Improving the quality of kikuyu by reducing the lignin content

Development of improved pasture grass via chemical mutagenesis and selection of mutations in lignin genes.

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.

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.

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. © 2015, The Author(s).

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).

Influence of environmental and instrumental variables on the non-invasive prediction of Brix in pineapple using near infrared spectroscopy

The Brix content of pineapple fruit can be non-invasively predicted from the second derivative of near infrared reflectance spectra. Correlations obtained using a NIRSystems 6500 spectrophotometer through multiple linear regression and modified partial least squares analyses using a post-dispersive configuration were comparable with that from a pre-dispersive configuration in terms of accuracy (e.g. coefficient of determination, R2, 0.73; standard error of cross validation, SECV, 1.01°Brix). The effective depth of sample assessed was slightly greater using the post-dispersive technique (about 20 mm for pineapple fruit), as expected in relation to the higher incident light intensity, relative to the pre-dispersive configuration. The effect of such environmental variables as temperature, humidity and external light, and instrumental variables such as the number of scans averaged to form a spectrum, were considered with respect to the accuracy and precision of the measurement of absorbance at 876 nm, as a key term in the calibration for Brix, and predicted Brix. The application of post-dispersive near infrared technology to in-line assessment of intact fruit in a packing shed environment is discussed.

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.

Piggery pond sludge as a nitrogen source for crops. 1. Mineral N supply estimated from laboratory incubations and field application of stockpiled and wet sludge

Piggery pond sludge (PPS) was applied, as-collected (Wet PPS) and following stockpiling for 12 months (Stockpiled PPS), to a sandy Sodosol and clay Vertosol at sites on the Darling Downs of Queensland. Laboratory measures of N availability were carried out on unamended and PPS-amended soils to investigate their value in estimating supplementary N needs of crops in Australia's northern grains region. Cumulative net N mineralised from the long-term (30 weeks) leached aerobic incubation was described by a first-order single exponential model. The mineralisation rate constant (0.057/week) was not significantly different between Control and PPS treatments or across soil types, when the amounts of initial mineral N applied in PPS treatments were excluded. Potentially mineralisable N (No) was significantly increased by the application of Wet PPS, and increased with increasing rate of application. Application of Wet PPS significantly increased the total amount of inorganic N leached compared with the Control treatments. Mineral N applied in Wet PPS contributed as much to the total mineral N status of the soil as did that which mineralised over time from organic N. Rates of C02 evolution during 30 weeks of aerobic leached incubation indicated that the Stockpiled PPS was more stabilised (19-28% of applied organic C mineralised) than the WetPPS (35-58% of applied organic C mineralised), due to higher lignin content in the former. Net nitrate-N produced following 12 weeks of aerobic non-leached incubation was highly correlated with net nitrate-N leached during 12 weeks of aerobic incubation (R^2 = 0.96), although it was <60% of the latter in both sandy and clayey soils. Anaerobically mineralisable N determined by waterlogged incubation of laboratory PPS-amended soil samples increased with increasing application rate of Wet PPS. Anaerobically minemlisable N from field-moist soil was well correlated with net N mineralised during 30 weeks of aerobic leached incubation (R^2 =0.90 sandy soil; R^2=0.93 clay soil). In the clay soil, the amount of mineral N produced from all the laboratory incubations was significantly correlated with field-measured nitrate-N in the soil profile (0-1.5 m depth) after 9 months of weed-free fallow following PPS application. In contrast, only anaerobic mineralisable N was significantly correlated with field nitrate-N in the sandy soil. Anaerobic incubation would, therefore, be suitable as a rapid practical test to estimate potentially mineralisable N following applications of different PPS materials in the field.

Assessment of internal quality attributes of mandarin fruit. 1. NIR calibration model development

The utility of near infrared spectroscopy as a non-invasive technique for the assessment of internal eating quality parameters of mandarin fruit (Citrus reticulata cv. Imperial) was assessed. The calibration procedure for the attributes of TSS (total soluble solids) and DM (dry matter) was optimised with respect to a reference sampling technique, scan averaging, spectral window, data pre-treatment (in terms of derivative treatment and scatter correction routine) and regression procedure. The recommended procedure involved sampling of an equatorial position on the fruit with 1 scan per spectrum, and modified partial least squares model development on a 720–950-nm window, pre-treated as first derivative absorbance data (gap size of 4 data points) with standard normal variance and detrend scatter correction. Calibration model performance for the attributes of TSS and DM content was encouraging (typical Rc2 of >0.75 and 0.90, respectively; typical root mean squared standard error of calibration of <0.4 and 0.6%, respectively), whereas that for juiciness and total acidity was unacceptable. The robustness of the TSS and DM calibrations across new populations of fruit is documented in a companion study.

Quantitative assessment of total phenol contents of European oak (Quercus petraea and Quercus robur) by diffuse reflectance NIR spectroscopy on solid wood surfaces

Near infrared spectroscopy (NIRS) combined with multivariate analysis techniques was applied to assess phenol content of European oak. NIRS data were firstly collected directly from solid heartwood surfaces: in doing so, the spectra were recorded separately from the longitudinal radial and the transverse section surfaces by diffuse reflectance. The spectral data were then pretreated by several pre-processing procedures, such as multiplicative scatter correction, first derivative, second derivative and standard normal variate. The tannin contents of sawmill collected from the longitudinal radial and transverse section surfaces were determined by quantitative extraction with water/methanol (1:4, by vol). Then, total phenol contents in tannin extracts were measured by the Folin-Ciocalteu method. The NIR data were correlated against the Folin-Ciocalteu results. Calibration models built with partial least squares regression displayed strong correlation - as expressed by high determination correlation coefficient (r2) and high ratio of performance to deviation (RPD) - between measured and predicted total phenols content, and weak calibration and prediction errors (RMSEC, RMSEP). The best calibration was provided with second derivative spectra (r2 value of 0.93 for the longitudinal radial plane and of 0.91 for the transverse section plane). This study illustrates that the NIRS technique when used in conjunction with multivariate analysis could provide reliable, quick and non-destructive assessment of European oak heartwood extractives.

