RESUMO
Biosurfactants have been profiled as a sustainable replacement for chemical-based surfactants since these bio-based molecules have higher biodegradability. Few research papers have focused on assessing biosurfactant production to elucidate potential bottlenecks. This research aims to assess the techno-economic and environmental performance of surfactin production in a potential scale of 65m3, considering different product yields and involving the European energy crisis of 2021-2022. The conceptual design, simulation, techno-economic, and environmental assessments were done by applying process engineering concepts and software tools such as Aspen Plus v.9.0 and SimaPro v.8.3.3. The results demonstrated the high economic potential of surfactin production since the higher values in the market offset the low fermentation yields, low recovery efficiency, and high capital investment. The sensitivity analysis of the economic assessment elucidated a minimum surfactin selling price between 29 and 31 USD/kg of surfactin, while a minimum processing scale for economic feasibility between 4 and 5 kg/h is needed to reach an equilibrium point. The environmental performance must be improved since the carbon footprint was 43 kg CO2eq/kg of surfactin. The downstream processing and energy demand are the main bottlenecks since these aspects contribute to 63 and 25% of the total emissions. The fermentation process and downstream process are key factors for future optimization and research.
RESUMO
Understanding the impacts of agricultural practices on belowground fungal communities is crucial in order to preserve biological diversity in agricultural soils and enhance their role in agroecosystem functioning. Although fungal communities are widely distributed, relatively few studies have correlated agricultural production practices. We investigated the diversity, composition and ecological functionality of fungal communities in roots of winter wheat (Triticum aestivum) growing in conventional and organic farming systems. Direct and nested polymerase chain reaction (PCR) amplifications spanning the internal transcribed spacer (ITS) region of the rDNA from pooled fine root samples were performed with two different sets of fungal specific primers. Fungal identification was carried out through similarity searches against validated reference sequences (RefSeq). The R package 'picante' and FUNGuild were used to analyse fungal community composition and trophic mode, respectively. Either by direct or cloning sequencing, 130 complete ITS sequences were clustered into 39 operational taxonomic units (OTUs) (25 singletons), belonging to the Ascomycota (24), the Basidiomycota (14) and to the Glomeromycota (1). Fungal communities from conventional farming sites are phylogenetically more related than expected by chance. Constrained ordination analysis identified total N, total S and Pcal that had a significant effect on the OTU's abundance and distribution, and a further correlation with the diversity of the co-occurring vegetation could be hypothesised. The functional predictions based on FUNGuild suggested that conventional farming increased the presence of plant pathogenic fungi compared with organic farming. Based on diversity, OTU distribution, nutrition mode and the significant phylogenetic clustering of fungal communities, this study shows that fungal communities differ across sampling sites, depending on agricultural practices. Although it is not fully clear which factors determine the fungal communities, our findings suggest that organic farming systems have a positive effect on fungal communities in winter wheat crops.
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Information on the genetic control of the quality traits of soft wheat (Triticum aestivum) is essential for breeding. Our objective was to identify QTL associated with end-use quality. We developed 150 F4-derived lines from a cross of Pioneer 26R46 × SS550 and tested them in four environments. We measured flour yield (FY), softness equivalent (SE), test weight (TW), flour protein content (FP), alkaline water retention capacity (AWRC), and solvent retention capacity (SRC) of water (WA), lactic acid (LA), sucrose (SU), sodium carbonate (SO). Parents differed for nine traits, transgressive segregants were noted, and heritability was high (0.67 to 0.90) for all traits. We detected QTL distributed on eight genomic regions. The QTL with the greatest effects were located on chromosome 1A, 1B, and 6B with each affecting at least five of ten quality traits. Pioneer 26R46 is one of the best quality soft wheats. The large-effect QTL on 1A novel and accounted for much of the variation for AWRC (r2 = 0.26), SO (0.26) and SE (0.25), and FY (0.15) and may explain why Pioneer 26R46 has such superior quality. All alleles that increased a trait came from the parent with the highest trait value. This suggests that in any population that marker-assisted selection for these quality traits could be conducted by simply selecting for the alleles at key loci from the parent with the best phenotype without prior mapping.
