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Showing papers by "Indian Agricultural Statistics Research Institute published in 2010"


Journal ArticleDOI
TL;DR: An investigation was undertaken to explore the biocidal efficacy of fungicidal compound(s) produced by Calothrix elenkenii against damping-off disease in three vegetable crops-tomato, chilli and brinjal and revealed the superiority of seed treatment with ethyl acetate extracts, in terms of percent mortality and plant parameters.
Abstract: An investigation was undertaken to explore the biocidal efficacy of fungicidal compound(s) produced by Calothrix elenkenii against damping-off disease in three vegetable crops-tomato, chilli and brinjal. Treatments included application of seeds soaked in water (control), culture filtrate and ethyl acetate extract of Calothrix elenkenii and Metalaxyl in potting mix inoculated with Pythium aphanidermatum in plastic pots. The observations taken after a period of four weeks revealed the superiority of seed treatment with ethyl acetate extracts, in terms of percent mortality and plant parameters. ANOVA revealed that the treatments, crops (tomato, chilli and brinjal) and their interactions exerted a significant influence on the parameters analyzed. Chilli recorded the highest percentage of survivors and responded best to the seed treatment with ethyl acetate extract of Calothrix elenkenii. Future work is being undertaken towards formulation of a biocontrol agent using Calothrix elenkenii and understanding the m...

76 citations


Journal ArticleDOI
TL;DR: Monte Carlo simulations based on both simulated and real datasets show that the proposed model-based direct estimator and its associated mean squared error estimator perform well and are worth considering in small area estimation applications where the underlying population regression relationships are non-linear or have a complicated functional form.

36 citations


Journal ArticleDOI
TL;DR: In this paper, the authors extended the work of Gupta et al. (2010) to s-level column balanced supersaturated designs and studied the optimality of the resulting design.

21 citations


Journal ArticleDOI
TL;DR: It seems that the interplay of the genotype-phenotype relationship for quantitative variation is not only complex but also requires a dialectical approach for its understanding in which ‘parts’ and ‘whole’ evolve as a consequence of their relationship and the relationship itself evolves.
Abstract: Most characters of economic importance in plants and animals, and complex diseases in humans, exhibit quantitative variation, the genetics of which has been a fascinating subject of study since Mendel’s discovery of the laws of inheritance. The classical genetic basis of continuous variation based on the infinitesimal model of Fisher and mostly using statistical methods has since undergone major modifications. The advent of molecular markers and their extensive mapping in several species has enabled detection of genes of metric characters known as quantitative trait loci (QTL). Modeling the high-resolution mapping of QTL by association analysis at the population level as well as at the family level has indicated that incorporation of a haplotype of a pair of single-nucleotide polymorphisms (SNPs) in the model is statistically more powerful than a single marker approach. High-throughput genotyping technology coupled with micro-arrays has allowed expression of thousand of genes with known positions in the genome and has provided an intermediate step with mRNA abundance as a sub-phenotype in the mapping of genotype onto phenotype for quantitative traits. Such gene expression profiling has been combined with linkage analysis in what is known as eQTL mapping. The first study of this kind was on budding yeast. The associated genetic basis of protein abundance using mass spectrometry has also been attempted in the same population of yeast. A comparative picture of transcript vs. protein abundance levels indicates that functionally important changes in the levels of the former are not necessarily reflected in changes in the levels of the latter. Genes and proteins must therefore be considered simultaneously to unravel the complex molecular circuitry that operates within a cell. One has to take a global perspective on life processes instead of individual components of the system. The network approach connecting data on genes, transcripts, proteins, metabolites etc. indicates the emergence of a systems quantitative genetics. It seems that the interplay of the genotype-phenotype relationship for quantitative variation is not only complex but also requires a dialectical approach for its understanding in which ‘parts’ and ‘whole’ evolve as a consequence of their relationship and the relationship itself evolves.

17 citations


Journal ArticleDOI
TL;DR: A review of the literature on two-level supersaturated designs can be found in this paper, where the focus is on the lower bound of the value of E(s 2 ), a measure of departure from orthogonality, and constructing designs that attain these lower bounds.
Abstract: Supersaturated Designs (SSDs) are fractional factorial designs in which the run size is not enough to estimate the main effects of all the factors in the experiment Two-level SSDs have been studied extensively in the literature. The thrust of research has been on obtaining lower bounds to the value of E(s 2), a measure of departure from orthogonality, and constructing designs that attain these lower bounds. The focus of this paper is to review the literature on two-level SSDs.

