Classification of Amazonian fast-growing tree species and wood chemical determination by FTIR and multivariate analysis (PLS-DA, PLS)

Fast-growing trees like Capirona, Bolaina, and Pashaco have the potential to reduce forest degradation because of their ecological features, the economic importance in the Amazon Forest, and an industry based on wood-polymer composites. Therefore, a practical method to discriminate specie (to avoid illegal logging) and determine chemical composition (tree breeding programs) is needed. This study aimed to validate a model for the classification of wood species and a universal model for the rapid determination of cellulose, hemicellulose, and lignin using FTIR spectroscopy coupled with chemometrics. Our results showed that PLS-DA models for the classification of wood species (0.84 ≤ R² ≤ 0.91, 0.12 ≤ RMSEP ≤ 0.20, accuracy, specificity, and sensibility between 95.2 and 100%) were satisfied with the full spectra and the differentiation among these species based on IR peaks related to cellulose, lignin, and hemicellulose. Besides, the full spectra helped build a three-species universal PLS model to quantify the principal wood chemical components. Lignin (RPD = 2.27, [Formula: see text] = 0.84) and hemicellulose (RPD = 2.46, [Formula: see text] = 0.83) models showed a good prediction, while cellulose model (RPD = 3.43, [Formula: see text] = 0.91) classified as efficient. This study showed that FTIR-ATR, together with chemometrics, is a reliable method to discriminate wood species and to determine the wood chemical composition in juvenile trees of Pashaco, Capirona, and Bolaina.

The micronutrient content in underutilized crops: the Lupinus mutabilis sweet case

Adequate intake of micronutrients is necessary to reduce widespread health issues linked to low intake of iron (Fe), zinc (Zn), boron (B), copper (Cu), and manganese (Mn). Because more than two billion people suffer from micronutrient deficiency globally, to address this problem, highly-nutritious ancestral Peruvian crops like tarwi can be an important component of food security. Thus, our work explores the tarwi micronutrient variability to select biofortified genotypes without affecting seed size and weight. Tarwi is a biofortified food because of its seeds' Fe, Zn, and B content. Furthermore, Boron showed a positive correlation between seed size and weight. At the same time, copper showed a negative correlation. Finally, six accessions (P14, P16, P21, T05, T08, and T25) that are biofortified for Fe, Zn, and B with excellent seed size and weight and with adequate levels of Cu and Mn; adding value to Peruvian biodiversity at a low cost is a starting point for a breeding program to prevent micronutrient disorders.

Determination of hemicellulose, cellulose, holocellulose and lignin content using FTIR in Calycophyllum spruceanum (Benth.) K. Schum. and Guazuma crinita Lam

Capirona (Calycophyllum spruceanum (Benth.) K. Schum.) and Bolaina (Guazuma crinita Lam.) are fast-growing Amazonian trees with increasing demand in timber industry. Therefore, it is necessary to determine the content of cellulose, hemicellulose, holocellulose and lignin in juvenile trees to accelerate forest breeding programs. The aim of this study was to identify chemical differences between apical and basal stem of Capirona and Bolaina to develop models for estimating the chemical composition using Fourier transform infrared (FTIR) spectra. FTIR-ATR spectra were obtained from 150 samples for each species that were 1.8 year-old. The results showed significant differences between the apical and basal stem for each species in terms of cellulose, hemicellulose, holocellulose and lignin content. This variability was useful to build partial least squares (PLS) models from the FTIR spectra and they were evaluated by root mean squared error of predictions (RMSEP) and ratio of performance to deviation (RPD). Lignin content was efficiently predicted in Capirona (RMSEP = 0.48, RPD > 2) and Bolaina (RMSEP = 0.81, RPD > 2). In Capirona, the predictive power of cellulose, hemicellulose and holocellulose models (0.68 < RMSEP < 2.06, 1.60 < RPD < 1.96) were high enough to predict wood chemical composition. In Bolaina, model for cellulose attained an excellent predictive power (RMSEP = 1.82, RPD = 6.14) while models for hemicellulose and holocellulose attained a good predictive power (RPD > 2.0). This study showed that FTIR-ATR together with PLS is a reliable method to determine the wood chemical composition in juvenile trees of Capirona and Bolaina.

Flow-cytometry applications in plant breeding

Population growth, climate change and global warming are the great challenges facing agriculture in the 21st century. Therefore, it is necessary to increase the efficiency of selection of new varieties in plant breeding programs. In this regard, flow cytometry has proven to be a very powerful tool to speed-up selection processes in plant breeding because of its versatility and capacity to evaluate large populations.