years. We also carried out near infrared reflectance spectroscopy (NIRS) predictions on the grain for these traits to see if NIRS phenotypic data could provide useful mapping results when compared to the reference phenotypic data. Several common QTLs were identified for FY and WA by both sets of data. The QTL on chromosome 4D was a consistently recurring QTL region for both traits. The QTL on chromosome 2A was positively linked to protein content which was supported by genetic correlation data. The results also indicated it was possible to obtain useful phenotypic data for mapping FY and WA using NIRS data. This would save time and costs as NIRS is quicker and cheaper than current rheology methods.

Application of commercially available, low-cost, miniaturised NIR spectrometers to the assessment of the sugar content of intact fruit

Recent decreases in costs, and improvements in performance, of silicon array detectors open a range of potential applications of relevance to plant physiologists, associated with spectral analysis in the visible and short-wave near infra-red (far-red) spectrum. The performance characteristics of three commercially available ‘miniature’ spectrometers based on silicon array detectors operating in the 650–1050-nm spectral region (MMS1 from Zeiss, S2000 from Ocean Optics, and FICS from Oriel, operated with a Larry detector) were compared with respect to the application of non-invasive prediction of sugar content of fruit using near infra-red spectroscopy (NIRS). The FICS–Larry gave the best wavelength resolution; however, the narrow slit and small pixel size of the charge-coupled device detector resulted in a very low sensitivity, and this instrumentation was not considered further. Wavelength resolution was poor with the MMS1 relative to the S2000 (e.g. full width at half maximum of the 912 nm Hg peak, 13 and 2 nm for the MMS1 and S2000, respectively), but the large pixel height of the array used in the MMS1 gave it sensitivity comparable to the S2000. The signal-to-signal standard error ratio of spectra was greater by an order of magnitude with the MMS1, relative to the S2000, at both near saturation and low light levels. Calibrations were developed using reflectance spectra of filter paper soaked in range of concentrations (0–20% w/v) of sucrose, using a modified partial least squares procedure. Calibrations developed with the MMS1 were superior to those developed using the S2000 (e.g. coefficient of correlation of 0.90 and 0.62, and standard error of cross-validation of 1.9 and 5.4%, respectively), indicating the importance of high signal to noise ratio over wavelength resolution to calibration accuracy. The design of a bench top assembly using the MMS1 for the non-invasive assessment of mesocarp sugar content of (intact) melon fruit is reported in terms of light source and angle between detector and light source, and optimisation of math treatment (derivative condition and smoothing function).

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.

Extent of dense native woodland and exotic weed infestation in the extensive grazing lands of the Upper Herbert and Upper Burdekin River Catchments of far north Queensland: results of a producer survey

The Mt Garnet Landcare Group commissioned a survey of landholders within the Upper Herbert and Upper Burdekin River Catchments to assess the density of native woodlands and to gauge the extent of exotic weed infestation. Twenty-four of 49 landholders responded, representing an area of nearly 500 000 ha or 47% of the total area. Dense native woodland covers 24% (>117 000 ha) of the area surveyed, while a further 30% (140 000 ha) supports moderately dense stands. The dense stands are largely confined to the highly fertile alluvial soils (26% dense woodland) and the lower fertility sandy-surfaced soils (33% or >96 000 ha). Moderate and dense infestations of exotic weeds, principally Lantana camara, occur on 54% (20 000 ha) of alluvial soils and on 13% of sandy-surfaced soils (39 000 ha), where praxelis (Praxelis clematidia) is the major weed. Basaltic soils have low levels of both dense woodland and exotic weed infestation. Some implications of the results are discussed.

Mycotoxins and Fungal Damage in Maize Harvested during 1982 in Far North Queensland

A survey for mycotoxins and fungal damage in maize (Zea mays L.) grown during 1982 in Far North Queensland is reported. This season had a rainfall distribution which was typical for the reglon. The 293 samples examined came from 11 1 farms in eight maize-growing districts. The samples were first subjected to rapid screening tests for fungal damage. Aflatoxins B1, B2, G1, G2 ochratoxin A, T-2 toxin, and sterigmatocystin were not detected, but zearalenone was found in 85% of the samples. The concentrations of zearalenone were correlated with the extent of Gibberella zeae cob rot as indicated by the proportion (up to 2%) of kernels in each sample having a reddish-purple discoloration. In four samples the zearalenone concentration exceeded 1 mg kg-1, but the mean ¦ s.d. (n = 293) concentration in all samples was 0.17 ¦ 0.225 mg kg-1. Concentrations were highest in districts with the highest rainfall during the period of maize growth.

