Indian Agricultural Statistics Research Institute

About: Indian Agricultural Statistics Research Institute is a facility organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Small area estimation. The organization has 454 authors who have published 870 publications receiving 7987 citations.

An Empirical Investigation on Classical Clustering Methods

Abstract: Five classical clustering methods: four hierarchical -single linkage, average-between linkage, average-within linkage, Wards - and one non-hierarchical - k-means - using five different distance measures: squared Euclidean, city block, Chebychev’s, Pearson correlation and Minkowski have been compared on the basis of simulated multivariate data on paddy crop genotypes. The performance of different clustering methods was compared based on the average percentage probability of misclassification and its standard error. The performance of different hierarchical clustering methods varied with distance measures used and it was found that squared Euclidean performed best among the five distances followed by city block distance in majority of cases. Among the five methods, the Ward’s method performed best with least average percentage probability of misclassification followed by non-hierarchical k-means method irrespective of the sample size. Among the different distance measures used under hierarchical clustering methods, the squared Euclidean distance showed least average percentage probability of misclassification followed by city block distance.

πPS Sampling Scheme Through Grouping

Abstract: A πPS sampling scheme is developed by combining Stevens and Midzuno-Sen Sampling schemes. The restriction on original probabilities is less severe in the proposed scheme than that in Stevens and Midzuno-Sen schemes. The performance of the scheme is satisfactory.

Comparative study of nonequilibrium vis-a-vis equilibrium Schaefer model

Abstract: Schaefer model is extensively used for efficient fishery management. Generally, due to mathematical convenience, the assumption is made that the fish population is in equilibrium. In this paper, the procedure for fitting a nonequilibrium Schaefer model is described. Comparative performance of the equilibrium vis-a-vis nonequilibrium version is carried out on catch and effort data of Bombay duck (Maharashtra) during 1974-'84. As the results obtained by the two approaches are found to differ markedly, it is concluded that nonequilibrium approach should invariably be adopted in order to capture reality.

Balanced designs for comparing test products with two controls in sensory trials

Abstract: Sensory trials are an integral part of food and nutrition experiments involving agricultural/animal produce to demonstrate some sensory fact. To draw definite conclusion from the study, it is important to eliminate or minimize all sources of error, and recognize and control all factors that may influence or interfere with the result. In addition to various potential sources associated with the preparation of the test products, there may be variability due to measurement or assessment process, order effects, carryover effects, assessor fatigue etc. Sometimes, designs are required which can provide higher precision estimates for the crucial product comparisons, at the cost of the comparisons which are of lesser interest, and will be estimated with lower precision. One situation where there is special interest in a subset of product contrasts arises when control products are included in the trial. A control product provides a calibration standard, which can serve as a basis for comparison of results across studies may be helpful to the panel. Here, a series of treatment vs. control designs for multi-session trials are obtained to deal with such situations.

Bioinformatics in Field of Agriculture: A Review

Abstract: Agriculture represents an inevitable component of our life. Across continents, different kind of cereals and crops occupy role of important food. Domestication and improvements of crops is practiced from thousand years. Bioinformatics is a newly emerging discipline, though making significant practice in every area of science, including agriculture. Bioinformatics including different -omics fields (genomics, transcriptomics, proteomics, metabolomics etc) and metagenomics is making a significant contribution in field of agricultural research. Bioinformatics is making available genomic and detailed information about different crops and agricultural important animals which is ultimately assisting researchers in development of improved varieties, disease diagnostic, pathogen resistance, disease tolerance etc. Bioinformatics is playing a significant role in discoveries and studies in field of agriculture.