Measuring free ellagic acid: influence of extraction conditions on recovery by studying solubility and UV-Visible spectra

Recent investigations into plant tissues have indicated that the free form of the natural polyphenolic antioxidant, ellagic acid (EA), is much more plentiful than first envisaged; consequently a re-assessment of solvent systems for the extraction of this water-insoluble form is needed. As EA solubility and its UV-Vis spectrum, commonly used for detection and quantification, are both governed by pH, an understanding of this dependence is vital if accurate EA measurements are to be achieved. After evaluating the pH effects on the solubility and UV-Vis spectra of commercial EA, an extraction protocol was devised that promoted similar pH conditions for both standard solutions and plant tissue extracts. The extraction so devised followed by HPLC with photodiode-array detection (DAD) provided a simple, sensitive and validated methodology that determined free EA in a variety of plant extracts. The use of 100 % methanol or a triethanolamine-based mixture as the standard dissolving solvents were the best choices, while these higher pH-generating solvents were more efficient in extracting EA from the plants tested with the final choice allied to the plants’ natural acidity. Two of the native Australian plants anise myrtle (Syzygium anisatum) and Kakadu plum (Terminalia ferdinandiana) exhibited high concentrations of free EA. Furthermore, the dual approach to measuring EA UV-Vis spectra made possible an assessment of the effect of acidified eluent on EA spectra when the DAD was employed.

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).

Deviant near-infrared spectra identifies Corymbia hybrids

The study examined the potential of Near Infrared Reflectance (NIR) spectroscopy for field diagnosis of hybrids between Corymbia (formerly Eucalyptus) species. NIR profiles were generated by scanning foliage from a total of 383 hybrid and 533 parental seedlings grown in a common garden and partial least squares discriminant analysis was used to test three-way model power to assign individuals to their appropriate taxon; either a parental or F1 hybrid class. Using the optimised conditions, fresh foliage from eight-month-old seedlings and a handheld NIR instrument (950–1800 nm), the mean assignment rates for the three hybrid groups ranged from 76% to 90%. Hybrid-parent contrast of NIR spectra deviated more so than parent–parent contrast. The F1 taxon assignment rates were usually higher than those for parents at 100% and 72%, respectively. Hybrid resolution was even greater for 2nd generation backcross hybrids. Similar to studies of morphology, taxon assignments tended to be more accurate for hybrid groups in which the parental taxa were more divergent. The practical application of this technique for hybrid diagnosis of seedlings in the nursery will require careful attention to control environmental factors because seedling age and storage effects influenced the ability of NIR to identify hybrids. The technique may also necessitate the generation of comparable reference populations, although exclusions approaches to analysis may circumvent the need for reference populations. The application of NIR in field diagnosis will be further complicated by the need to generate global models across environments but such models have been obtained for reliable prediction of chemistries in other situations.

Estimating Hydrogen Cyanide in Forage Sorghum (Sorghum bicolor) by Near-Infrared Spectroscopy

Hydrogen cyanide (HCN) is a toxic chemical that can potentially cause mild to severe reactions in animals when grazing forage sorghum. Developing technologies to monitor the level of HCN in the growing crop would benefit graziers, so that they can move cattle into paddocks with acceptable levels of HCN. In this study, we developed near-infrared spectroscopy (MRS) calibrations to estimate HCN in forage sorghum and hay. The full spectral NIRS range (400-2498 nm) was used as well as specific spectral ranges within the full spectral range, i.e., visible (400-750 nm), shortwave (800-1100 nm) and near-infrared (NIR) (1100-2498 nm). Using the full spectrum approach and partial least-squares (PLS), the calibration produced a coefficient of determination (R-2) = 0.838 and standard error of cross-validation (SECV) = 0.040%, while the validation set had a R-2 = 0.824 with a low standard error of prediction (SEP = 0.047%). When using a multiple linear regression (MLR) approach, the best model (NIR spectra) produced a R-2 = 0.847 and standard error of calibration (SEC) = 0.050% and a R-2 = 0.829 and SEP = 0.057% for the validation set. The MLR models built from these spectral regions all used nine wavelengths. Two specific wavelengths 2034 and 2458 nm were of interest, with the former associated with C=O carbonyl stretch and the latter associated with C-N-C stretching. The most accurate PLS and MLR models produced a ratio of standard error of prediction to standard deviation of 3.4 and 3.0, respectively, suggesting that the calibrations could be used for screening breeding material. The results indicated that it should be feasible to develop calibrations using PLS or MLR models for a number of users, including breeding programs to screen for genotypes with low HCN, as well as graziers to monitor crop status to help with grazing efficiency.

The utility of near infrared spectroscopy for age estimation of deepwater sharks

Reliable age information is vital for effective fisheries management, yet age determinations are absent for many deepwater sharks as they cannot be aged using traditional methods of growth bands counts. An alternative approach to ageing using near infrared spectroscopy (NIRS) was investigated using dorsal fin spines, vertebrae and fin clips of three species of deepwater sharks. Ages were successfully estimated for the two dogfish, Squalus megalops and Squalus montalbani, and NIRS spectra were correlated with body size in the catshark, Asymbolus pallidus. Correlations between estimated-ages of the dogfish dorsal fin spines and their NIRS spectra were good, with S. megalops R2=0.82 and S. montalbani R2=0.73. NIRS spectra from S. megalops vertebrae and fin clips that have no visible growth bands were correlated with estimated-ages, with R2=0.89 and 0.76, respectively. NIRS has the capacity to non-lethally estimate ages from fin spines and fin clips, and thus could significantly reduce the numbers of sharks that need to be lethally sampled for ageing studies. The detection of ageing materials by NIRS in poorly calcified deepwater shark vertebrae could potentially enable ageing of this group of sharks that are vulnerable to exploitation.