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.

Fishery biology and management of Protonibea diacanthus (Sciaenidae) aggregations in far Northern Cape York Peninsula waters

The sciaenid Protonibea diacanthus is a large, long-lived predatory fish of inshore northern Australian waters, which forms annual aggregations that are fished extensively by traditional (subsistence) and recreational fishers. There are now widespread concerns that the resource is being overexploited. Indigenous fishers of the Cape York Northern Peninsula Area (NPA) relate that large adult fish (up to 1500 mm total length (TL)) made up the bulk of the catch from the sciaenid aggregations until about 1994. In contrast, sexually mature P. diacanthus comprised only a small component (12 fish out of 270=4.4%) examined in a 1999–2000 sampling programme that was biased towards the largest individuals available. At 790 mm TL, the minimum size at first maturity for female P. diacanthus in this study is much smaller than the 920 mm TL reported previously in Queensland waters. Developing ovaries were observed in specimens sampled from sciaenid aggregations which formed in NPA waters between May and September 2000. However, no fish with ripe or spent gonads were found in the study, so the current timing and location of the spawning season for P. diacanthus in the region remain unknown. Food items observed in the analysis of the diet of P. diacanthus from the NPA included a variety of teleosts and invertebrates. The range of animal taxa represented in the prey items support the description of an ‘opportunistic predator’ attributed to the species. In our sampling, the stomach contents of fish caught during the time of the aggregation events did not differ from those observed at other times of the year. A total of 114 P. diacanthus were tagged and released at aggregation sites during the study period, and 3 fish (2.6%) were subsequently recaptured. The low rate of tag returns from the wild stock tagging programme, both in this study (2.6%) and from recreational fisher tag/release programmes for the sciaenid elsewhere in Queensland (6.5%), were not explained by tag loss nor mortality, given the high retention rate of tags and the zero mortality seen in tank trials. In response to the biological findings from this study, indigenous community councils of the NPA imposed a 2-year fishing moratorium for P. diacanthus. Surveys at aggregation sites in 2002 and 2003 established that much larger fish (mean size 103.5 cm TL) were again present on the grounds, albeit in very low numbers. These recent preliminary results highlight the critical need for continued monitoring and management of the P. diacanthus fishery in the NPA, if prospects for resource recovery are to be realised. The NPA initiative has provided a rare opportunity to negotiate a co-management strategy, based on scientific data and traditional knowledge, for the recovery of a cultural and economically significant fished resource.

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.

Field and laboratory evaluations of fungicides for the control of brown spot (Corynespora cassiicola) and black spot (Asperisporium caricae) of papaya in far north Queensland, Australia

Several chemicals including strobilurins (pyraclostrobin and azoxystrobin), triazoles (difenoconazole and tebuconazole), dithiocarbamates (propineb, metiram, ziram and mancozeb) and the phthalimide chlorothalonil were evaluated in three field experiments in north Queensland, Australia, for the control of brown spot (caused by Corynespora cassiicola) and black spot (caused by Asperisporium caricae) of papaya. Chlorothalonil and pyraclostrobin were shown to be more effective than the industry standard, mancozeb, for the control of brown spot. In the black spot experiments, difenoconazole, pyraclostrobin and chlorothalonil used alone or in spray programs were as effective as, or better than, the industry standards, mancozeb and tebuconazole. Plants treated with pyraclostrobin and difenoconazole had more fruit unaffected by black spot (97% and 99% respectively) than plants treated with tebuconazole (51%), mancozeb (20%) and the untreated controls (1%). Laboratory tests also showed that A. caricae was more sensitive to difenoconazole (EC50 of 2ppm) than tebuconazole (EC50 of 14ppm). In 2007, off-label permits were obtained for chlorothalonil for control of brown spot and difenoconazole and chlorothalonil for the control of black spot of papaya.

Incidence and pathogenicity of Phytophthora palmivora and Pythium vexans associated with durian decline in far northern Queensland

In recent years, dieback of durian has become a major problem in mature orchards in the northern Queensland wet tropics region. A survey of 13 durian orchards was conducted during the dry season (July-September 2001) and following wet season (February-April 2002), with roots and soil from the root zone of affected trees being sampled. Phytophthora palmivora was recovered from the roots of affected trees on 12 of the 13 farms in the dry season, and all farms in the wet season. Pythium vexans was recovered from all 13 farms in both seasons. P. palmivora and P. vexans were recovered from diseased roots of 3-month-old durian seedlings cv. Monthong artificially inoculated with these organisms.

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.

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.