Many countries have developed strategies and instruments in order to stimulate the availability of domestic biomass feedstocks and the use of these resources for bioenergy purposes. However, a good matching between domestic bioenergy policies and markets is still challenging. CT4 participants discussed whether these examples could be replicated in other Member States.
The discussions showed that promising market segments for biomass heating are mainly driven by local biomass suppliers and need adapted financial instruments to expand given that investors primarily face CAPEX barriers, rather than OPEX barriers. For biogas, a vivid discussion shows local solutions are manifold depending on a variety of policy and physical parameters.
This appears to be a good topic for a next workshop. Published online Dec Author information Article notes Copyright and License information Disclaimer. Corresponding author. Received Oct 19; Accepted Dec The solid lines and dashed lines overlaid upon each histogram represent normal distributions and were used to embody the discrepancy between each histogram and normality. R 2 V represents the square of the correlation coefficients of the external validation subsets.
Table S1. Feedstock quality grades of 59 Jerusalem artichoke accessions. Table S2.
A summary of NIR application in different biomass feedstocks for chemical components. Table S3. A summary of NIR application in different biomass feedstocks for biomass digestibility. Additional file 2. Raw NIRS data. Additional file 3. The procedure code of grey relational grade analysis. Abstract Background High-throughput evaluation of lignocellulosic biomass feedstock quality is the key to the successful commercialization of bioethanol production.
Results The distinct geographical distribution of JA accessions generated varied chemical composition as well as related biomass digestibility after soluble sugars extraction and mild alkali pretreatment. Electronic supplementary material The online version of this article Keywords: Jerusalem artichoke, Chemical composition, Chemical pretreatment, Biomass digestibility, Near-infrared spectroscopy, Grey relational grade analysis. Background In recent years, fossil fuels consumption and greenhouse gas emissions have increased dramatically in step with rapid global industrialization, especially in China.
Open in a separate window. Optimization of spectral variable selection and samples sets partitioning Judicious selection of spectral information is a crucial step for successful NIRS modeling, which not only permits the collection of strong informative variables but also removes interference due to uninformative variables [ 23 , 26 ]. Comprehensive assessment of feedstock quality score Based on chemical composition and biomass digestibility total carbohydrates released after pretreatment and subsequent enzymatic hydrolysis , the feedstock quality of tested JA accessions was comprehensively evaluated using the GRA model.
Discussion Evaluation and selection of ideal feedstock among bioenergy crops are necessary to enhance lignocellulosic biofuel production [ 37 , 38 ]. Conclusions In this study, 59 JA clone stems originating from six regions of China exhibited diverse chemical compositions, biomass digestibility, and variable NIRS results, which were applicable for statistical analysis and NIRS modeling.
Methods Sample collection and preparation A total of 59 JA natural clones were collected nationwide from to Biomass components and digestibility analysis The main topic of this research was to build upon the laboratory-scale alkali-based conversion process developed by Li et al. Grey relational grade analysis In this study, JA stem feedstock quality specifications could be divided into two categories: chemical components soluble sugars, cellulose, hemicellulose, lignin, and ash and biomass digestibility hexoses, pentoses, and total carbohydrates.
Additional files Additional file 1: Fig. Competing interests The authors declare that they have no competing interests. Availability of data and materials The datasets supporting the conclusions of this article are included within the article and its additional files. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. Contributor Information Meng Li, Email: nc. References 1. Field crop residue estimate and availability for biofuel production in China.
Renew Sustain Energy Rev. BP statistical review of world energy. Demirbas A, Demirbas A. Modernization of biomass energy conversion facilities. Energy Sources Part B. Annual accounting of net greenhouse gas balance response to biochar addition in a coastal saline bioenergy cropping system in China.
Soil Tillage Res. Annual net greenhouse gas balance in a halophyte Helianthus tuberosus bioenergy cropping system under various soil practices in Southeast China. GCB Bioenergy.
Kim S, Kim CH. Evaluation of whole Jerusalem artichoke Helianthus tuberosus L. Renew Energy. Growth and yield performance of Jerusalem artichoke clones in a semiarid region of china. Agron J. Chemical composition and potential ethanol yield of Jerusalem artichoke in a semi-arid region of China. Ital J Agron. Genetic variation and yield performance of Jerusalem artichoke germplasm collected in China. Agric Sci China. Analysis of sugars by liquid chromatography-mass spectrometry in Jerusalem artichoke tubers for bioethanol production optimization.
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Biomass Bioenergy. Alkali-based pretreatments distinctively extract lignin and pectin for enhancing biomass saccharification by altering cellulose features in sugar-rich Jerusalem artichoke stem.
Bioresour Technol. Cellulosic bioethanol production from Jerusalem artichoke Helianthus tuberosus L. Potential of Jerusalem artichoke Helianthus tuberosus L. Ind Crop Prod. Impact of feedstock quality and variation on biochemical and thermochemical conversion. Biomass recalcitrance: engineering plants and enzymes for biofuels production.
Deng J. Control problems of grey systems. Syst Control Lett. Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy.
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Qualitative and quantitative analysis of lignocellulosic biomass using infrared techniques: a mini-review. Appl Energy. Evaluation of infrared techniques for the assessment of biomass and biofuel quality parameters and conversion technology processes: a review.
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Random frog: an efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification. Genetic modification of plant cell walls to enhance biomass yield and biofuel production in bioenergy crops. Biotechnol Adv. A laboratory-scale pretreatment and hydrolysis assay for determination of reactivity in cellulosic biomass feedstocks. NIR and Py-mbms coupled with multivariate data analysis as a high-throughput biomass characterization technique: a review.
Front Plant Sci. Use of NIRS to predict composition and bioethanol yield from cell wall structural components of sweet sorghum biomass. Microchem J.
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