Selection of putative relic cacao (Theobroma cacao L.) genotypes in farmers’ fields in Trinidad and Tobago

2019 ◽  
Vol 96 (1) ◽  
pp. 1-14
Author(s):  
Kamaldeo Maharaj ◽  
◽  
Frances L. Bekele ◽  
Davinan Ramnath ◽  
Reishma Sankar Sankar ◽  
...  

Trinidad and Tobago is a repository of putative relic cacao genotypes, given its long history of cultivating cacao from the 1700s onwards. As part of a project conducted between 2009 and 2011, funded by the World Bank Development Market Place, World Bank Project TF 093747 (DM 2008), 106 putative, ancient cacao varieties were collected from farms throughout Trinidad and Tobago to be conserved and utilized to preserve traditional quality (flavour) attributes. The objective of this article is to provide information on agronomic and phenotypic traits of 94 of these ‘relic’ accessions collected in farmers’ fields (FA). These are presumed to be relic Criollos or Trinitarios (selected pre-and post-1930s), and were selected over six cocoa production zones in Trinidad and Tobago. In addition, data for 31 regional Trinitario cacao accessions, which are conserved at the International Cocoa Genebank Trinidad (ICGT) were assessed. Morphological assessment of the selections was based on 22 phenotypic traits including characteristics of economic interest, viz. bean number (BN), individual dried bean weight (DBW), total wet bean weight (TWBW) and pod index (PI), which ranged from 26.4 to 58.0 (CV 16.3%); 0.6g to 2.12g (CV 22.6%); 42.5 to 228g (CV 24.2%) and 10 to 57 (CV 27.5%), respectively. Significant differences (p < 0.0001) were found among the production zones for BN and DBW only. Four zones had selections with significantly higher BN and all six had selections with superior TWBW relative to the ICGT clones studied. No association between cotyledon colour and leaf petiole hairiness was found, suggesting independent inheritance of these traits used for preliminary identification of ‘Criollo-like’ genotypes in the field. FAs from Tobago generally had selections with paler cotyledons, implying relatively more pronounced Criollo ancestry. Principal Component (PC) scores 1 and 2 accounted for 74.7% of the phenotypic variation expressed by the accessions studied in terms of five traits, based on Principal Component Analysis (PCA). PI and TWBW were major contributors to PC 1, while for PC 2, the major contributors were BN and DBW. The results of PCA and cluster analyses suggest that a phenotypically diverse and unique selection of genotypes was collected from the farmers’ fields, relative to studied ICGT types, several of which displayed ‘Criollo-like’ and Trinitario characteristics (large, plump seeds/beans with pale cotyledons) and favourable yield potential. These can be utilized to enhance the genepool at the ICGT, for breeding to introgress favourable Trinitario genes into national recurrent breeding programmes and for commercial cultivation.

2021 ◽  
Vol 13 (2) ◽  
pp. 168781402199295
Author(s):  
Ziqiang Zhang ◽  
Qi Yang ◽  
Xingkun Liu ◽  
Chuanzhong Zhang ◽  
Jinnong Liao

One degree-of-freedom (DOF) jumping leg has the advantages of simple control and high stiffness, and it has been widely used in bioinspired jumping robots. Compared with four-bar jumping leg, six-bar jumping leg mechanism can make the robot achieve more abundant motion rules. However, the differences among different configurations have not been analyzed, and the choice of configurations lacks basis. In this study, five Watt-type six-bar jumping leg mechanisms were selected as research objects according to the different selection of equivalent tibia, femur and trunk link, and a method for determining the dimension of the jumping leg was proposed based on the movement law of jumping leg of locust in take-off phase. On this basis, kinematics indices (sensitivity of take-off direction angle and trunk attitude angle), dynamics indices (velocity loss, acceleration fluctuation, and mean and variance of total inertial moment) and structure index (distribution of center of mass) were established, and the differences of different configurations were compared and analyzed in detail. Finally, according to the principal component analysis method, the optimal selection method for different configurations was proposed. This study provides a reference for the design of one DOF bioinspired mechanism.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Debayan Mondal ◽  
Prudveesh Kantamraju ◽  
Susmita Jha ◽  
Gadge Sushant Sundarrao ◽  
Arpan Bhowmik ◽  
...  

AbstractIndigenous folk rice cultivars often possess remarkable but unrevealed potential in terms of nutritional attributes and biotic stress tolerance. The unique cooking qualities and blissful aroma of many of these landraces make it an attractive low-cost alternative to high priced Basmati rice. Sub-Himalayan Terai region is bestowed with great agrobiodiversity in traditional heirloom rice cultivars. In the present study, ninety-nine folk rice cultivars from these regions were collected, purified and characterized for morphological and yield traits. Based on traditional importance and presence of aroma, thirty-five genotypes were selected and analyzed for genetic diversity using micro-satellite marker system. The genotypes were found to be genetically distinct and of high nutritive value. The resistant starch content, amylose content, glycemic index and antioxidant potential of these genotypes represented wide variability and ‘Kataribhog’, ‘Sadanunia’, ‘Chakhao’ etc. were identified as promising genotypes in terms of different nutritional attributes. These cultivars were screened further for resistance against blast disease in field trials and cultivars like ‘Sadanunia’, ‘T4M-3-5’, ‘Chakhao Sampark’ were found to be highly resistant to the blast disease whereas ‘Kalonunia’, ‘Gobindabhog’, ‘Konkanijoha’ were found to be highly susceptible. Principal Component analysis divided the genotypes in distinct groups for nutritional potential and blast tolerance. The resistant and susceptible genotypes were screened for the presence of the blast resistant pi genes and association analysis was performed with disease tolerance. Finally, a logistic model based on phenotypic traits for prediction of the blast susceptibility of the genotypes is proposed with more than 80% accuracy.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nicole Pretini ◽  
Leonardo S. Vanzetti ◽  
Ignacio I. Terrile ◽  
Guillermo Donaire ◽  
Fernanda G. González

