Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

The role of fruit traits of bird-dispersed plants in invasiveness and weed risk assessment

Aim: Birds play a major role in the dispersal of seeds of many fleshy-fruited invasive plants. The fruits that birds choose to consume are influenced by fruit traits. However, little is known of how the traits of invasive plant fruits contribute to invasiveness or to their use by frugivores. We aim to gain a greater understanding of these relationships to improve invasive plant management. Location: South-east Queensland, Australia. Methods: We measure a variety of fruit morphology, pulp nutrient and phenology traits of a suite of bird-dispersed alien plants. Frugivore richness of these aliens was derived from the literature. Using regressions and multivariate methods, we investigate relationships between fruit traits, frugivore richness and invasiveness. Results: Plant invasiveness was negatively correlated to fruit size, and all highly invasive species had quite similar fruit morphology [smaller fruits, seeds of intermediate size and few (<10) seeds per fruit]. Lower pulp water was the only pulp nutrient trait associated with invasiveness. There were strong positive relationships between the diversity of bird frugivores and plant invasiveness, and in the diversity of bird frugivores in the study region and another part of the plants' alien range. Main conclusions: Our results suggest that weed risk assessments (WRA) and predictions of invasive success for bird-dispersed plants can be improved. Scoring criteria for WRA regarding fruit size would need to be system-specific, depending on the fruit-processing capabilities of local frugivores. Frugivore richness could be quantified in the plant's natural range, its invasive range elsewhere, or predictions made based on functionally similar fruits.

Prediction of breeding values for average fruit weight in mango using a multivariate individual mixed model

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.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

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.

A Comparison of Methods for Describing Irregular Animal Growth and Testing for Treatment Effects

In many designed experiments with animals liveweight is recorded several times during the trial. Such data are commonly referred to as repeated measures data. An aim of such experiments is generally to compare the growth patterns for the applied treatments. This paper discusses some of the methods of analysing repeated measures data and illustrates the use of cubic smoothing splines to describe irregular cattle growth data. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

Using simulation techniques to investigate methods to determine resistance of helminths to anthelmintic treatment

The widespread and increasing resistance of internal parasites to anthelmintic control is a serious problem for the Australian sheep and wool industry. As part of control programmes, laboratories use the Faecal Egg Count Reduction Test (FECRT) to determine resistance to anthelmintics. It is important to have confidence in the measure of resistance, not only for the producer planning a drenching programme but also for companies investigating the efficacy of their products. The determination of resistance and corresponding confidence limits as given in anthelmintic efficacy guidelines of the Standing Committee on Agriculture (SCA) is based on a number of assumptions. This study evaluated the appropriateness of these assumptions for typical data and compared the effectiveness of the standard FECRT procedure with the effectiveness of alternative procedures. Several sets of historical experimental data from sheep and goats were analysed to determine that a negative binomial distribution was a more appropriate distribution to describe pre-treatment helminth egg counts in faeces than a normal distribution. Simulated egg counts for control animals were generated stochastically from negative binomial distributions and those for treated animals from negative binomial and binomial distributions. Three methods for determining resistance when percent reduction is based on arithmetic means were applied. The first was that advocated in the SCA guidelines, the second similar to the first but basing the variance estimates on negative binomial distributions, and the third using Wadley’s method with the distribution of the response variate assumed negative binomial and a logit link transformation. These were also compared with a fourth method recommended by the International Co-operation on Harmonisation of Technical Requirements for Registration of Veterinary Medicinal Products (VICH) programme, in which percent reduction is based on the geometric means. A wide selection of parameters was investigated and for each set 1000 simulations run. Percent reduction and confidence limits were then calculated for the methods, together with the number of times in each set of 1000 simulations the theoretical percent reduction fell within the estimated confidence limits and the number of times resistance would have been said to occur. These simulations provide the basis for setting conditions under which the methods could be recommended. The authors show that given the distribution of helminth egg counts found in Queensland flocks, the method based on arithmetic not geometric means should be used and suggest that resistance be redefined as occurring when the upper level of percent reduction is less than 95%. At least ten animals per group are required in most circumstances, though even 20 may be insufficient where effectiveness of the product is close to the cut off point for defining resistance.

