Forest biotechnology advances to support global bioeconomy

The world is shifting to an innovation economy and forest biotechnology can play a major role in the bio-economy by providing farmers, producers, and consumers with tools that can better advance this transition. First-generation or conventional biofuels are primarily produced from food crops and are therefore limited in their ability to meet challenges for petroleum-product substitution and climate change mitigation, and to overcome the food-versus-fuel dilemma. In the longer term, forest lignocellulosic biomass will provide a unique renewable resource for large-scale production of bioenergy, biofuels and bio-products. These second-generation or advanced biofuels and bio-products have also the potential to avoid many of the issues facing the first-generation biofuels, particularly the competition concerning land and water used for food production. To expand the range of natural biological resources the rapidly evolving tools of biotechnology can ameliorate the conversion process, lower the conversion costs and also enhance target yield of forest biomass feedstock and the product of interest. Therefore, linking forest biotechnology with industrial biotechnology presents a promising approach to convert woody lignocellulosic biomass into biofuels and bio-products. Major advances and applications of forest biotechnology that are being achieved to competitively position forest biomass feedstocks with corn and other food crops are outlined. Finally, recommendations for future work are discussed

Contamination of the Environmental Matrices in Agricultural Areas Produced by Industrial Discharges: The Case Study of the Land of the City of Statte (Taranto, Southern Italy)

The diffusion of pollutants in the atmosphere, agricultural soil, irrigation water, crops and food chain can produce potential environmental health risk. The aims of this study are the environmental risk assessment for the aquifers and the estimation of pollutants concentration in the forage for evaluating the risk for human health. The risk analysis was applied in the rural territory of Statte (Taranto, Italy) using an innovative methodology based on the integration of models for estimation of pollutant leaching in the groundwater and for the evaluation of bio-transfer of pollutant in the plant. The model results are in accordance with the experimental values and therefore the proposed methodology allows the evaluation and management of environmental health risks in agricultural areas interested by pollution phenomena generated by industrial plants

Sanitary risk analysis for farm workers exposed to environmental pollutants

In Italy, a large number of agricultural areas are contaminated by organic and inorganic polluting substances. In such areas, the agricultural operators come into contact with the environmental contaminants through inhalation and dermic contact with dusts and vapour, and this exposure can potentially alter the biological equilibrium with consequent poisonings and/or work-related illness. The aim of this paper is to apply a methodological procedure for the numerical evaluation of the health risk for agricultural employees operating in open fields or inside greenhouses located in areas contaminated with organic pollutants. This procedure is in response to the lack of calculation models concerning these types of environment and agricultural activities. As a case study, this methodology has been applied to an agricultural area of southern Italy characterised by the presence of pollutants. The results underline that in this area there is a smaller concentration of pollutants in open field cultivations than inside greenhouses owing to a phenomenon of dispersion into the atmosphere. This numeric analysis will later be verified by measurements carried out in situ in order to evaluate the real situation on the ground

A Three-Step Neural Network Artificial Intelligence Modeling Approach for Time, Productivity and Costs Prediction: A Case Study in Italian Forestry

The improvement of harvesting methodologies plays an important role in the optimization of wood production in a context of sustainable forest management. Different harvesting methods can be applied according to forest site-specific condition and the appropriate mechanization level depends on a number of factors. Therefore, efficiency and functionality of wood harvesting operations depend on several factors. The aim of this study is to analyze how the different harvesting processes affect operational costs and labor productivity in typical small-scale Italian harvesting companies. A multiple linear regression model (MLR) and artificial neural network (ANN) have been carried out to predict gross time, productivity and costs estimation in a series of qualitative and quantitative variables. The results have created a correct statistical model able to accurately estimate the technical parameters (work time and productivity) and economic parameters (costs per unit of product and per hectare) useful to the forestry entrepreneur to predict the results of the work in advance, considering only the values detectable of some characteristic elements of the worksite

Phenotypic plasticity, QTL mapping and genomic characterization of bud set in black poplar

<p>Abstract</p> <p>Background</p> <p>The genetic control of important adaptive traits, such as bud set, is still poorly understood in most forest trees species. Poplar is an ideal model tree to study bud set because of its indeterminate shoot growth. Thus, a full-sib family derived from an intraspecific cross of <it>P. nigra </it>with 162 clonally replicated progeny was used to assess the phenotypic plasticity and genetic variation of bud set in two sites of contrasting environmental conditions.</p> <p>Results</p> <p>Six crucial phenological stages of bud set were scored. Night length appeared to be the most important signal triggering the onset of growth cessation. Nevertheless, the effect of other environmental factors, such as temperature, increased during the process. Moreover, a considerable role of genotype × environment (G × E) interaction was found in all phenological stages with the lowest temperature appearing to influence the sensitivity of the most plastic genotypes.</p> <p>Descriptors of growth cessation and bud onset explained the largest part of phenotypic variation of the entire process. Quantitative trait loci (QTL) for these traits were detected. For the four selected traits (the onset of growth cessation (date2.5), the transition from shoot to bud (date1.5), the duration of bud formation (subproc1) and bud maturation (subproc2)) eight and sixteen QTL were mapped on the maternal and paternal map, respectively. The identified QTL, each one characterized by small or modest effect, highlighted the complex nature of traits involved in bud set process. Comparison between map location of QTL and <it>P. trichocarpa </it>genome sequence allowed the identification of 13 gene models, 67 bud set-related expressional and six functional candidate genes (CGs). These CGs are functionally related to relevant biological processes, environmental sensing, signaling, and cell growth and development. Some strong QTL had no obvious CGs, and hold great promise to identify unknown genes that affect bud set.</p> <p>Conclusions</p> <p>This study provides a better understanding of the physiological and genetic dissection of bud set in poplar. The putative QTL identified will be tested for associations in <it>P. nigra </it>natural populations. The identified QTL and CGs will also serve as useful targets for poplar breeding.</p