Abstract Background In breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with higher grains per spike (GN) and occasionally increased grain weight (GW) (main numerical components of the yield). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two doubled haploid (DH) populations (Baguette Premium 11 × BioINTA 2002 and Baguette 19 × BioINTA 2002). Results In total 305 QTL were identified for 14 traits, out of which 12 QTL were identified in more than three environments and explained more than 10% of the phenotypic variation in at least one environment. Eight hotspot regions were detected on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B in which at least two major and stable QTL sheared confidence intervals. QTL on two of these regions (R5A.1 and R5A.2) have previously been described, but the other six regions are novel. Conclusions Based on the pleiotropic analysis within a robust physiological model we conclude that two hotspot genomic regions (R5A.1 and R5A.2) together with the QGW.perg-6B are of high relevance to be used in marker assisted selection in order to improve the spike yield potential. All the QTL identified for the spike related traits are the first step to search for their candidate genes, which will allow their better manipulation in the future.


Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 599
Author(s):  
Miguel A. Gutierrez-Reinoso ◽  
Pedro M. Aponte ◽  
Manuel Garcia-Herreros

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.


Author(s):  
Davide Arella ◽  
Maddalena Dilucca ◽  
Andrea Giansanti

AbstractIn each genome, synonymous codons are used with different frequencies; this general phenomenon is known as codon usage bias. It has been previously recognised that codon usage bias could affect the cellular fitness and might be associated with the ecology of microbial organisms. In this exploratory study, we investigated the relationship between codon usage bias, lifestyles (thermophiles vs. mesophiles; pathogenic vs. non-pathogenic; halophilic vs. non-halophilic; aerobic vs. anaerobic and facultative) and habitats (aquatic, terrestrial, host-associated, specialised, multiple) of 615 microbial organisms (544 bacteria and 71 archaea). Principal component analysis revealed that species with given phenotypic traits and living in similar environmental conditions have similar codon preferences, as represented by the relative synonymous codon usage (RSCU) index, and similar spectra of tRNA availability, as gauged by the tRNA gene copy number (tGCN). Moreover, by measuring the average tRNA adaptation index (tAI) for each genome, an index that can be associated with translational efficiency, we observed that organisms able to live in multiple habitats, including facultative organisms, mesophiles and pathogenic bacteria, are characterised by a reduced translational efficiency, consistently with their need to adapt to different environments. Our results show that synonymous codon choices might be under strong translational selection, which modulates the choice of the codons to differently match tRNA availability, depending on the organism’s lifestyle needs. To our knowledge, this is the first large-scale study that examines the role of codon bias and translational efficiency in the adaptation of microbial organisms to the environment in which they live.


2019 ◽  
Vol 21 (1) ◽  
pp. 165 ◽  
Author(s):  
Dennis N. Lozada ◽  
Jayfred V. Godoy ◽  
Brian P. Ward ◽  
Arron H. Carter

Secondary traits from high-throughput phenotyping could be used to select for complex target traits to accelerate plant breeding and increase genetic gains. This study aimed to evaluate the potential of using spectral reflectance indices (SRI) for indirect selection of winter-wheat lines with high yield potential and to assess the effects of including secondary traits on the prediction accuracy for yield. A total of five SRIs were measured in a diversity panel, and F5 and doubled haploid wheat breeding populations planted between 2015 and 2018 in Lind and Pullman, WA. The winter-wheat panels were genotyped with 11,089 genotyping-by-sequencing derived markers. Spectral traits showed moderate to high phenotypic and genetic correlations, indicating their potential for indirect selection of lines with high yield potential. Inclusion of correlated spectral traits in genomic prediction models resulted in significant (p < 0.001) improvement in prediction accuracy for yield. Relatedness between training and test populations and heritability were among the principal factors affecting accuracy. Our results demonstrate the potential of using spectral indices as proxy measurements for selecting lines with increased yield potential and for improving prediction accuracy to increase genetic gains for complex traits in US Pacific Northwest winter wheat.


2010 ◽  
Vol 46 (4) ◽  
pp. 679-685 ◽  
Author(s):  
Oscar Flórez-Acosta ◽  
Gloria Tobón-Zapata ◽  
Jaime Valencia-Velasquez

With the purpose of enabling the analysis by digital methods of particles of multisource pharmaceutical raw materials, this study analyzed different crystal habits of ampicillin particles, by grouping the external shapes obtained from 3 different solvents (acetonitrile, ethanol, and methanol), thereby reducing the number of descriptors necessary to adequately represent each shape. For this purpose, a selection of morphological descriptors was used including: circularity, roughness, roundness, compactness, aspect ratio, effective diameter, solidity, convexity, fractal dimension, and 10 Complex Fourier descriptors. These measures cover highly diverse morphological properties and define the crystal habit of a particle. Principal Component Analysis (PCA) and the Cluster Analysis (CA) were the grouping techniques used, which demonstrated the possibility of using between 2 and 4 descriptors instead of the 18 proposed initially.


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