Multiple-trait selection of soybean for biodiesel production in Brazil

Woyann, Leomar Guilherme; Meira, Daniela; Zdziarski, Andrei Daniel; Matei, Gilvani; Milioli, Anderson Simionato; Rosa, Ana Claudia; Madella, Laura Alexandra

doi:10.1016/j.indcrop.2019.111721

Cited by 43 publications

(19 citation statements)

References 49 publications

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“…Oliveira et al (2019) selected five sorghum hybrids with higher potential for energy cogeneration using the FAI-BLUP index. Woyann et al (2019) used the FAI-BLUP index in recombinant soybean inbreed lines to identify those that best related to the ideotype for the biodiesel production.…”

Section: Discussionmentioning

confidence: 99%

Selection of Jatropha genotypes for bioenergy purpose: an approach with multitrait, multiharvest and effective population size

et al. 2020

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Jatropha curcas L. is a perennial plant with great potential for biodiesel production. Thus, the aim of this study was to select J. curcas genotypes for bioenergy purpose considering multitrait, multiharvest and effective population size. To this end, a data set with 70 J. curcas families, obtained through controlled crosses, evaluated in a randomized block design, with six replications, three plants per plot, spaced at 4 × 2 m was used. The following traits were evaluated: plant height in the 2014 and 2015 crop seasons; canopy projection in the row (2015 crop season); canopy projection between rows (2015 crop season); and grain yield (2015, 2016, and 2017 harvests). The mixed model methodology was used to estimate the variance components and to predict the genetic values. Superior genotypes were selected through Multitrait index based on factor analysis and genotype-ideotype distance (FAI-BLUP index), considering the effective population size. According to this index, 98% of all additive genetic variability were summarized in three factors. By adopting the selection intensity that allows maintaining the effective population size equal to 30 (i.e., selection of 214 individuals), the predicted gains were 15.56, 21.75, 4.16, and 5.37% for the traits grain yield in the 2015 and 2016 harvests, canopy projection in the row, and canopy projection between rows in the 2015 crop season, respectively. Thus, the results suggest that the FAI-BLUP index can be successfully used in J. curcas breeding.

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Section: Discussionmentioning

confidence: 99%

Selection of Jatropha genotypes for bioenergy purpose: an approach with multitrait, multiharvest and effective population size

et al. 2020

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“…Soybean oil is one of the most used vegetable oils in the biofuel and polymer fields. It accounts for 20 % of the total mass of soybean and contains a high quantity of unsaturated fatty acids: oleic acid (18–20 %), linoleic acid (55 %) and α‐linolenic acid (8–10 %) [89] . Only the most recent finds regarding the use of soybean oil will be discussed here.…”

Section: Soybeanmentioning

confidence: 99%

“…In 2018 alone, 5.4 billion litres of biodiesel were produced in Brazil, of which 70 % was made using soybean oil. [89] Biodiesel is often used as a petrol-diesel substitute and is a mixture of mono-alkyl esters, synthesised by a transesterification reaction between vegetable oils (triacylglycerides) and methanol or ethanol. [90] Normally, the transesterification process occurs in the presence of a strong alkaline catalyst, such as sodium or potassium hydroxide.…”

Section: Soybean Oil As a Source Of Chemicals And Materialsmentioning

confidence: 99%

Opportunities for the Use of Brazilian Biomass to Produce Renewable Chemicals and Materials

et al. 2020

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This Review highlights the principal crops of Brazil and how their harvest waste can be used in the chemicals and materials industries. The Review covers various plants; with grains, fruits, trees and nuts all being discussed. Native and adopted plants are included and studies on using these plants as a source of chemicals and materials for industrial applications, polymer synthesis, medicinal use and in chemical research are discussed. The main aim of the Review is to highlight the principal Brazilian agricultural resources; such as sugarcane, oranges and soybean, as well as secondary resources, such as andiroba brazil nut, buriti and others, which should be explored further for scientific and technological applications. Furthermore, vegetable oils, carbohydrates (starch, cellulose, hemicellulose, lignocellulose and pectin), flavones and essential oils are described as well as their potential applications.

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“…As a strategy, the construction of a selection index could be applied to overcome this problem. The construction of selection index for multiple traits with negative genetic correlation has been demonstrated in common bean (Phaseolus vulgaris) (Lima et al 2015), soybean (Woyann et al 2019), rice , as well as in the tree breeding scenario as exemplified in scots pine (Pinus sylvestris) (Hong et al 2014) and Khasi pine (Pinus kesiya) (Missanjo and Matsumura 2017). Therefore, utilization of the selection index could simultaneously improve agronomic traits and nutrient content in yardlong bean.…”

Section: Cluster Analysismentioning

confidence: 99%

Multivariate analysis unravels genetic diversity and relationship between agronomic traits, protein, and dietary fiber in yardlong bean (Vigna unguiculata subsp. sesquipedalis Verdc.)

et al. 2020

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Abstract. Widyawan MB, Hasanah A, Taryono, Alam T, Sayekti RS, Pramana AAC, Wulandari RA. 2020. Multivariate analysis unravels genetic diversity and relationship between agronomic traits, protein, and dietary fiber in yardlong bean (Vigna unguiculata subsp. sesquipedalis Verdc.). Biodiversitas 21: 5662-5671. Yardlong bean (Vigna unguiculata subsp. sesquipedalis Verdc.) is a vegetable legume that possesses the highest amount of protein and total dietary fiber (TDF) content among other vegetables. However, protein and TDF content diversity are found among yardlong bean genotypes. Genetic improvement to produce cultivars with high yield and improved nutritional content is required. This study aimed to analyze genetic diversity and identify the relationship between important agronomic traits from 21 yardlong bean genotypes assessed by multivariate statistical analysis. The experiment was arranged in alpha design with three replicates, each consist of six blocks. Six pod-related important agronomic traits, protein, and TDF content were observed in this study. Total pod weight, pod weight, and pod length were found to be negatively correlated with protein and TDF content based on correlation and principal component analysis (PCA). Although negatively correlated, several variables possess a large and positive direct effect on protein and TDF content, such as the number of pod, pod weight, and days to flower. D2 analysis and Tocher’s method classify genotypes used in this study into five clusters with diverse traits value. Information from this study laid a foundation for the improvement of important agronomic traits as well as nutritional content in yardlong bean.

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Multiple-trait selection of soybean for biodiesel production in Brazil

Cited by 43 publications

References 49 publications

Selection of Jatropha genotypes for bioenergy purpose: an approach with multitrait, multiharvest and effective population size

Selection of Jatropha genotypes for bioenergy purpose: an approach with multitrait, multiharvest and effective population size

Opportunities for the Use of Brazilian Biomass to Produce Renewable Chemicals and Materials

Multivariate analysis unravels genetic diversity and relationship between agronomic traits, protein, and dietary fiber in yardlong bean (Vigna unguiculata subsp. sesquipedalis Verdc.)

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