10 citations


Journal ArticleDOI
TL;DR: In this article, a wavelet analysis in frequency domain for analyzing time-series data is studied, which is carried out using SPLUS WAVELET TOOLKIT software package, where the discrete wavelet transform (DWT) and multiresolution analysis (MRA) of the data are computed to analyze the behaviour of trend present in the time series data.
Abstract: The powerful methodology of “Wavelet analysis in frequency domain” for analyzing time-series data is studied. As an illustration, Indian monsoon rainfall time-series data from 1879–2006 is considered. The entire data analysis is carried out using SPLUS WAVELET TOOLKIT software package. The discrete wavelet transform (DWT) and multiresolution analysis (MRA) of the data are computed to analyze the behaviour of trend present in the time-series data in terms of different times and scales. By using bootstrap method, size and power of the test for testing significance of trend in the data is computed. It is found that the size of the test for Daubechies wavelet is more than that for Haar wavelet. In respect of both Daubechies and Haar wavelet filters, it is found that the test for presence of trend is unbiased. Also, power of the test for both Daubechies (D4) and Haar wavelets, at level 5 is less than the one at level 6. Further, Haar wavelet at level 6 has generally performed better than Daubechies (D4) wavelet at level 6 in terms of power of the test. Using the former wavelet, a declining trend in the data under consideration is revealed.

6 citations


Book ChapterDOI
12 Jul 2010
TL;DR: This paper proposes a cluster ensemble method based on Discriminant Analysis to obtain robust clustering using K-means clusterer and provides strong empirical evidence of the high quality of resultant clustering scheme.
Abstract: Cluster ensemble technique has attracted serious attention in the area of unsupervised learning. It aims at improving robustness and quality of clustering scheme, particularly in scenarios where either randomization or sampling is the part of the clustering algorithm. In this paper, we address the problem of instability and non robustness in K-means clusterings. These problems arise naturally because of random seed selection by the algorithm, order sensitivity of the algorithm and presence of noise and outliers in data. We propose a cluster ensemble method based on Discriminant Analysis to obtain robust clustering using K-means clusterer. The proposed algorithm operates in three phases. The first phase is preparatory in which multiple clustering schemes generated and the cluster correspondence is obtained. The second phase uses discriminant analysis and constructs a label matrix. In the final stage, consensus partition is generated and noise, if any, is segregated. Experimental analysis using standard public data sets provides strong empirical evidence of the high quality of resultant clustering scheme.

6 citations


Journal ArticleDOI
TL;DR: In this article, Gupta, Parsad, Kole and Bhar developed an algorithm to generate multi-level supersaturated designs using the popular E(fNOD) and E(χ2) criterion.
Abstract: Motivated by the computer search algorithms for constructing two-level supersaturated designs by Heavlin and Finnegan (1993), Li and Wu (1997), Nguyen (1996), Lejeune (2003) and Gupta, Parsad, Kole and Bhar (2008), this paper develops an algorithm to generate multi-level supersaturated designs. Popular E(f NOD) and E(χ2) criterion have been used as a measure of non-orthogonality for the designs generated. The algorithm also ensures that no two columns in the designs generated are fully aliased. A catalogue of 120 optimal supersaturated designs for different number of factors m, design runs n, with 5 ≤ n ≤ 16 runs, and different number of factor levels q, with 3 ≤ q ≤ 6, has been prepared. All the designs generated are f NOD-optimal; some designs are χ2-optimal too.

6 citations


Journal Article
TL;DR: In this paper, the development of Artificial Neural Network (ANN) models for predicting wheat crop evapotranspiration using measured weather data and lysimeter measured crop EVAP (ETc) for Delhi is described.
Abstract: The development of Artificial Neural Network (ANN) models for prediction of wheat crop evapotranspiration using measured weather data and lysimeter measured crop evapotranspiration (ETc) for Delhi is described. Eleven meteorological variables were taken into consideration for this study. ANN models were developed in MATLAB© with different network architectures using Feed Forward Back Propagation (FFBP) and Elman Back Propagation (EBP) algorithms. The total length of data record used was 744, out of that 60% was taken for model training, 20% for model testing and remaining 20% for model validation. Training and testing data sets were used for model development purpose, while validation data set was used for model evaluation. The ANN modelling strategy having back propagation learning algorithm, log-sigmoid transfer function and model input strategy-1 exhibited better results with Nash-Sutcliffe Coefficient (E) and Root Mean Square Error (RMSE) of 0.972 and 0.498 mm for development data set and 0.776 and 1.334 mm for evaluation data set, respectively. FAO Penman-Monteith method was also used to estimate evapotranspiration. Comparison of the ANN predicted ETc and FAO Penman-Monteith estimated ETc with lysimeter values showed that the ANN predicted ETc was more close to the lysimeter measured values.

