Identification of Wheat Varieties with a Parallel-Plate Capacitance Sensor Using Fisher’s Linear Discriminant Analysis

Fisher’s linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle (θ), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD models. Z and θ of a parallel-plate capacitance system, holding the wheat samples, were measured using an impedance meter, and the C value was computed. The best model developed classified the wheat varieties, with accuracy of 95.4%, over the six wheat varieties tested. This method is simple, rapid, and nondestructive and would be useful for the breeders and the peanut industry

Fortification Support Access Control Manipulate Procedure Intended for Relational Data

Present days majorly concentrated  on meticulous speculation on data.  Access control systems are every  time touch with  Safe and secrecy  maintenance of data but now a days  hackers acting like reliance. Then they are remove info from the user. Last few decades we are fight for the  accuracy privacy preserving on data  but however we not solved this type  of issue. The Access control mechanism avoids the unauthorized access of sensitive information. It protects the user information from the unauthorized access. The privacy protection mechanism is a much important concern in the case of sharing the sensitive information. The privacy protection mechanism provides better privacy for the sensitive information which is to be shared. The generally used privacy protection mechanism uses the generalization and suppression of the sensitive data. It prevents the privacy disclosure of the sensitive data. The privacy protection mechanism avoids the identity and attributes disclosure. The privacy is achieved by the high accuracy and consistency of the user information, ie., the precision of the user information. In this paper, it proposes a privacy persevered access control mechanism for relational data. The literature survey  might provide techniques for workload –aware anonymization for selection predicates, as the problem of satisfying the accuracy constraints for multiple roles has not been studied before. The purpose of the present project is to propose  heuristics for anonymization algorithms and to show the viability of the proposed approach for empirically  satisfying the imprecision bounds for more permission

Comparative evaluation of protein content in groundnut samples by near infrared reflectance spectroscopy and Skalar colorimetric methods

A lot of research has been done in developing groundnut cultivars with high-quality oil. As a result, methods for routinely determining oil content and quality have been developed and utilized1. However, groundnut is also a source of protein, and obviously, there is a need to develop a rapid, accurate and economic method that can be routinely used for screening a large number of groundnut cultivars for protein content. At the ICRISAT analytical service laboratory, protein (total N) in various crops is routinely determined by colorimetric method using Skalar auto analyser. However, near infrared reflectance spectroscopy (NIRS) also provides an opportunity to determine protein content in groundnut samples; and the method seems attractive as it is low cost, simple and rapid. The NIRS based method provides an automated measurement and has the potential to become a valuable tool for providing analytical support for agricultural research2,3. The objectives of this study were to estimate and compare the relative efficacy of the NIRS method, with that of a conventional colorimetric method, following digestion of ground samples, using Skalar autoanalyser for determining protein in groundnut samples..

Plant prebiotics and human health: Biotechnology to breed prebiotic-rich nutritious food crops

Microbiota in the gut play essential roles in human health. Prebiotics are non-digestible complex carbohydrates that are fermented in the colon, yielding energy and short chain fatty acids, and selectively promote the growth of Bifidobacteria and Lactobacillae in the gastro-intestinal tract. Fructans and inulin are the best-characterized plant prebiotics. Many vegetable, root and tuber crops as well as some fruit crops are the best-known sources of prebiotic carbohydrates, while the prebiotic-rich grain crops include barley, chickpea, lentil, lupin, and wheat. Some prebiotic-rich crop germplasm have been reported in barley, chickpea, lentil, wheat, yacon, and Jerusalem artichoke. A few major quantitative trait loci and gene-based markers associated with high fructan are known in wheat. More targeted search in genebanks using reduced subsets (representing diversity in germplasm) is needed to identify accessions with prebiotic carbohydrates. Transgenic maize, potato and sugarcane with high fructan, with no adverse effects on plant development, have been bred, which suggests that it is feasible to introduce fructan biosynthesis pathways in crops to produce health-imparting prebiotics. Developing prebiotic-rich and super nutritious crops will alleviate the widespread malnutrition and promote human health. A paradigm shift in breeding program is needed to achieve this goal and to ensure that newly-bred crop cultivars are nutritious, safe and health promoting