Investigation and application of methods for enumerating heterotrophs and Escherichia coli in the air within piggery sheds

Aims: To investigate methods for the recovery of airborne bacteria within pig sheds and to then use the appropriate methods to determine the levels of heterotrophs and Escherichia coli in the air within sheds. Methods and Results: AGI-30 impingers and a six-stage Andersen multi-stage sampler (AMS) were used for the collection of aerosols. Betaine and catalase were added to impinger collection fluid and the agar plates used in the AMS. Suitable media for enumerating E. coli with the Andersen sampler were also evaluated. The addition of betaine and catalase gave no marked increase in the recovery of heterotrophs or E. coli. No marked differences were found in the media used for enumeration of E. coli. The levels of heterotrophs and E. coli in three piggeries, during normal pig activities, were 2Æ2 · 105 and 21 CFU m)3 respectively. Conclusions: The failure of the additives to improve the recovery of either heterotrophs or E. coli suggests that these organisms are not stressed in the piggery environment. The levels of heterotrophs in the air inside the three Queensland piggeries investigated are consistent with those previously reported in other studies. Flushing with ponded effluent had no marked or consistent effect on the heterotroph or E. coli levels. Significance and Impact of the Study: Our work suggests that levels of airborne heterotrophs and E. coli inside pig sheds have no strong link with effluent flushing. It would seem unlikely that any single management activity within a pig shed has a dominant influence on levels of airborne heterotrophs and E. coli

Comparison of sampling sites and detection methods for Haemophilus parasuis

Objective To improve the isolation rate and identification procedures for Haemophilus parasuis from pig tissues. Design Thirteen sampling sites and up to three methods were used to confirm the presence of H. parasuis in pigs after experimental challenge. Procedure Colostrum-deprived, naturally farrowed pigs were challenged intratracheally with H parasuis serovar 12 or 4. Samples taken during necropsy were either inoculated onto culture plates, processed directly for PCR or enriched prior to being processed for PCR. The recovery of H parasuis from different sampling sites and using different sampling methods was compared for each serovar. Results H parasuis was recovered from several sample sites for all serovar 12 challenged pigs, while the trachea was the only positive site for all pigs following serovar 4 challenge. The method of solid medium culture of swabs, and confirmation of the identity of cultured bacteria by PCR, resulted in 38% and 14% more positive results on a site basis for serovars 12 and 4, retrospectively, than direct PCR on the swabs. This difference was significant in the serovar 12 challenge. Conclusion Conventional culture proved to be more effective in detecting H parasuis than direct PCR or PCR on enrichment broths. For subacute (serovar 4) infections, the most successful sites for culture or direct PCR were pleural fluid, peritoneal fibrin and fluid, lung and pericardial fluid. For acute (serovar 12) infections, the best sites were lung, heart blood, affected joints and brain. The methodologies and key sampling sites identified in this study will enable improved isolation of H parasuis and aid the diagnosis of Glässer's disease.

A comparison of mark-recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos

Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

Comparison of nitrogen fertilization methods and rates for subsurface drip irrigated corn in the semi-arid Great Plains

In semi-arid areas such as western Nebraska, interest in subsurface drip irrigation (SDI) for corn is increasing due to restricted irrigation allocations. However, crop response quantification to nitrogen (N) applications with SDI and the environmental benefits of multiple in-season (IS) SDI N applications instead of a single early-season (ES) surface application are lacking. The study was conducted in 2004, 2005, and 2006 at the University of Nebraska-Lincoln West Central Research and Extension Center in North Platte, Nebraska, comparing two N application methods (IS and ES) and three N rates (128, 186, and 278 kg N ha(-1)) using a randomized complete block design with four replications. No grain yield or biomass response was observed in 2004. In 2005 and 2006, corn grain yield and biomass production increased with increasing N rates, and the IS treatment increased grain yield, total N uptake, and gross return after N application costs (GRN) compared to the ES treatment. Chlorophyll meter readings taken at the R3 corn growth stage in 2006 showed that less N was supplied to the plant with ES compared to the IS treatment. At the end of the study, soil NO3-N masses in the 0.9 to 1.8 m depth were greater under the IS treatment compared to the ES treatment. Results suggested that greater losses of NO3-N below the root zone under the ES treatment may have had a negative effect on corn production. Under SDI systems, fertigating a recommended N rate at various corn growth stages can increase yields, GRN, and reduce NO3-N leaching in soils compared to concentrated early-season applications.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Hardness Methods for Testing Maize Kernels