NIR model development and robustness in prediction of melon fruit total soluble solids

Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695-1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The 'global' modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the 'local' MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.

Phenotypic variation in natural populations of kikuyu in Australia

The quality of tropical grasses is a major limitation to animal production in tropical and subtropical areas. This is mainly associated with the lower digestibility because C4 grasses have higher fibre levels. Any improvement in quality would require a reduction in the lignin and an increase in the digestion of the neutral detergent fibre content of these plants (Clark and Wilson 1993). Kikuyu (Pennisetum clandestinum) is an important grass for the dairy and beef industries of the subtropics of Australia, South Africa and New Zealand (Mears 1970). Increased digestibility could substantially improve animal production in these industries. These experiments investigated the variation in agronomic and quality of natural populations selected from diverse regions within Australia. Runners of 14 kikuyu selections were collected by project staff or local agronomists from areas considered to have grown kikuyu for over 30 years while Whittet and Noonan were established by seed. Entries were established as single spaced plants on a 1.5 m grid in a randomised block with 3 replicates and evaluated under irrigation at Mutdapilly (brown podsol) and Wollongbar (red ferrosol). Foliage height, forage production and runner yield were assessed along with crude protein (CP), in vitro dry matter digestibility (IVDMD), metabolisable energy (ME), acid detergent fibre (ADF) and neutral detergent fibre (NDF) content of the leaf in autumn, winter and spring.

Leaf trait co-ordination in relation to construction cost, carbon gain and resource-use efficiency in exotic invasive and native woody vine species

Background and Aims: Success of invasive plant species is thought to be linked with their higher leaf carbon fixation strategy, enabling them to capture and utilize resources better than native species, and thus pre-empt and maintain space. However, these traits are not well-defined for invasive woody vines. Methods: In a glass house setting, experiments were conducted to examine how leaf carbon gain strategies differ between non-indigenous invasive and native woody vines of south-eastern Australia, by investigating their biomass gain, leaf structural, nutrient and physiological traits under changing light and moisture regimes. Key Results: Leaf construction cost (CC), calorific value and carbon : nitrogen (C : N) ratio were lower in the invasive group, while ash content, N, maximum photosynthesis, light-use efficiency, photosynthetic energyuse efficiency (PEUE) and specific leaf area (SLA) were higher in this group relative to the native group. Trait plasticity, relative growth rate (RGR), photosynthetic nitrogen-use efficiency and water-use efficiency did not differ significantly between the groups. However, across light resource, regression analyses indicated that at a common (same) leaf CC and PEUE, a higher biomass RGR resulted for the invasive group; also at a common SLA, a lower CC but higher N resulted for the invasive group. Overall, trait co-ordination (using pair-wise correlation analyses) was better in the invasive group. Ordination using 16 leaf traits indicated that the major axis of invasive-native dichotomy is primarily driven by SLA and CC (including its components and/or derivative of PEUE) and was significantly linked with RGR. Conclusions: These results demonstrated that while not all measures of leaf resource traits may differ between the two groups, the higher level of trait correlation and higher revenue returned (RGR) per unit of major resource need (CC) and use (PEUE) in the invasive group is in line with their rapid spread where introduced.

Factors contributing to wear tolerance of Bermudagrass (Cynodon dactylon (L.) Pers., C. dactylon x C. transvaalensis Burtt-Davey) on a sand-based profile under simulated sports field conditions

Wear resistance and recovery of 8 Bermudagrass (Cynodon dactylon (L.) Pers.) and hybrid Bermudagrass (C. Dactylon x C. transvaalensis Burtt-Davey) cultivars grown on a sandbased soil profile near Brisbane, Australia, were assessed in 4 wear trials conducted over a two year period. Wear was applied on a 7-day or a 14-day schedule by a modified Brinkman Traffic Simulator for 6-14 weeks at a time, either during winter-early spring or during summer-early autumn. The more frequent wear under the 7-day treatment was more damaging to the turf than the 14-day wear treatment, particularly during winter when its capacity for recovery from wear was severely restricted. There were substantial differences in wear tolerance among the 8 cultivars investigated, and the wear tolerance rankings of some cultivars changed between years. Wear tolerance was associated with high shoot density, a dense stolon mat strongly rooted to the ground surface, high cell wall strength as indicated by high total cell wall content, and high levels of lignin and neutral detergent fiber. Wear tolerance was also affected by turf age, planting sod quality, and wet weather. Resistance to wear and recovery from wear are both important components of wear tolerance, but the relative importance of their contributions to overall wear tolerance varies seasonally with turf growth rate.

A tilling approach to develop high quality tropical and sub-tropical pasture gra

This project aims to develop high quality kikuyu pasture grass via chemical mutagenesis, followed by screening for mutations in lignin biosynthesis genes.