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This study aimed to evaluate the potential of FT-Raman spectroscopy in the prediction of the chemical composition of Lavandula spp. monofloral honey. Partial Least Squares (PLS) regression models were performed for the quantitative estimation and the results were correlated with those obtained using reference methods. Good calibration models were obtained for electrical conductivity, ash, total acidity, pH, reducing sugars, hydroxymethylfurfural (HMF), proline, diastase index, apparent sucrose, total flavonoids content and total phenol content. On the other hand, the model was less accurate for pH determination. The calibration models had high r 2 (ranging between 92.8% and 99.9%), high residual prediction deviation - RPD (ranging between 4.2 and 26.8) and low root mean square errors. These results confirm the hypothesis that FT-Raman is a useful technique for the quality control and chemical properties’ evaluation of Lavandula spp honey. Its application may allow improving the efficiency, speed and cost of the current laboratory analysis. Acknowledgements: CEF is a research unit funded by Fundação para a Ciência e a Tecnologia I.P. (FCT), Portugal (UID/AGR/00239/2013). Centre of Molecular and Environmental Biology is a research unit funded by FCT, UID/BIA/04050/2013 (POCI-01–0145-FEDER-007569) and by the ERDF through the COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI). info:eu-repo/semantics/publishedVersion

The aim of this work is to develop a tool to predict some pulp properties e.g., pulp yield, Kappa number, ISO brightness (ISO 2470:2008), fiber length and fiber width, using the sapwood and heartwood proportion in the raw-material. For this purpose, Acacia melanoxylon trees were collected from four sites in Portugal. Percentage of sapwood and heartwood, area and the stem eccentricity (in N-S and E-W directions) were measured on transversal stem sections of A. melanoxylon R. Br. The relative position of the samples with respect to the total tree height was also considered as an input variable. Different configurations were tested until the maximum correlation coefficient was achieved. A classical mathematical technique (multiple linear regression) and machine learning methods (classification and regression trees, multi-layer perceptron and support vector machines) were tested. Classification and regression trees (CART) was the most accurate model for the prediction of pulp ISO brightness (R = 0.85). The other parameters could be predicted with fair results (R = 0.64–0.75) by CART. Hence, the proportion of heartwood and sapwood is a relevant parameter for pulping and pulp properties, and should be taken as a quality trait when assessing a pulpwood resource. info:eu-repo/semantics/acceptedVersion

Bee pollen contains almost all nutrients required by the human organism as well as diverse health-promoting substances. However, its composition and nutritional value greatly depend on the botanical origin. As such, it is important to develop a rapid and non-expensive methodology that allows studying its characteristics, making labelling more objective and easier. The FTIR-ATR technique was used to predict some nutritional parameters in 126 bee pollen samples. FTIR-ATR spectrum obtained in the region between 4000 and 400 cm -1 with PLS Regression models were used to correlate spectral information with the data obtained using reference methods. In this first approach with pollen samples, good correlation models with appropriate accuracy were obtained for the evaluated parameters with r 2 varying from 74.8 to 97% and residual prediction deviation between 2.0 and 5.8. These results suggest that FTIR-ATR may be a useful technique for assessing bee pollen’s composition. Centro de Estudos Florestais is a research unit funded by FCT (PEst-OE/AGR/UI0239-2014). Centre of Molecular and Environmental Biology is a research unit funded by FCT, UID/ BIA/04050/2013 (POCI-01-0145-FEDER-007569) and by the ERDF through the COMPETE2020 – Programa Operacional Competitividade e Internacionalizac¸a˜o (POCI). info:eu-repo/semantics/publishedVersion

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In this paper, the morphological properties of fiber length (weighted in length) and of fiber width of unbleached Kraft pulp of Acacia melanoxylon were determined using TECHPAP Morfi® equipment (Techpap SAS, Grenoble, France), and were used in the calibration development of Near Infrared (NIR) partial least squares regression (PLS-R) models based on the spectral data obtained for the wood. It is the first time that fiber length and width of pulp were predicted with NIR spectral data of the initial woodmeal, with high accuracy and precision, and with ratios of performance to deviation (RPD) fulfilling the requirements for screening in breeding programs. The selected models for fiber length and fiber width used the second derivative and first derivative + multiplicative scatter correction (2ndDer and 1stDer + MSC) pre-processed spectra, respectively, in the wavenumber ranges from 7506 to 5440 cm−1. The statistical parameters of cross-validation (RMSECV (root mean square error of cross-validation) of 0.009 mm and 0.39 μm) and validation (RMSEP (root mean square error of prediction) of 0.007 mm and 0.36 μm) with RPDTS (ratios of performance to deviation of test set) values of 3.9 and 3.3, respectively, confirmed that the models are robust and well qualified for prediction. This modeling approach shows a high potential to be used for tree breeding and improvement programs, providing a rapid screening for desired fiber morphological properties of pulp prediction. info:eu-repo/semantics/publishedVersion

