16 resultados para action prediction
em eResearch Archive - Queensland Department of Agriculture
Resumo:
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.
Resumo:
Traps baited with synthetic aggregation pheromone and fermenting bread dough were used to monitor seasonal incidence and abundance of the ripening fruit pests, Carpophilus hemipterus (L.), C. mutilatus Erichson and C. davidsoni Dobson in stone fruit orchards in the Leeton district of southern New South Wales during five seasons (1991-96). Adult beetles were trapped from September-May, but abundance varied considerably between years with the amount of rainfall in December-January having a major influence on population size and damage potential during the canning peach harvest (late February-March). Below average rainfall in December-January was associated with mean trap catches of < 10 beetles/trap/week in low dose pheromone traps during the harvest period in 1991/92 and 1993/94 and no reported damage to ripening fruit. Rainfall in December-January 1992/93 was more than double the average and mean trap catches ranged from 8-27 beetles/week during the harvest period with substantial damage to the peach crop. December-January rainfall was also above average in 1994/95 and 1995/96 and means of 50-300 beetles/trap/week were recorded in high dose pheromone traps during harvest periods. Carpophilus spp. caused economic damage to peach crops in both seasons. These data indicate that it may be possible to predict the likelihood of Carpophilus beetle damage to ripening stone fruit in inland areas of southern Australia, by routine pheromone-based monitoring of beetle populations and summer temperatures and rainfall.
Resumo:
Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695-1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The 'global' modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the 'local' MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.
Resumo:
The incorporation of sown pastures as short-term rotations into the cropping systems of northern Australia has been slow. The inherent chemical fertility and physical stability of the predominant vertisol soils across the region enabled farmers to grow crops for decades without nitrogen fertiliser, and precluded the evolution of a crop–pasture rotation culture. However, as less fertile and less physically stable soils were cropped for extended periods, farmers began to use contemporary farming and sown pasture technologies to rebuild and maintain their soils. This has typically involved sowing long-term grass and grass–legume pastures on the more marginal cropping soils of the region. In partnership with the catchment management authority, the Queensland Murray–Darling Committee (QMDC) and Landcare, a pasture extension process using the LeyGrain™ package was implemented in 2006 within two Grain & Graze projects in the Maranoa-Balonne and Border Rivers catchments in southern inland Queensland. The specific objectives were to increase the area sown to high quality pasture and to gain production and environmental benefits (particularly groundcover) through improving the skills of producers in pasture species selection, their understanding and management of risk during pasture establishment, and in managing pastures and the feed base better. The catalyst for increasing pasture sowings was a QMDC subsidy scheme for increasing groundcover on old cropping land. In recognising a need to enhance pasture knowledge and skills to implement this scheme, the QMDC and Landcare producer groups sought the involvement of, and set specific targets for, the LeyGrain workshop process. This is a highly interactive action learning process that built on the existing knowledge and skills of the producers. Thirty-four workshops were held with more than 200 producers in 26 existing groups and with private agronomists. An evaluation process assessed the impact of the workshops on the learning and skill development by participants, their commitment to practice change, and their future intent to sow pastures. The results across both project catchments were highly correlated. There was strong agreement by producers (>90%) that the workshops had improved knowledge and skills regarding the adaptation of pasture species to soils and climates, enabling a better selection at the paddock level. Additional strong impacts were in changing the attitudes of producers to all aspects of pasture establishment, and the relative species composition of mixtures. Producers made a strong commitment to practice change, particularly in managing pasture as a specialist crop at establishment to minimise risk, and in the better selection and management of improved pasture species (particularly legumes and the use of fertiliser). Producers have made a commitment to increase pasture sowings by 80% in the next 5 years, with fourteen producers in one group alone having committed to sow an additional 4893 ha of pasture in 2007–08 under the QMDC subsidy scheme. The success of the project was attributed to the partnership between QMDC and Landcare groups who set individual workshop targets with LeyGrain presenters, the interactive engagement processes within the workshops themselves, and the follow-up provided by the LeyGrain team for on-farm activities.