Genome-wide transcriptome and physiological analyses provide new insights into peanut drought response mechanisms

Drought is one of the main constraints in peanut production in West Texas and eastern New Mexico regions due to the depletion of groundwater. A multi-seasonal phenotypic analysis of 10 peanut genotypes revealed C76-16 (C-76) and Valencia-C (Val-C) as the best and poor performers under deficit irrigation (DI) in West Texas, respectively. In order to decipher transcriptome changes under DI, RNAseq was performed in C-76 and Val-C. Approximately 369 million raw reads were generated from 12 different libraries of two genotypes subjected to fully irrigated (FI) and DI conditions, of which ~329 million (90.2%) filtered reads were mapped to the diploid ancestors of peanut. The transcriptome analysis detected 4,508 differentially expressed genes (DEGs), 1554 genes encoding transcription factors (TFs) and a total of 514 single nucleotide polymorphisms (SNPs) among the identified DEGs. The comparative analysis between the two genotypes revealed higher and integral tolerance in C-76 through activation of key genes involved in ABA and sucrose metabolic pathways. Interestingly, one SNP from the gene coding F-box protein (Araip.3WN1Q) and another SNP from gene coding for the lipid transfer protein (Aradu.03ENG) showed polymorphism in selected contrasting genotypes. These SNPs after further validation may be useful for performing early generation selection for selecting drought responsive genotypes

Evaluating the Ability of Swell Prediction Models to Predict the Swell Behavior of Excessively High Plastic Soils

Lightly loaded structures underneath expansive soils encounter severe damage due to the swell/shrink nature of expansive soils resulting from moisture variations. Billions of dollars are spent every year to repair the damages caused by these soils in the U.S. and worldwide. Designing structures to accommodate the swelling strains is a major challenge as predicting the swelling potential of these soils accurately is not easy. A wide variety of swell prediction models have been introduced by various researchers to predict the behavior of these often-problematic expansive soils. These models include various properties of soils such as, plasticity characteristics, compaction conditions, consolidation characteristics, moisture content variations, matric suction, and clay mineralogical characteristics. However, these models are generally developed with typical moderate to high plastic soils in mind whose plasticity indices range from 25 to 45. Their applicability to soils that have liquid limits in the order of 200% is not well understood. In this paper, the ability of these models to predict the behavior of excessively high plastic soils with plasticity indices ranging from 45 to 85 were evaluated. For this purpose, four existing analytical prediction models that use combinations of above-mentioned properties were selected and used to predict the one-dimensional and three-dimensional swelling strains on three high swelling soils. These predictions were verified by conducting one-dimensional and three-dimensional swell tests on the three soil types. The swell tests were conducted at three different initial moisture contents to observe how well the models could predict different levels of moisture absorption. The ability of each of the four selected methods in predicting both 1D and 3D swell strains was discussed and their relative merits and demerits are highlighted. In addition, finite element modeling was performed to simulate one-dimensional and three-dimensional swell tests by using material models that use volumetric and suction changes with moisture contents to simulate expansive soil behavior within the finite element model. The results indicated that while the analytical prediction models gave reasonable results the finite element analysis predicted results were closest to the laboratory measure soils in case both 1D and 3D analyses. Among other analytical models the ones that incorporated mineralogical and suction data exhibited better results

Genetic enhancement of Valencia core collection and molecular characterization of U.S. peanut mini core collection using SSR markers

A core collection is a gateway for the utilization of diverse accessions with beneficial traits in applied breeding programs. 630 USDA Valencia peanut germplasm and a control cultivar (New Mexico Valencia C) were evaluated for 26 descriptors in augmented design for two seasons. The accessions were stratified by country of origin, and data on morphological and agronomic descriptors were used for clustering following Ward’s method. About 10% or a minimum of one accession from each cluster and region was selected to develop core subset of 77 accessions. The similarity in correlation coefficients in entire collection and core subset suggest that this core subset has preserved most of the co-adapted gene complexes controlling these associations. The peanut breeders engaged in improving the genetic potential of Valencia peanuts will find this core subset useful in cultivar development