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Cultivars have to be evaluated under different crop management systems across agro-ecosystems and years using multi-environment trials (MET) before releasing them to the market. Frequently, data collected in METs are arranged according to cultivar (G), management (M), location, (L) and year (Y) combinations in a four-way G x M x L x Y data table that is highly unbalanced for cultivars across locations and time. Therefore, we present the restricted maximum likelihood method (REML) for linear mixed models (LMM) with a factor analytic variance-covariance matrix for assessing cultivar adaptation to crop management systems and environments based on unbalanced datasets. Such a multi-environmental trial system has been in operation in Poland for winter wheat (Triticum aestivum L.) in the form of the Post-registration Variety Testing System (PVTS). This study aimed to illustrate the use of LMM in the analysis of unbalanced four-way G x M x L x Y data. LMM analysis provided adjusted means of grain yield for 51 winter wheat cultivars bred in different regions in Europe, tested across 18 trial locations and seven consecutive cropping seasons in two crop management intensities. The application of the four-way LMM with a factor analytic variance-covariance matrix is a complementary and effective tool for evaluating the unbalanced G x M x L x Y table. Cultivars tested had different adaptive responses to the Polish agro-ecosystems separately for each of the crop management intensities. Wide adaptation in both crop management systems was exhibited by cultivars Mulan and Jenga bred in Germany.
Assuntos
Análise de Dados , 24444 , Modelos Lineares , TriticumRESUMO
Cultivars have to be evaluated under different crop management systems across agro-ecosystems and years using multi-environment trials (MET) before releasing them to the market. Frequently, data collected in METs are arranged according to cultivar (G), management (M), location, (L) and year (Y) combinations in a four-way G x M x L x Y data table that is highly unbalanced for cultivars across locations and time. Therefore, we present the restricted maximum likelihood method (REML) for linear mixed models (LMM) with a factor analytic variance-covariance matrix for assessing cultivar adaptation to crop management systems and environments based on unbalanced datasets. Such a multi-environmental trial system has been in operation in Poland for winter wheat (Triticum aestivum L.) in the form of the Post-registration Variety Testing System (PVTS). This study aimed to illustrate the use of LMM in the analysis of unbalanced four-way G x M x L x Y data. LMM analysis provided adjusted means of grain yield for 51 winter wheat cultivars bred in different regions in Europe, tested across 18 trial locations and seven consecutive cropping seasons in two crop management intensities. The application of the four-way LMM with a factor analytic variance-covariance matrix is a complementary and effective tool for evaluating the unbalanced G x M x L x Y table. Cultivars tested had different adaptive responses to the Polish agro-ecosystems separately for each of the crop management intensities. Wide adaptation in both crop management systems was exhibited by cultivars Mulan and Jenga bred in Germany.(AU)
Assuntos
Análise de Dados , 24444 , Modelos Lineares , TriticumRESUMO
Background The quality of wheat grain depends on several characteristics, among which the composition of high molecular weight glutenin subunits, encoded by Glu-1 loci, are the most important. Application of biotechnological tools to accelerate the attainment of homozygous lines may influence the proportion of segregated genotypes. The objective was to determine, whether the selection pressure generated by the methods based on in vitro cultures, may cause a loss of genotypes with desirable Glu-1 alleles. Results Homozygous lines were derived from six winter wheat crosses by pollination with maize (DH-MP), anther culture (DH-AC) and single seed descent (SSD) technique. Androgenetically-derived plants that originated from the same callus were examined before chromosome doubling using allele-specific and microsatellite markers. It was found that segregation distortion in SSD and DH-MP populations occurred only in one case, whereas in anther-derived lines they were observed in five out of six analyzed combinations. Conclusions Segregation distortion in DH-AC populations was caused by the development of more than one plant of the same genotype from one callus. This distortion was minimized if only one plant per callus was included in the population. Selection of haploid wheat plants before chromosome doubling based on allele-specific markers allows us to choose genotypes that possess desirable Glu-1 alleles and to reduce the number of plants in the next steps of DH production. The SSD technique appeared to be the most advantageous in terms of Mendelian segregation, thus the occurrence of residual heterozygosity can be minimized by continuous selfing beyond the F6 generation.