Resumo:
BACKGROUND: The inability to consistently guarantee internal quality of horticulture produce is of major importance to the primary producer, marketers and ultimately the consumer. Currently, commercial avocado maturity estimation is based on the destructive assessment of percentage dry matter (%DM), and sometimes percentage oil, both of which are highly correlated with maturity. In this study the utility of Fourier transform (FT) near-infrared spectroscopy (NIRS) was investigated for the first time as a non-invasive technique for estimating %DM of whole intact 'Hass' avocado fruit. Partial least squares regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. RESULTS: It was found that combining three harvests (early, mid and late) from a single farm in the major production district of central Queensland yielded a predictive model for %DM with a coefficient of determination for the validation set of 0.76 and a root mean square error of prediction of 1.53% for DM in the range 19.4-34.2%. CONCLUSION: The results of the study indicate the potential of FT-NIRS in diffuse reflectance mode to non-invasively predict %DM of whole 'Hass' avocado fruit. When the FT-NIRS system was assessed on whole avocados, the results compared favourably against data from other NIRS systems identified in the literature that have been used in research applications on avocados.
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:
Hip height, body condition, subcutaneous fat, eye muscle area, percentage Bos taurus, fetal age and diet digestibility data were collected at 17 372 assessments on 2181 Brahman and tropical composite (average 28% Brahman) female cattle aged between 0.5 and 7.5 years of age at five sites across Queensland. The study validated the subtraction of previously published estimates of gravid uterine weight to correct liveweight to the non-pregnant status. Hip height and liveweight were linearly related (Brahman: P<0.001, R-2 = 58%; tropical composite P<0.001, R-2 = 67%). Liveweight varied by 12-14% per body condition score (5-point scale) as cows differed from moderate condition (P<0.01). Parallel effects were also found due to subcutaneous rump fat depth and eye muscle area, which were highly correlated with each other and body condition score (r = 0.7-0.8). Liveweight differed from average by 1.65-1.66% per mm of rump fat depth and 0.71-0.76% per cm(2) of eye muscle area (P<0.01). Estimated dry matter digestibility of pasture consumed had no consistent effect in predicting liveweight and was therefore excluded from final models. A method developed to estimate full liveweight of post-weaning age female beef cattle from the other measures taken predicted liveweight to within 10 and 23% of that recorded for 65 and 95% of cases, respectively. For a 95% chance of predicted group average liveweight (body condition score used) being within 5, 4, 3, 2 and 1% of actual group average liveweight required 23, 36, 62, 137 and 521 females, respectively, if precision and accuracy of measurements matches that used in the research. Non-pregnant Bos taurus female cattle were calculated to be 10-40% heavier than Brahmans at the same hip height and body condition, indicating a substantial conformational difference. The liveweight prediction method was applied to a validation population of 83 unrelated groups of cattle weighed in extensive commercial situations on 119 days over 18 months (20 917 assessments). Liveweight prediction in the validation population exceeded average recorded liveweight for weigh groups by an average of 19 kg (similar to 6%) demonstrating the difficulty of achieving accurate and precise animal measurements under extensive commercial grazing conditions.
Resumo:
Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The R-v(2) and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but <= 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of R-v(2) = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation. Crown Copyright (c) 2012 Published by Elsevier B.V. All rights reserved.
Resumo:
The mechanisms of action of Cu 2+ in improving the longevity of cut flowers and foliage have not been elucidated. Possible antimicrobial action of Cu 2+ against stem end and vase solution colonising bacteria was investigated using Cu 2+ treatments optimised for cut Acacia holosericea A. Cunn. ex G. Don foliage stems. These treatments were a 5h pulse with 2.2mM Cu 2+ or a 0.5mM Cu 2+ vase solution versus a deionised water (no Cu 2+) control. Bacterial growth over time was assessed by a standard plate count agar technique and with scanning electron microscopy. Cu 2+ treatments significantly extended the cut foliage vase life. However, they did not have sustained antibacterial activity against stem end or vase solution colonising bacteria. Also, regular recutting of 1-2cm from the stem ends did not substantially improve either cut stem water relations or longevity. The positive effects of Cu 2+ treatments were unaffected by the repeated stem end recutting. It was concluded that the primary mechanism of Cu 2+ was not antibacterial. Moreover, naturally growing vase solution and stem end microbial populations had relatively insignificant effects on cut A. holosericea vase life. Research into alternative mechanisms of Cu 2+ is required. © 2012 Elsevier B.V.