Genome-Wide Linkage Scan for Genes Influencing Plasma Triglyceride Levels in the Veterans Administration Genetic Epidemiology Study

OBJECTIVE—Elevated plasma triglyceride concentration is a component of the insulin resistance syndrome and is commonly associated with type 2 diabetes, obesity, and coronary heart disease. The goal of our study was to perform a genome-wide linkage scan to identify genetic regions that influence variation in plasma triglyceride levels in families that are enriched with individuals with type 2 diabetes

Population structure and diversity in Valencia peanut germplasm collection

Valencia peanuts [Arachis hypogaea L. subsp. fastigiata Waldron var. fastigiata (Waldron) Krapov. & W. C. Greg.] are well known for their in-shell market value. Assessment of genetic diversity is key to the success of developing improved cultivars with desirable agronomic and quality traits. Seventy-eight U.S. Valencia core collection accessions together with 36 Valencia accessions representing the global peanut mini-core collection were used to study population structure and diversity and to identify genetically diverse Valencia germplasm for use in peanut breeding. Fifty-two simple sequence repeats loci amplifi ed 683 alleles, with an average of 13 alleles per locus. The mean polymorphism information content and gene diversity, respectively, were 0.270 and 0.335. The pairwise genetic distance ranged from 0.143 to 0.474, with an average of 0.631. Neighbor-joining clustering, principal coordinate analysis, and STRUCTURE analysis consistently separated the Valencia germplasm into fi ve clusters with two distinct major groups. The fi rst major group consisted of genotypes from South America (64%) with few accessions from Africa, North America, Caribbean, and European regions. The second group consisted of accessions mostly from diverse regions of Africa, North and South America, Asia, and the Caribbean. However, the structuring was not related to the geographic origin and several admixtures were observed. The information generated in this study and phenotyping of this material for biotic and abiotic stress responses and yield-quality traits will facilitate selection of trait-specifi c, genetically diverse parents for developing Valencia peanut cultivars with a broad genetic base

Genome-Wide Mapping of Quantitative Trait Loci for Yield-Attributing Traits of Peanut

Peanuts (Arachis hypogaea L.) are important high-protein and oil-containing legume crops adapted to arid to semi-arid regions. The yield and quality of peanuts are complex quantitative traits that show high environmental influence. In this study, a recombinant inbred line population (RIL) (Valencia-C × JUG-03) was developed and phenotyped for nine traits under two environments. A genetic map was constructed using 1323 SNP markers spanning a map distance of 2003.13 cM. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified seventeen QTLs for nine traits. Intriguingly, a total of four QTLs, two each for 100-seed weight (HSW) and shelling percentage (SP), showed major and consistent effects, explaining 10.98% to 14.65% phenotypic variation. The major QTLs for HSW and SP harbored genes associated with seed and pod development such as the seed maturation protein-encoding gene, serine-threonine phosphatase gene, TIR-NBS-LRR gene, protein kinase superfamily gene, bHLH transcription factor-encoding gene, isopentyl transferase gene, ethylene-responsive transcription factor-encoding gene and cytochrome P450 superfamily gene. Additionally, the identification of 76 major epistatic QTLs, with PVE ranging from 11.63% to 72.61%, highlighted their significant role in determining the yield- and quality-related traits. The significant G × E interaction revealed the existence of the major role of the environment in determining the phenotype of yield-attributing traits. Notably, the seed maturation protein-coding gene in the vicinity of major QTLs for HSW can be further investigated to develop a diagnostic marker for HSW in peanut breeding. This study provides understanding of the genetic factor governing peanut traits and valuable insights for future breeding efforts aimed at improving yield and quality