Aim of the study: The ability of NIR spectroscopy for predicting the ISO brightness was studied on unbleached Kraft pulps of Acacia melanoxylon R. Br.Area of study: Sites covering littoral north, mid interior north and centre interior of Portugal.Materials and methods: The samples were Kraft pulped in standard identical conditions targeted to a kappa number of 15. A Near Infrared (NIR) partial least squares regression (PLSR) model was developed for the ISO brightness prediction using 75 pulp samples with a variation range of 18.9 to 47.9 %.Main results: Very good correlations between NIR spectra and ISO brightness were obtained. Ten methods were used for PLS analysis (cross validation with 48 samples), and a test set validation was made with 27 samples. The 1stDer pre-processed spectra coupling two wavenumber ranges from 9404 to 7498 cm-1 and 4605 to 4243 cm-1 allowed the best model with a root mean square error of ISO brightness prediction of 0.5 % (RMSEP), a r2 of 99.5 % with a RPD of 14.7.Research highlights: According to AACC Method 39-00, the present model is sufficiently accurate to be used for process control (RPD ≥ 8).Key words: Acacia melanoxylon; unbleached Kraft pulps; ISO Brightness; NIR; RPD.

The pulping properties of cypress species are not known and the present paper aims to filling this gap. Namely, Cupressus lusitanica Mill., C. sempervirens L. and C. arizonica Greene have been submitted to kraft pulping and the pulp properties are compared with those of Pinus pinaster Aiton. and P. sylvestris Watereri as references. Schopper Riegler degree, density, Bekk’s smoothness, tensile index, tear index, burst index, stretch, dry zero-span strength, wet zero-span strength, brightness, opacity and light scattering coefficient have been tested. The pulp yields and delignification degrees of cypress woods were lower than those of the pine references. Fibre length, width and coarseness were statistically different between pines and cypress species and C. sempervirens pulps have corresponding data close to those of pine species. Cypress pulps can be refined much faster than pine pulps. The papers sheets of cypress fibres have, in general, lower mechanical performance than those of pine fibres. Papers from C. arizonica and C. lusitanica are similar and C. sempervirens has intermediate properties being between the other cypress and pine species. However, cypress fibres are relatively short, flexible and collapsible and can be refined with low energy demand, and thus could be incorporated into papers resulting in products with better light scattering and smoothness.

Wood density and pulp yield are key parameters in the evaluation of tree productivity and quality for pulping and their relationships are of high practical importance. The influence of wood density on pulp yield and other pulp quality parameters was investigated using Acacia melanoxylon and its natural variability as a case study. Twenty trees were harvested (five trees in each of four sites in Portugal), and wood discs taken at different height levels, from the base to the top of the tree, providing 100 wood samples, covering the natural variability of wood density ranging from 449 kg m−3 to 649 kg m−3. Under the same experimental conditions of kraft pulping, screened pulp yield ranged 47.0–58.2 %, Kappa number 10.9–18.4, ISO brightness 14.9–45.6, fibre length 0.660–0.940 mm and fibre width 16.2–22.9 μm. The pulp yield and Kappa number were not correlated with wood density. Higher pulp yields were associated with lower Kappa numbers and alkali consumption, suggesting the important role of chemical composition of wood on kraft cooking. The results confirm the high pulping potential of Acacia melanoxylon trees grown in Portugal and suggest the possibility of tree selection using both wood density and pulp yield.

Two models were developed to evaluate total volume under and over-bark of Blackwood (Acacia melanoxylon R. Br.) stand trees. By variance analysis regarding volume with and without bark it was confirmed that trees age is responsible for 48 to 50% of its volumetric behaviour. Considered the averages of those variables and regarding the three homogeneous groups of the studied sites, a single model type was used (v=β1dβ2hβ3) for estimating volumes. The critical errors are between 72 and 195 dm3 under-bark, and 82 and 212dm3 over-bark. The model that uses sites as dummy variables to the estimation of stand tree volumes is the same, and this method performs maximum expected errors with values of 155 dm3 (under-bark) and 169dm3 (over-bark), to mean maximum volumes of 1362 and 1459 dm3 respectively.The use of dummy variables is a more expedite and rapid modelling method, and its maximum expected errors perform lower values.Keywords: Blackwood; tree volume; modelling; ANOVA; dummy variables. ResumoDois métodos para estimar o volume em pé de árvores de Acacia melanoxylon em Portugal. Foram construídos dois modelos para estimar o volume sobre e sob casca de árvores em pé da acácia austrália (Acacia melanoxylon R. Br.). Por análise de variância do volume com e sem casca, foi confirmado que a idade das árvores é responsável por 48 a 50% do seu comportamento volumétrico. Consideradas as médias dessas variáveis e tendo em conta os três grupos homogêneos das “estações” estudadas, foi usado um único modelo tipo (v = β1dβ2hβ3) para estimar volumes. Os erros críticos situam-se entre 72 e 195 dm3 sobre casca, e 82 e 212 dm3 sob casca. O modelo que usa as “estações” como variáveis dummy para estimar volumes de árvores em pé é o mesmo e gera erros máximos esperados com valores de 155 dm3 (sob casca) e de 169 dm3 (sobre casca), para volumes máximos médios de 1362 e 1459 dm3, respectivamente. A utilização de variáveis dummy é um método de modelação rápido e mais expedito, e os seus valores de erros máximos esperados são inferiores.Palavras-chave: Austrália; volume de árvore; modelação; ANOVA; variáveis dummy.

• Background Genetic selection for one trait can have an impact on other important traits for final use; thus, it is important to assess the correlation between traits.