Genetic variability in partitioning to the yield component of cacao (Theobroma cacao L.)

Biomass partitioning of cacao (Theobroma cacao L.) was studied in seven clones and five hybrids in a replicated experiment in Bahia, Brazil. Over an eighteen month period, a seven- fold difference in dry bean yield was demonstrated between genotypes, ranging from the equivalent of 200 to 1389 kg.ha-1. During the same interval, the increase in trunk cross-sectional area ranged from 11.1 cm2 for clone EEG-29 to 27.6 cm2 for hybrid PA-150 * MA-15. Yield efficiency increment (the ratio of cumulative yield to the increase in trunk circumference), which indicated partitioning between the vegetative and reproductive components, ranged from 0.008 kg.cm-2 for clone CP-82 to 0.08 kg.cm-2 for clone EEG-29. An examination of biomass partitioning within the pod of the seven clones revealed that the beans accounted for between 32.0% (CP-82) and 44.5% (ICS-9) of the pod biomass. The study demonstrated the potential for yield improvement in cacao by selectively breeding for more efficient partitioning to the yield component.

J-measure based hybrid pruning for complexity reduction in classification rules

Prism is a modular classification rule generation method based on the ‘separate and conquer’ approach that is alternative to the rule induction approach using decision trees also known as ‘divide and conquer’. Prism often achieves a similar level of classification accuracy compared with decision trees, but tends to produce a more compact noise tolerant set of classification rules. As with other classification rule generation methods, a principle problem arising with Prism is that of overfitting due to over-specialised rules. In addition, over-specialised rules increase the associated computational complexity. These problems can be solved by pruning methods. For the Prism method, two pruning algorithms have been introduced recently for reducing overfitting of classification rules - J-pruning and Jmax-pruning. Both algorithms are based on the J-measure, an information theoretic means for quantifying the theoretical information content of a rule. Jmax-pruning attempts to exploit the J-measure to its full potential because J-pruning does not actually achieve this and may even lead to underfitting. A series of experiments have proved that Jmax-pruning may outperform J-pruning in reducing overfitting. However, Jmax-pruning is computationally relatively expensive and may also lead to underfitting. This paper reviews the Prism method and the two existing pruning algorithms above. It also proposes a novel pruning algorithm called Jmid-pruning. The latter is based on the J-measure and it reduces overfitting to a similar level as the other two algorithms but is better in avoiding underfitting and unnecessary computational effort. The authors conduct an experimental study on the performance of the Jmid-pruning algorithm in terms of classification accuracy and computational efficiency. The algorithm is also evaluated comparatively with the J-pruning and Jmax-pruning algorithms.

Genetic analysis reveals a novel locus in Vicia faba decoupling pigmentation in the flower from that in the extra-floral nectaries

The genetics of the stipule spot pigmentation (SSP) in faba bean (Vicia faba L.) was studied using four inbred lines, of which Disco/2 was zero-tannin (zt2) with colourless stipule spots, ILB938/2 was normal-tannin (ZT2) with colourless stipule spots, and both Aurora/2 and Mélodie/2 were ZT2 with coloured stipule spots. Crosses Mélodie/2 × ILB 938/2, Mélodie/2 × Disco/2, ILB 938/2 × Aurora/2 and ILB 938/2 × Disco/2 (A, B, C and D, respectively) were prepared, along with reciprocals and backcrosses, and advanced through single-seed descent. All F1 hybrid plants had pigmented stipule spots, and in the F2 generation, the segregation ratio fit 3 coloured:1 colourless in crosses A, B and C and 9:7 in cross D. In the F3 generation, the ratio fit 5:3 in crosses A and C and 25:39 in cross D, and in the F4 generation, 9:7 in cross A. SSP was linked to the zero-tannin characteristics (white flower) only in cross B. The results show that coloured stipule spot is dominant to colourless and that colouration is determined by two unlinked complementary recessive genes. We propose the symbols ssp2 for the gene associated with zt2 in Disco/2 and ssp1 for the gene not associated with tannin content in ILB938/2. The novel ssp1 locus was mapped at F5 in cross ‘A’ using Medicago truncatula-derived single-nucleotide polymorphism and was on chromosome 1 of faba bean, in a well-conserved region of M. truncatula chromosome 5 containing some candidate Myb and basic helix–loop–helix transcription factor genes.

Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing nonlinearity

We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR with respect to two traditional methods (4DVAR and ETKF) and an ensemble transform Kalman smoother (ETKS) on the Lorenz 1963 model. We specifically investigated this performance with increasing nonlinearity and using a quasi-static variational assimilation algorithm as a comparison. Using the analysis root mean square error (RMSE) as a metric, these methods have been compared considering (1) assimilation window length and observation interval size and (2) ensemble size to investigate the influence of hybrid background error covariance matrices and nonlinearity on the performance of the methods. For short assimilation windows with close to linear dynamics, it has been shown that all hybrid methods show an improvement in RMSE compared to the traditional methods. For long assimilation window lengths in which nonlinear dynamics are substantial, the variational framework can have diffculties fnding the global minimum of the cost function, so we explore a quasi-static variational assimilation (QSVA) framework. Of the hybrid methods, it is seen that under certain parameters, hybrid methods which do not use a climatological background error covariance do not need QSVA to perform accurately. Generally, results show that the ETKS and hybrid methods that do not use a climatological background error covariance matrix with QSVA outperform all other methods due to the full flow dependency of the background error covariance matrix which also allows for the most nonlinearity.

Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design

Heterosis refers to the phenomenon in which an F1 hybrid exhibits enhanced growth or agronomic performance. However, previous theoretical studies on heterosis have been based on bi-parental segregating populations instead of F1 hybrids. To understand the genetic basis of heterosis, here we used a subset of F1 hybrids, named a partial North Carolina II design, to perform association mapping for dependent variables: original trait value, general combining ability (GCA), specific combining ability (SCA) and mid-parental heterosis (MPH). Our models jointly fitted all the additive, dominance and epistatic effects. The analyses resulted in several important findings: 1) Main components are additive and additive-by-additive effects for GCA and dominance-related effects for SCA and MPH, and additive-by-dominant effect for MPH was partly identified as additive effect; 2) the ranking of factors affecting heterosis was dominance > dominance-by-dominance > over-dominance > complete dominance; and 3) increasing the proportion of F1 hybrids in the population could significantly increase the power to detect dominance-related effects, and slightly reduce the power to detect additive and additive-by-additive effects. Analyses of cotton and rapeseed datasets showed that more additive-by-additive QTL were detected from GCA than from trait phenotype, and fewer QTL were from MPH than from other dependent variables.