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.

Bibulocystis gloriosa sp nov (Pucciniales) on Caesalpinia scortechinii in Queensland, with comments on Spumula caesalpiniae

A rust causing leaf spotting and distortion of twigs and branches of Caesalpinia scortechinii in Queensland is described as the new species Bibulocystis gloriosa. Uredinia and telia occur on spotted pinnules, and pycnia, aecial uredinia and telia on galled and twisted leaf rachides, twigs and branches. B. gloriosa is similar to Bibulocystis viennotii on Albizia granulosa in New Caledonia in having a macrocyclic life cycle with all spore states, and teliospores with two fertile cells and two cysts. It differs in having aecial urediniospores and urediniospores with uniformly thickened walls and several scattered germ pores, rather than the apically thickened walls and equatorial germ pores of B. viennotii. Teliospores in the two species are similar in size, but those of B. gloriosa have proportionally larger fertile cells and smaller cysts than in B. viennotii. To date, B. gloriosa is known from only two localities in south-eastern Queensland. Comparison with the type specimen of Spumula caesalpiniae on Caesalpinia nuga from Indonesia has shown that the two rusts are generically distinct.

Gaseous Nitrogen Losses Following Soil Amendment with Biosolids under Controlled Conditions.

This paper quantifies gaseous N losses due to ammonia volatilisation and denitrification under controlled conditions at 30 degrees C and 75% to 150% of Field Capacity (FC). Biosolids were mixed with two contrasting soils from subtropical Australia at a rate designed to meet crop N requirements for irrigated cotton or maize (i.e., equivalent to 180 kg N ha(-1)). In the first experiment, aerobically (AE) and anaerobically (AN) digested biosolids were mixed into a heavy Vertosol soil and then incubated for 105 days. Ammonia volatilization over 72 days accounted for less than 4% of the applied NH4-N but 24% (AN) to 29% (AE) of the total applied biosolids' N was lost through denitrification in 105 days. In the second experiment AN biosolids with and without added polyacrimide polymer were mixed with either a heavy Vertosol or a lighter Red Ferrosol and then incubated for 98 days. The N loss was higher from the Vertosol with 16-29% of total N applied versus the Red Ferrosol with 7-10% of total N applied, while addition of polymer to the biosolids increased N loss from 7 to 10% and from 16 to 29% in the Red Ferrosol and Vertosol, respectively. A major product from the denitrification process was N-2 gas, accounting for >90% of the emitted N gases from both experiments. Our findings demonstrate that denitrification could be a major pathway of gaseous N losses under warm and moist conditions.

Effect of Broadcast Baiting on Abundance Patterns of Red Imported Fire Ants (Hymenoptera: Formicidae) and Key Local Ant Genera at Long-Term Monitoring Sites in Brisbane, Australia

In 2001, the red imported fire ant (Solenopsis invicta Buren) was identified in Brisbane, Australia. An eradication program involving broadcast bait treatment with two insect growth regulators and a metabolic inhibitor began in September of that year and is currently ongoing. To gauge the impacts of these treatments on local ant populations, we examined long-term monitoring data and quantified abundance patterns of S. invicta and common local ant genera using a linear mixed-effects model. For S. invicta, presence in pitfalls reduced over time to zero on every site. Significantly higher numbers of S. invicta workers were collected on high-density polygyne sites, which took longer to disinfest compared with monogyne and low-density polygyne sites. For local ants, nine genus groups of the 10 most common genera analyzed either increased in abundance or showed no significant trend. Five of these genus groups were significantly less abundant at the start of monitoring on high-density polygyne sites compared with monogyne and low-density polygyne sites. The genus Pheidole significantly reduced in abundance over time, suggesting that it was affected by treatment efforts. These results demonstrate that the treatment regime used at the time successfully removed S. invicta from these sites in Brisbane, and that most local ant genera were not seriously impacted by the treatment. These results have important implications for current and future prophylactic treatment efforts, and suggest that native ants remain in treated areas to provide some biological resistance to S. invicta.

Quantitative effects of in-line operations on Campylobacter and Escherichia coli through two Australian broiler processing plants

Campylobacter is an important food borne pathogen, mainly associated with poultry. A lack of through-chain quantitative Campylobacter data has been highlighted within quantitative risk assessments. The aim of this study was to quantitatively and qualitatively measure Campylobacter and Escherichia coli concentration on chicken carcasses through poultry slaughter. Chickens (n = 240) were sampled from each of four flocks along the processing chain, before scald, after scald, before chill, after chill, after packaging and from individual caeca. The overall prevalence of Campylobacter after packaging was 83% with a median concentration of 0.8 log10 CFU/mL. The processing points of scalding and chilling had significant mean reductions of both Campylobacter (1.8 and 2.9 log10 CFU/carcase) and E. coli (1.3 and 2.5 log10 CFU/carcase). The concentration of E. coli and Campylobacter was significantly correlated throughout processing indicating that E. coli may be a useful indicator organism for reductions in Campylobacter concentration. The carriage of species varied between flocks, with two flocks dominated by Campylobacter coli and two flocks dominated by Campylobacter jejuni. Current processing practices can lead to significant reductions in the concentration of Campylobacter on carcasses. Further understanding of the variable effect of processing on Campylobacter and the survival of specific genotypes may enable more targeted interventions to reduce the concentration of this poultry associated pathogen.

Fungus-feeding Thysanoptera: Phlaeothripinae of the Idiothrips genus-group in Australia, with nine new species

In a group of fungus-feeding Phlaeothripinae characterized by complex body sculpture, identification keys are provided to three genera and 15 species from Australia, including nine new species. In the genus Azaleothrips one new species is described, and one Asian species is newly recorded from Australia. The genus Stictothrips is recorded from Australia for the first time, with two new species. Within the genus Strepterothrips considerable structural diversity is recorded including three new species in which antennal segment III is greatly reduced and bears no sense cones. Some species in this genus exhibit the unusual condition of having several setae on the pelta, the first abdominal tergite. Problems in the production of generic diagnoses within the Phlaeothripinae are discussed.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.