6 citations


Journal Article
TL;DR: In this paper, a mechanical onion seed extractor was evaluated to study the effects of operational variables on seed quality parameters, and a performance index was developed for using principal component analysis method that proved to be a tool to select best design and operational variables.
Abstract: A mechanical onion seed extractor was evaluated to study the effects of operational variables on seed quality parameters, and a performance index was developed for using principal component analysis method that proved to be a tool to select best design and operational variables. The concave clearance marginally affected vigour index, and the average values were 30.27, 30.70 and 29.63 per cent. However, the average vigour index was 29.89, 28.97 and 31.74% at the cylinder speed of 3, 4 and 5 m/s, respectively. The best performance combination with performance index of 1.0 was obtained for spike tooth mechanism, with concave clearance of 4.5 mm and cylinder speed of 5 m/s. The performance indices were categorized as high (1–6), moderate (7–24) and low performance (25–27) for onion seed extractor. The best combination with highest value of performance index was obtained with spike tooth extraction mechanism (E1), 4.5 mm concave clearance (C3) and 5 m/s cylinder speed (S3).

5 citations


Journal ArticleDOI
TL;DR: In this paper, the importance of finding appropriate parameterizations for nonlinear statistical models is highlighted, and the influence of each observation on the estimation of each parameter is displayed for each error model.
Abstract: The importance of finding appropriate parameterizations for nonlinear statistical models is highlighted. The purpose of this paper is to explore the principles of reparameterization, using an example from real data. It is shown that stable parameterizations allow likelihood-based confidence intervals to be computed. Further, it is noted that the choice of error distribution may seriously affect the estimates and confidence intervals of quantities of interest. The influence of each observation on the estimation of each parameter is displayed for each error model. Multidimensional likelihood contours may be displayed pairwise using profile likelihood computations.

Proceedings ArticleDOI
01 Dec 2010
TL;DR: The design and development of a system that helps the managers in educational institutions to screen, recruit, manage and develop the team of competent faculty members for the enhancement of teaching and learning process is presented.
Abstract: An expert system is computer software that solves real world problems using human knowledge and reasoning skills Knowledge base is the heart and mind of such system where knowledge is stored in the form of rules, databases, heuristics and facts The key conceptual challenge in this approach is the exploitation of the domain knowledge that is vast and mainly in the minds of experts and is a major bottleneck in development The field of Knowledge engineering addresses these challenges by applying AI principles to add new knowledge in the system and extract information with explanation with the powerful mechanism The developed system is an example of such system that allows a user to add decision making rules and provide platform to add new facts from the existing knowledge, by applying heuristics techniques and methods associated with it The evaluation of human resources is the continuous process in any organization It involves a complex and complicated process to match the right competencies for the right job as per the requirements with in the organization It requires the years of experience for the competence assessment and performance manager to build up competent team and utilize the talent of the team to get the job performed in an efficient manner The development of expert system helps in acquiring the knowledge of the domain expert by the process of knowledge engineering to represent it in the form of rules and facts Consequently it helps us to develop the inference process by applying the Heuristics obtained by various statistical techniques such as regression analysis, classification analysis This inference process becomes instrumental to constitute the production rules that help in decision making for the various stake holders in order to perform their work in a strategic manner To achieve this purpose, the developed Inference engine works both forward (evaluation) and backward chaining (sensitivity analysis) In the paper we have presented the design and development of a system that helps the managers in educational institutions to screen, recruit, manage and develop the team of competent faculty members for the enhancement of teaching and learning process The knowledge elicitation technique used for developing the knowledge base of the competence and performance assessment system is the statistical survey method The results of analysis helped us to develop the inference engine and decision making rules The developed system helps to identify a right person for the right job, to add new designations as per the organization's mission and vision planned by the management and makes a mechanized system for its growth The system is designed for the Indian higher technical education system

Journal ArticleDOI
TL;DR: Generalized incomplete Trojan-type designs are defined to be row-column designs in which each cell, corresponding to the intersection of row and column, contains more than one treatment and the rows are incomplete as discussed by the authors.

