Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy.

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.

Characterization of highly informative cross-species microsatellite panels for the Australian dugong (Dugong dugon) and Florida manatee (Trichechus manatus latirostris) including five novel primers

The Australian dugong (Dugong dugon) and Florida manatee (Trichechus manatus latirostris) are threatened species of aquatic mammals in the order Sirenia. Sirenian conservation and management actions would benefit from a more complete understanding of genetic diversity and population structure. Generally, species-specific microsatellite markers are employed in conservation genetic studies; however, robust markers can be difficult and costly to isolate. To increase the number of available markers, dugong and manatee microsatellite primers were evaluated for cross-species amplification. Furthermore, one manatee and four dugong novel primers are reported. After polymerase chain reaction optimization, 23 (92%) manatee primers successfully amplified dugong DNA, of which 11 (48%) were polymorphic. Of the 32 dugong primers tested, 27 (84%) yielded product in the manatee, of which 17 (63%) were polymorphic. Dugong and manatee primers were compared and the most informative markers were selected to create robust and informative marker-panels for each species. These cross-species microsatellite marker-panels can be employed to assess other sirenian populations and can provide beneficial information for the protection and management of these unique mammals.

Sexing Sirenians: Validation of Visual and Molecular Sex Determination in Both Wild Dugongs (Dugong dugon) and Florida Manatees (Trichechus manatus latirostris)

Sexing wild marine mammals that show little to no sexual dimorphism is challenging. For sirenians that are difficult to catch or approach closely, molecular sexing from tissue biopsies offers an alternative method to visual discrimination. This paper reports the results of a field study to validate the use of two sexing methods: (1) visual discrimination of sex vs (2) molecular sexing based on a multiplex PCR assay which amplifies the male-specific SRY gene and differentiates ZFX and ZFY gametologues. Skin samples from 628 dugongs (Dugong dugon) and 100 Florida manatees (Trichechus manatus latirostris) were analysed and assigned as male or female based on molecular sex. These individuals were also assigned a sex based on either direct observation of the genitalia and/or the association of the individual with a calf. Individuals of both species showed 93 to 96% congruence between visual and molecular sexing. For the remaining 4 to 7%, the discrepancies could be explained by human error. To mitigate this error rate, we recommend using both of these robust techniques, with routine inclusion of sex primers into microsatellite panels employed for identity, along with trained field observers and stringent sample handling.

Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit

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.

Effect of Time of Planting and Plant Size on the Productivity of ‘Festival’ and ‘Florida Fortuna’ Strawberry Plants in a Subtropical Environment

The effect of time of planting and plant size on the performance of ‘Festival’ and ‘Florida Fortuna’ strawberry (Fragaria ×ananassa) plants was studied at Nambour in southeastern Queensland, Australia, over 2 years. The main objective of the work was to determine whether small plants yielded proportionally less than large plants as planting was delayed. First, bare-rooted transplants of ‘Festival’ were divided into small (crown diameters ranging from 6 to 10 mm) or large plants (10 to 17 mm) and planted in late March, mid-April, or late April. Second, transplants of ‘Florida Fortuna’ were divided into small (5 to 8 mm) or large plants (8 to 17 mm) and planted in early April, mid-April, or early May. The early planting for each cultivar corresponded with the time that the transplants are first available from commercial strawberry nurseries. Yields were generally greater in plants planted in late March/early April compared with plants planted later. Differences in yield between the small and large plants were consistent across the different times of planting, with the small plants always having lower yields. Small transplants are an issue for the productivity of strawberry fields in this environment whether they are planted early or late. Producers should consider paying a premium for large transplants delivered early in the season.

Variation in the hindgut microbial communities of the Florida manatee, Trichechus manatus latirostris over winter in Crystal River, Florida

The Florida manatee, Trichechus manatus latirostris, is a hindgut-fermenting herbivore. In winter, manatees migrate to warm water overwintering sites where they undergo dietary shifts and may suffer from cold-induced stress. Given these seasonally induced changes in diet, the present study aimed to examine variation in the hindgut bacterial communities of wild manatees overwintering at Crystal River, west Florida. Faeces were sampled from 36 manatees of known sex and body size in early winter when manatees were newly arrived and then in mid-winter and late winter when diet had probably changed and environmental stress may have increased. Concentrations of faecal cortisol metabolite, an indicator of a stress response, were measured by enzyme immunoassay. Using 454-pyrosequencing, 2027 bacterial operational taxonomic units were identified in manatee faeces following amplicon pyrosequencing of the 16S rRNA gene V3/V4 region. Classified sequences were assigned to eight previously described bacterial phyla; only 0.36% of sequences could not be classified to phylum level. Five core phyla were identified in all samples. The majority (96.8%) of sequences were classified as Firmicutes (77.3 ± 11.1% of total sequences) or Bacteroidetes (19.5 ± 10.6%). Alpha-diversity measures trended towards higher diversity of hindgut microbiota in manatees in mid-winter compared to early and late winter. Beta-diversity measures, analysed through permanova, also indicated significant differences in bacterial communities based on the season.

A novel method for the age estimation of Saddletail snapper (Lutjanus malabaricus) using Fourier Transform-near infrared (FT-NIR) spectroscopy

Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

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.