Combined analysis of categorical and numerical descriptors of Australian groundnut accessions using nonlinear principal component analysis

For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection I. Two-way quantitative data

Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection. II. Two-way data with mixed data types

As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

Patterns of diversity in fatty acid composition in the Australian groundnut germplasm collection

Knowledge of the amounts and types of fatty acids in groundnut oil is beneficial, particularly from a nutritional standpoint. Germplasm evaluation data for fatty acid composition on 819 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for eight quantitative fatty acid descriptors have been documented. Statistical assessment, via methods of pattern analysis, summarised and described the patterns of variation in fatty acid composition of the groundnut accessions in the Australian germplasm collection. Presentation of the results from principal components analysis and hierarchical cluster analysis using a biplot was shown to be a very useful interpretative tool. Such a biplot enables a simultaneous examination of the relationships among all the accessions and the fatty acids. Unlike that information available via database searches, the results from contribution analysis together with the biplot provide a global picture of the diversity available for use in plant breeding programs. The use of standardised data for eight fatty acids, compared to using three specific fatty acids, provided a better description of the total diversity available because it remains relevant with possible changes in the nutritional preferences for fatty acids. Fatty acid composition was found to vary in relation to the branching pattern of the accessions. This pattern is generally indicative of the botanical types of groundnuts; Virginia (alternate) compared to Spanish and Valencia (sequential) botanical types.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

A soluble preparation from developing groundnut seeds (Arachis hypogaea) catalyzes de novo synthesis of long chain fatty acids

A 100,000 x g supernatant fraction prepared from developing groundnut seeds (30-35 days after flowering) catalyzed the synthesis of fatty acids from [l-14C]acetate at a rate of 120nmoles of acetate incorporated per hr per gram fresh weight of tissue. 90% of this incorporated label was associated with fatty acids. The major fatty acids formed were stearic- (77%) and palmitic acids (14%) with 4% of oleic acid. The fatty acid synthetase activity was stable when stored at 0-4 degrees C for at least fifteen days. It is concluded from these results that acetyl-coA carboxylase and all the enzymes of fatty acid synthetase from developing groundnut seeds are soluble.

Genetic Options for Drought Management in Groundnut

Groundnut is one of the principal oilseeds in the world. It is cultivated on 24.8 million ha with a total production of 32.8 million t and an average productivity of 1.32 t ha-'. Developing countries account for 96.9% of the world groundnut area and 93.8% of total production. Production is concentrated in Asia (56.8% area and 66.5% production of the world) and Africa (38.0% area and 24.7% production). The groundnut productivity in Africa is only 0.86 t ha-' compared with 1.55 t hx1 of Asia. The world groundnut economy-facts, trends and outlook are desaibed in detail by Freeman et al., 1999. Briefly, in medium-term (i.e. up to 2010), 'groundnut production and consumption is likely to shift increasingly to developing countries; production will grow in all regions but most rapidly in Asia, slowly in sub-Saharan Africa and decline in Latin America; and utilizationwill continue to shift away from groundnut oil toward groundnut meal, specially confectionery products'.

Distribution and abundance of white grubs (Coleoptera: Scarabaeidae) on groundnut in southern India

Scarab species associated with groundnuts were surveyed in Andhra Pradesh, Karnataka and Tamil Nadu, southern India, between 1995 and 2001. Scarab adults were collected from trees on which they were feeding and/or mating, and larvae (white grubs) from groundnut fields. Holotrichia species, especially H. reynaudi and H. serrata were the major species associated with groundnut. H. reynaudi predominated in the central Deccan area, while H. serrata was most abundant in areas to the south and west. A new, undescribed, Holotrichia species near H. consanguinea was collected south and south-west of Hyderabad in mixed populations with H. reynaudi. However, the full extent of this new species’ distribution remains uncertain. H. rufoflava was rarely associated with groundnut, but was common as an adult at some locations. Other genera encountered during surveys were Anomala, Adoretus, Schizonycha, Autoserica. In survey data, densities of Holotrichia larvae and ‘all other white grubs’ were both very highly correlated with % of damaged groundnut plants. These correlations in combination with concurrent observations of plant damage establish a causal link between white grubs and plant damage and death in southern Indian groundnut. Ranking of preferred host trees for adults were developed from field observations for four Holotrichia species and Schizonycha spp. and will assist grower-initiated surveys of pest occurrence. In combination with insecticide efficacy data published elsewhere, the survey provides the basis for an environmentally friendly and economically viable pest-management system for white grubs on groundnut in southern India.

