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.

Identification of Paddy Leaf Disease (Blast and Brown Spot) Detection Algorithm

Abstract: In the field of agriculture, there is need of recognizing as well as classifying diseases from leaf images that are taken from plant. Finding the diseases of paddy leaf by making use of image processing mechanism would reduce the reliance on farmers in order to save the product related to agricultural activity. This research paper is finding and categorizing the disease in paddy leaf with the help of CNN with integration of edge detection mechanism. The proposed work is focusing on the classification of paddy leaf on the basis of the brown spot, bacterial blight, blast disease and sheath rot after spot detection. However, there have been some previous researches to fulfill such objectives but the proposed work used edge detection mechanism to reduce the time consumption as well as space consumption.Leaves of the rice plant have been captured from the field for the normal, brown spot, bacterial blight, blast diseases and sheath rot. During the pre-processing operation RGB images have been converted in HSV images. Image processing is made on the basis of hue and saturation. The portions of binary graphical contents have been captured to split the infected and non-infected portion. A clustering mechanism has been used for segmentation of the infected portion. However, there are several existing researches that have classified diseases with the support of optimized DNN_JOA (Deep Neural Network with Jaya Optimization Algorithm). Time and space consumption are the major issue in those researches. There is need to provide the solution to improve the performance and space consumption thus proposed work is making use of deep neural network with integration of canny edge detection. In this paper, pattern detection using edge based CNN (convolution neural network) algorithm is proposed.

Effect of post harvest treatments and harvesting stage on vase life and flower quality of cut Oriental lily

Abstract: An investigation was carried out to study the effect of post harvest treatments and harvesting stage on vase life and flower quality of cut Oriental lily cv. Avocado. The results showed that highest vase life (15.83 days) and vase solution uptake (49.17 ml) was recorded with sucrose (2%) + 5-SSA (200ppm), whereas maximum flower diameter (15.17 cm) was recorded in vase solution containing sucrose (2%) + 5-SSA (100ppm). Earliest opening of florets (4.42 days) reported under sucrose (2%) + 5-SSA (200ppm). Effect of treatments was found non-significant in respect to opening of florets. Harvesting at green bud stage exhibited extended vase life (14.33 days) and higher vase solution uptake (40.43 ml), whereas maximum flower diameter (14.25 cm) recorded at 75% colour development stage. Based on the results it is concluded that 5-SSA could be an inexpensive and potential chemical for delaying senescence and for extending the keeping quality of cut liliums commercially.

Statistical Measures of Instability in Crop Output

Abstract: Some aspects of methodological issues relating to statistical measures of instability in crop output has been discussed. Several existing techniques for detection and measurement of instability have been reviewed and some additions and modifications suggested. The application of distribution-free tests has been indicated to test the significance of variability in the crop output over space and time. Various procedures have been explained by numerical data on crop output.

A generalized allometric model for determining length-weight relationship

Abstract: Well-known allometric model is critically reviewed for determining the length-weight relationship. Procedure to be followed for applying this model under the assumption of multiplicative as well as additive error is discussed. The possibility of autocorrelations in error term is explored. It has been demonstrated that the usual allometric relationship does not always work satisfactorily. Accordingly, a generalization of this model is studied in detail. As an illustration, this generalized version of allometric model is used to determine the length-weight relationship of some data on the Indian pearl oyster.

Probability of Inadmissible Estimates of Heritability from Full-Sib Analysis Under a General Model of Gene Action

Abstract: Evaluation of probabilities of the heritability (h2) estimates in full-sib analysis falling outside the permissible limits [0,1] was undertaken for several combinations of sire/dam numbers, h2 and proportions of dominance and additive × additive epistatic variances, assuming two full-sibs per mating and the dominance related epistasis as negligible. In the light of the results use of sire component and sire-dam combination has been recommended in the estimation of heritability of lowly and highly heritable traits respectively.