Resumo:
Mango is an important horticultural fruit crop and breeding is a key strategy to improve ongoing sustainability. Knowledge of breeding values of potential parents is important for maximising progress from breeding. This study successfully employed a mixed linear model methods incorporating a pedigree to predict breeding values for average fruit weight from highly unbalanced data for genotypes planted over three field trials and assessed over several harvest seasons. Average fruit weight was found to be under strong additive genetic control. There was high correlation between hybrids propagated as seedlings and hybrids propagated as scions grafted onto rootstocks. Estimates of additive genetic correlation among trials ranged from 0.69 to 0.88 with correlations among harvest seasons within trials greater than 0.96. These results suggest that progress from selection for broad adaptation can be achieved, particularly as no repeatable environmental factor that could be used to predict G x E could be identified. Predicted breeding values for 35 known cultivars are presented for use in ongoing breeding programs.
Resumo:
In current simulation packages for the management of extensive beef-cattle enterprises, the relationships for the key biological rates (namely conception and mortality) are quite rudimentary. To better estimate these relationships, cohort-level data covering 17 100 cow-years from six sites across northern Australia were collated and analysed. Further validation data, from 7200 cow-years, were then used to test these relationships. Analytical problems included incomplete and non-standardised data, considerable levels of correlation among the 'independent' variables, and the close similarity of alternate possible models. In addition to formal statistical analyses of these data, the theoretical equations for predicting mortality and conception rates in the current simulation models were reviewed, and then reparameterised and recalibrated where appropriate. The final models explained up to 80% of the variation in the data. These are now proposed as more accurate and useful models to be used in the prediction of biological rates in simulation studies for northern Australia. © The State of Queensland (through the Department of Agriculture, Fisheries and Forestry) 2012. © CSIRO.
Resumo:
Odour from meat chicken (broiler) farms is an environmental issue affecting the sustainable development of the chicken meat industry but is a normal part of broiler production. Odour plumes exhausted from broiler sheds interact with the environment, where dispersion and dilution of the odours varies constantly, especially diurnally. The potential for odour impacts is greatest when odour emission rates are high and/or when atmospheric dispersion and dilution of odour plumes is limited (i.e. during stable conditions). We continuously monitored ventilation rate, on-site weather conditions, atmospheric stability, and estimated odour concentration with an artificial olfaction system. Detailed inspection of odour emission rates at critical times, i.e. dawn, dusk and night time, revealed that maximum daily and batch odour emission rates are not necessarily the cause of odour impacts. Periods of lower odour emission rates on each day are more likely to correspond with odour impacts. Odour emission rates need to be measured at the times when odour impacts are most likely to occur, which is likely to be at night. Additionally, high resolution ventilation rate data should be sought after to improve odour emission models, especially at critical times of the day. Consultants, regulators and researchers need to give more thought to odour emission rates from meat chicken farms to improved prediction and management of odour impacts.
Resumo:
A recently developed hanging drop air exposure system for toxicity studies of volatile chemicals was applied to evaluate the cell viability of lung carcinoma A549 cells after 1 h and 24 h of exposure to benzene, toluene, ethylbenzene and xylenes (BTEX) as individual compounds and mixtures of 4 or 6 components. The cellular chemical concentrations causing 50% reduction of cell viability (EC50) were calculated use a mass balance model and came to 17, 12, 11, 9, 4 and 4 mmol/kg cell dry weight for benzene, toluene, ethylbenzene, m-xylene, o-xylene and p-xylene respectively after 1 h of exposure. The EC50 decreased by a factor of four after 24 h of exposure. All mixture effects were best described by the mixture toxicity model of concentration addition, which is valid for chemicals with the same mode of action. Good agreement with the model predictions were found for benzene, toluene, ethylbenzene and m-xylene at four different representative fixed concentration ratios after 1 h of exposure but lower agreement to mixture prediction was obtained after 24 h of exposure. A recreated car exhaust mixture, which involved the contribution of the more toxic p-xylene and o-xylene, yielded an acceptable but lower quality prediction as well.
Resumo:
BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.
Resumo:
High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.