Damage potential of two Scarab species on groundnut

The damage potential of two phytophagous scarab larvae on groundnut (peanut) yield was determined. Holotrichia serrata, a root and pod feeding species from southern India, was studied in microplots while the damage potential of Heteronyx piceus, a pod feeder from Queensland, Australia, was determined by analysis of on-farm chemical-rate trials. H. serrata larva reduced groundnut yield by an average of 7.52 g/ larva. In crops yielding less and more than 1900 kg ha-1, H. piceus reduced yield by 4.20 g and 1.43 g/ larva, respectively. These damage potential estimates were used to determine provisional economic injury levels (EIL). For H. piceus, the provisional EIL is 1.67 and 4.91 larvae/ row-metre in crops yielding less and more than 1900 kg/ha, respectively. For H. serrata, the provisional EIL is one H. serrata larva in 7.1 m2. As more than 70% of southern India groundnut fields have Holotrichia populations greater than 1 larva in 1.35 m2, more widespread use of chlorpyrifos seed dressing of groundnut is likely to produce regional economic benefits.

Management of white grubs (Coleoptera: Scarabaeidae) on groundnut in southern India

The chemical control of groundnut white grubs, Holotrichia serrata F. and H. reynaudi Blanchard (Coleoptera: Scarabaeidae), was studied in south--central India. Microplot trials demonstrated that chlorpyrifos and imidacloprid seed--dressings were effective against H. serrata at rates as low as 0.6 and 3.5 g a.i. kg-1, respectively, while microplot and on--farm trials showed that 1.2 and 3.5 g a.i. kg-1of chlorpyrifos and imidacloprid, respectively, were required for H. reynaudi. Chlorpyrifos residue analyses indicated that at 20 days after sowing (d.a.s.) rates up to 5.0 g a.i. kg-1 produced residues in soil and groundnut seedlings markedly below the relevant MRL, and no detectable residues at harvest under the southern Indian rainy--season environment. A farmer survey found that in Andhra Pradesh (AP), insecticides (chlorpyrifos and phorate) were applied for white grub control in 37.5% of farms sampled, while no insecticides were applied for this purpose in Karnataka and Tamil Nadu. The white grub density on farms in AP where insecticide had been applied averaged 0.07 larvae m-2, compared to 1.04 larvae m-2 in the remaining AP farms. In AP, Karnataka and Tamil Nadu, 70%, 42% and 39% of currently untreated groundnut fields, respectively, exceed the provisional economic threshold. A survey in the Anantapur district of AP found that farmer’s target and achieved rates for seed treatment averaged 0.44 and 0.52 g a.i. kg-1, both below optimal rates determined in microplot experiments. These data provide the foundation for an effective and sustainable program of management for groundnut white grubs in south--central India by providing key efficacy data and baseline data on farmer insecticide- use patterns.

Isolation and characterization of novel microsatellite markers and their application for diversity assessment in cultivated groundnut (Arachis hypogaea)

Background: Cultivated peanut or groundnut (Arachis hypogaea L.) is the fourth most important oilseed crop in the world, grown mainly in tropical, subtropical and warm temperate climates. Due to its origin through a single and recent polyploidization event, followed by successive selection during breeding efforts, cultivated groundnut has a limited genetic background. In such species, microsatellite or simple sequence repeat (SSR) markers are very informative and useful for breeding applications. The low level of polymorphism in cultivated germplasm, however, warrants a need of larger number of polymorphic microsatellite markers for cultivated groundnut. Results: A microsatellite- enriched library was constructed from the genotype TMV2. Sequencing of 720 putative SSR-positive clones from a total of 3,072 provided 490 SSRs. 71.2% of these SSRs were perfect type, 13.1% were imperfect and 15.7% were compound. Among these SSRs, the GT/CA repeat motifs were the most common (37.6%) followed by GA/CT repeat motifs (25.9%). The primer pairs could be designed for a total of 170 SSRs and were optimized initially on two genotypes. 104 (61.2%) primer pairs yielded scorable amplicon and 46 (44.2%) primers showed polymorphism among 32 cultivated groundnut genotypes. The polymorphic SSR markers detected 2 to 5 alleles with an average of 2.44 per locus. The polymorphic information content (PIC) value for these markers varied from 0.12 to 0.75 with an average of 0.46. Based on 112 alleles obtained by 46 markers, a phenogram was constructed to understand the relationships among the 32 genotypes. Majority of the genotypes representing subspecies hypogaea were grouped together in one cluster, while the genotypes belonging to subspecies fastigiata were grouped mainly under two clusters. Conclusion. Newly developed set of 104 markers extends the repertoire of SSR markers for cultivated groundnut. These markers showed a good level of PIC value in cultivated germplasm and therefore would be very useful for germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships in cultivated groundnut as well as related Arachis species.

