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).

Assessment of quality defects in macadamia kernels using NIR spectroscopy

Spectral data were collected of intact and ground kernels using 3 instruments (using Si-PbS, Si, and InGaAs detectors), operating over different areas of the spectrum (between 400 and 2500 nm) and employing transmittance, interactance, and reflectance sample presentation strategies. Kernels were assessed on the basis of oil and water content, and with respect to the defect categories of insect damage, rancidity, discoloration, mould growth, germination, and decomposition. Predictive model performance statistics for oil content models were acceptable on all instruments (R2 > 0.98; RMSECV < 2.5%, which is similar to reference analysis error), although that for the instrument employing reflectance optics was inferior to models developed for the instruments employing transmission optics. The spectral positions for calibration coefficients were consistent with absorbance due to the third overtones of CH2 stretching. Calibration models for moisture content in ground samples were acceptable on all instruments (R2 > 0.97; RMSECV < 0.2%), whereas calibration models for intact kernels were relatively poor. Calibration coefficients were more highly weighted around 1360, 740 and 840 nm, consistent with absorbance due to overtones of O-H stretching and combination. Intact kernels with brown centres or rancidity could be discriminated from each other and from sound kernels using principal component analysis. Part kernels affected by insect damage, discoloration, mould growth, germination, and decomposition could be discriminated from sound kernels. However, discrimination among these defect categories was not distinct and could not be validated on an independent set. It is concluded that there is good potential for a low cost Si photodiode array instrument to be employed to identify some quality defects of intact macadamia kernels and to quantify oil and moisture content of kernels in the process laboratory and for oil content in-line. Further work is required to examine the robustness of predictive models across different populations, including growing districts, cultivars and times of harvest.

Assessing the relationship between patch type and soil mites: A molecular approach

An urgent need exists for indicators of soil health and patch functionality in extensive rangelands that can be measured efficiently and at low cost. Soil mites are candidate indicators, but their identification and handling is so specialised and time-consuming that their inclusion in routine monitoring is unlikely. The aim of this study was to measure the relationship between patch type and mite assemblages using a conventional approach. An additional aim was to determine if a molecular approach traditionally used for soil microbes could be adapted for soil mites to overcome some of the bottlenecks associated with soil fauna diversity assessment. Soil mite species abundance and diversity were measured using conventional ecological methods in soil from patches with perennial grass and litter cover (PGL), and compared to soil from bare patches with annual grasses and/or litter cover (BAL). Soil mite assemblages were also assessed using a molecular method called terminal-restriction fragment length polymorphism (T-RFLP) analysis. The conventional data showed a relationship between patch type and mite assemblage. The Prostigmata and Oribatida were well represented in the PGL sites, particularly the Aphelacaridae (Oribatida). For T-RFLP analysis, the mite community was represented by a series of DNA fragment lengths that reflected mite sequence diversity. The T-RFLP data showed a distinct difference in the mite assemblage between the patch types. Where possible, T-RFLP peaks were matched to mite families using a reference 18S rDNA database, and the Aphelacaridae prevalent in the conventional samples at PGL sites were identified, as were prostigmatids and oribatids. We identified limits to the T-RFLP approach and this included an inability to distinguish some species whose DNA sequences were similar. Despite these limitations, the data still showed a clear difference between sites, and the molecular taxonomic inferences also compared well with the conventional ecological data. The results from this study indicated that the T-RFLP approach was effective in measuring mite assemblages in this system. The power of this technique lies in the fact that species diversity and abundance data can be obtained quickly because of the time taken to process hundreds of samples, from soil DNA extraction to data output on the gene analyser, can be as little as 4 days.