Journal ArticleDOI
TL;DR: Two three-class association schemes called tetrahedral association scheme and cubical association scheme have been proposed along with methods of constructing partially balanced incomplete block designs based on these schemes and are seen to be more efficient than the circular lattices.
Abstract: Here, two three-class association schemes called tetrahedral association scheme and cubical association scheme have been proposed along with methods of constructing partially balanced incomplete block designs based on these schemes. Designs based on cubical association scheme are found to be resolvable. An outline of the method of analysis of the designs has also been presented together with a list of PBIB(3) designs obtained using the proposed methods for number of treatments v < 100. The proposed designs are seen to be more efficient than the circular lattices (PBIB(3) designs) with the same number of experimental units for the estimation of elementary treatment effect contrasts.

Journal ArticleDOI
TL;DR: In this article, generalized autoregressive conditional heteroscedastic (GARCH) nonlinear time series model is employed to describe data sets depicting volatility and its estimation procedure is thoroughly studied.
Abstract: Generalized autoregressive conditional heteroscedastic (GARCH) nonlinear time series model may be employed to describe data sets depicting volatility. This model along with its estimation procedure is thoroughly studied. Lagrange multiplier (LM) test for testing presence of Autoregressive conditional heteroscedastic (ARCH) effects is also discussed. As an illustration, modeling and forecasting of monthly rainfall data of Sub-Himalayan West Bengal meteorological subdivision, India is carried out. As the data exhibits presence of seasonal component, Hylleberg, Engle, Granger and Yoo (1990) [HEGY] seasonal unit root test is applied to the data with a view to make the series stationary through “differencing filter”. Subsequently, GARCH model is employed on the residuals obtained after carrying out Periodic autoregressive (PAR) modeling of the seasonal variation. Further, Mixture periodic ARCH (MPARCH) model, which is an extension of GARCH model, is also applied on zero conditional mean residual serie...

Journal ArticleDOI
TL;DR: A versatile nonparametric nonlinear time-series model, viz.
Abstract: In this paper, a versatile nonparametric nonlinear time-series model, viz. Functional-coefficient autoregressive (FCAR) model, in which the coefficient function changes gradually rather than abruptly, is considered. As an illustration, this model is applied for modelling and forecasting of India's annual export lac data during the period 1900 to 2000. Comparison of the performance of FCAR model vis-` the Self exciting threshold autoregressive (SETAR) and Autoregressive integrated moving average (ARIMA) models is also made from the viewpoint of dynamic one-step and two-step ahead forecasts along with Mean square prediction error (MSPE), Mean absolute prediction error (MAPE) and Relative mean absolute prediction error (RMAPE). The SAS, Ver. 9.1 and SPSS software packages are used for data analysis. Superiority of FCAR model over SETAR and ARIMA models is demonstrated for the data under consideration.

Journal ArticleDOI
TL;DR: An alternative estimator of the variance of the ratio estimator under the two phase sampling scheme has been proposed, approximately unbiased and more efficient than the existing classical estimator due to Cochran and Rao-Sitter.
Abstract: An alternative estimator of the variance of the ratio estimator under the two phase sampling scheme has been proposed. The proposed variance estimator is approximately unbiased and more efficient than the existing classical estimator due to Cochran (2) and Rao-Sitter (6) under a linear superpoulation model with intercept.

Journal ArticleDOI
TL;DR: In this article, the status of social and economic well-being of Indian families as measured by a primary survey-based composite index, the India Protection Index (IPI), is discussed.
Abstract: The success and failure of any democratic government is gauged in terms of how effectively it has fulfilled its constitutional obligation of enhancing social and economic well-being, particularly the common man. While developed economies use a set of indices to measure well-being, a systematic and comprehensive empirical assessment of well-being is found wanting in most developing countries, including India. This paper discusses the status of social and economic well-being of Indian families as measured by a primary survey-based composite index, the India Protection Index (IPI), which is an integration of the important dimensions of well-being. It finds that nearly 65 per cent of households and people in India have a reasonable degree of protection (i.e., the power of well-being) and that most of the less- and under-protected are daily wage earners, without any village–urban divide. The western states are better protected, as Maharashtra has the largest number of well-protected households (16 per cent), f...

Posted Content
TL;DR: In this article, a mixture model based approach for small area estimation (SAE) for zero-inflated data under a mixture of linear mixed model was proposed, which produces an efficient set of small area estimates.
Abstract: Small area estimation (SAE) under a linear mixed model may not be efficient if data contain substantial proportion of zeros than would be expected under standard model assumptions (hereafter zero-inflated data). We discuss the SAE for zero-inflated data under a mixture model (Fletcher et al., 2005 and Karlberg, 2000) that account for excess zeros in the data. Our results from simulation studies show that mixture model based approach for SAE works well and produces an efficient set of small area estimates. An application to real survey data from the National Sample Survey Organisation of India demonstrates the satisfactory performance of the approach.