SSR analysis of cultivated groundnut (Arachis hypogaea L.) germplasm resistant to rust and late leaf spot diseases

Cultivated groundnut (Arachis hypogaea L.) is an agronomically and economically important oilseed crop grown extensively throughout the semi-arid tropics of Asia, Africa and Latin America. Rust (Puccinia arachidis) and late leaf spot (LLS, Phaseoisariopsis personata) are among the major diseases causing significant yield loss in groundnut. The development of varieties with high levels of resistance has been constrained by adaptation of disease isolates to resistance sources and incomplete resistance in resistant sources. Despite the wide range of morphological diversity observed in the cultivated groundnut gene pool, molecular marker analyses have thus far been unable to detect a parallel level of genetic diversity. However, the recent development of simple sequence repeat (SSR) markers presents new opportunities for molecular diversity analysis of cultivate groundnut. The current study was conducted to identify diverse disease resistant germplasm for the development of mapping populations and for their introduction into breeding programs. Twenty-three SSRs were screened across 22 groundnut genotypes with differing levels of resistance to rust and LLS. Overall, 135 alleles across 23 loci were observed in the 22 genotypes screened. Twelve of the 23 SSRs (52%) showed a high level of polymorphism, with PIC values ≥0.5. This is the first report detecting such high levels of genetic polymorphism in cultivated groundnut. Multi-dimensional scaling and cluster analyses revealed three well-separated groups of genotypes. Locus by locus AMOVA and Kruskal-Wallis one-way ANOVA identified candidate SSR loci that may be valuable for mapping rust and LLS resistance. The molecular diversity analysis presented here provides valuable information for groundnut breeders designing strategies for incorporating and pyramiding rust and late leaf spot resistances and for molecular biologists wishing to create recombinant inbred line populations to map these traits.

NSs Encoded by Groundnut Bud Necrosis Virus Is a ifunctional Enzyme

Groundnut bud necrosis virus (GBNV), a member of genus Tospovirus in the family Bunyaviridae, infects a large number of leguminosae and solanaceae plants in India. With a view to elucidate the function of nonstructural protein, NSs encoded by the small RNA genome (S RNA), the NSs protein of GBNV-tomato (Karnataka) [1] was over-expressed in E.coli and purified by Ni-NTA chromatography. The purified rNSs protein exhibited an RNA stimulated NTPase activity. Further, this activity was metal ion dependent and was inhibited by adenosine 5' (beta, gamma imido) triphosphate, an ATP analog. The rNSs could also hydrolyze dATP.Interestingly, in addition to the NTPase and dATPase activities, the rNSs exhibited ATP independent 5' RNA/DNA phosphatase activity that was completely inhibited by AMP. The 5' alpha phosphate could be removed from ssDNA, ssRNA, dsDNA and dsRNA thus confirming that rNSs has a novel 5' alpha phosphatase activity. K189A mutation in the Walker motif A (GxxxxGKT) resulted in complete loss of ATPase activity, but the 5'phosphatase activity was unaffected. On the other hand, D159A mutation in the Walker motif B (DExx) resulted in partial loss of both the activities. These results demonstrate for the first time that NSs is a bifunctional enzyme, which could participate in viral movement, replication or in suppression of the host defense mechanism.

Effect of phenoxy acids and their derivatives on lipid metabolism in groundnut (Arachis hypogaea) leaves

The effect of four phenoxy compounds [2,4-dichlorophenoxyacetic acid (2,4-D), 2,4,5-trichlorophenoxyacetic acid, 4-chlorophenoxyacetic acid 2-(dimethylamino)ethyl ester (centrophenoxine), and 4-chlorophenoxy ethyl 2-(dimethylamino) ethyl ether (neophenoxine)] on lipid metabolism in groundnut (Arachis hypogaea) leaves was investigated under nonphotosynthetic conditions. In experiments with leaf disks, the uptake of [1-14C]acetate, [32P]orthophosphate, [35S]sulfate and [methyl-14C]choline was substantially inhibited by all the phenoxy compounds except neophenoxine. When the incorporation of these precursors into lipids was measured and expressed as percentage of total uptake, there was significant inhibition of incorporation of [1-14C]acetate and [32P]orthophosphate into lipids by all the compounds except neophenoxine. The incorporation of [methyl-14C]choline was unaffected by all except centrophenoxine which showed stastically significant stimulation. [35S]Sulfate incorporation into lipids was markedly inhibited only by centrophenoxine. The fatty acid synthetase of isolated chloroplasts assayed in the absence of light was inhibited 20–50% by the phenoxy compounds at 0.5 mM concentration. This inhibition showed a dependence on time of preincubation with the herbicide suggesting an interaction with the enzyme. It was, however, reversible and excess substrate did not prevent the inhibition, suggesting that the herbicide interaction may not be at the active site. sn-Glycerol-3-phosphate acyltransferase in the chloroplast and microsomal fractions was inhibited by 2,4-D while the phosphatidic acid phosphatase was insensitive to all the phenoxy compounds. It is concluded that phenoxy compounds affect precursor uptake, their incorporation into lipids, and the chloroplast fatty acid synthetase. The free acids were the most potent compounds while the ester (centrophenoxine) was less effective and the ether (neophenoxine) was completely ineffective in their influence on lipid metabolism.