Maize is a highly important crop to many countries around the world, through the sale of the maize crop to domestic processors and subsequent production of maize products and also provides a staple food to subsistance farms in undeveloped countries. In many countries, there have been long-term research efforts to develop a suitable hardness method that could assist the maize industry in improving efficiency in processing as well as possibly providing a quality specification for maize growers, which could attract a premium. This paper focuses specifically on hardness and reviews a number of methodologies as well as important biochemical aspects of maize that contribute to maize hardness used internationally. Numerous foods are produced from maize, and hardness has been described as having an impact on food quality. However, the basis of hardness and measurement of hardness are very general and would apply to any use of maize from any country. From the published literature, it would appear that one of the simpler methods used to measure hardness is a grinding step followed by a sieving step, using multiple sieve sizes. This would allow the range in hardness within a sample as well as average particle size and/or coarse/fine ratio to be calculated. Any of these parameters could easily be used as reference values for the development of near-infrared (NIR) spectroscopy calibrations. The development of precise NIR calibrations will provide an excellent tool for breeders, handlers, and processors to deliver specific cultivars in the case of growers and bulk loads in the case of handlers, thereby ensuring the most efficient use of maize by domestic and international processors. This paper also considers previous research describing the biochemical aspects of maize that have been related to maize hardness. Both starch and protein affect hardness, with most research focusing on the storage proteins (zeins). Both the content and composition of the zein fractions affect hardness. Genotypes and growing environment influence the final protein and starch content and. to a lesser extent, composition. However, hardness is a highly heritable trait and, hence, when a desirable level of hardness is finally agreed upon, the breeders will quickly be able to produce material with the hardness levels required by the industry.

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.

An improved technique for estimating short-term survival of released line-caught fish, and an application comparing barotrauma-relief methods in red emperor (Lutjanus sebae Cuvier 1816).

Promotion of better procedures for releasing undersize fish, advocacy of catch-and-release angling, and changing minimum legal sizes are increasingly being used as tools for sustainable management of fish stocks. However without knowing the proportion of released fish that survive, the conservation value of any of these measures is uncertain. We developed a floating vertical enclosure to estimate short-term survival of released line-caught tropical and subtropical reef-associated species, and used it to compare the effectiveness of two barotrauma-relief procedures (venting and shotline releasing) on red emperor (Lutjanus sebae). Barotrauma signs varied with capture depth, but not with the size of the fish. Fish from the greatest depths (40-52 m) exhibited extreme signs less frequently than did those from intermediate depths (30-40 m), possibly as a result of swim bladder gas being vented externally through a rupture in the body wall. All but two fish survived the experiment, and as neither release technique significantly improved short-term survival of the red emperor over non-treatment we see little benefit in promoting either venting or shotline releasing for this comparatively resilient species. Floating vertical enclosures can improve short-term post-release mortality estimates as they overcome many problems encountered when constraining fish in submerged cages.

Controlled pollination methods for creating Corymbia hybrids.

Inter-specific Corymbia hybrids are of increasing interest to plantation forestry, yet there is little knowledge of the most suitable controlled pollination methods for this genus. Inter-specific crosses were made between C. torelliana [CT(maternal parent)] and C. citriodora subsp. variegata (CCV), C. henryi (CH) and C. citriodora subsp. citriodora (CCC) using conventional pollination, one-stop pollination (OSP) and artificially-induced protogyny on yellow buds (AIP Y) pollination methods. Additional treatments included AIP on green buds (AIP G) and the use of exclusion bags for the OSP and AIP methods. Inter-specific hybrids (CT x CCV, CT x CH and CT x CCC) were successfully created using all three pollination methods. The AIP Y treatment provided the highest seed yields and achieved time savings of >41% over the conventional and OSP methods, resulting in up to five-fold increases in operator productivity. However, the AIP Y treatment also had the highest C. torelliana contamination levels (9.3–13.2%). The use of exclusion bags with the AIP method had minimal effect on contamination rates, indicating a high proportion of selfpollen contamination. Contamination rates varied between maternal parents, suggesting variation in selfcompatibility for C. torelliana individuals. AIP using semi-ripe green buds was not effective at reducing selfing and had low operator productivity. The AIP method is suitable for use in a large-scale hybrid breeding program for C. torelliana. When self-pollination effects are managed, it could greatly reduce the costs associated with the production of seed of elite family crosses for commercial forestry deployment.