Brown leaf spot disease and fertilizer interaction in irrigated rice growing on different soil types
Studies have been undertaken in a 1000 ha area of irrigated rice (Oryzica sativa) at Caroni (1975) Limited to determine the effect of the fertilizer programme on the incidence of important diseases. Over a period of three years higher levels of brown leaf spot (Cochliobolus miyabeanus) on rice varieties Oryzica 1 and Oryzica 5 on three different soil types were associated with increasing levels of leaf P, from a low of 0.149% of dry matter (DM) to a high of 0.396% DM. On the Washington silty clay loam series (Inceptisol) brown leaf spot incidence was lowest when leaf P was between 0.135% and 0.149% of DM. However, disease incidence was higher when leaf P levels fell to 0.133% of DM or rose above 0.149%, under conditions where N was more than adequate. The moderate levels of the disease experienced over the period had no effect on yield, as grain infection was minimal. The results support the conclusion that the incidence of brown leaf spot on irrigated rice at Caroni is influenced by sub-optimal levels paticularly of P. Careful monitoring and managememt of P nutrition is seen as an important part in the overall strategy for controlling the disease.
Image processing based rice plant leaves diseases in Thanjavur, Tamilnadu
India is a highly populated agricultural country which has land area of 60.3% for agriculture purpose. The production of rice plant is decreased up to 20–30% because of various diseases. The most frequent diseases occurred in paddy leaves are leaf blast, leaf blight, false smut, brown spot and leaf streak. This paper mainly considers a method to detect the leaf diseases automatically using image processing techniques. To determine these diseases, the proposed methodology involves image Acquisition, image pre-processing, segmentation and classification of paddy leaf disease. In this proposed system, the features are extracted using hybrid method of discrete wavelet transform, scale invariant feature transform and gray scale co-occurrence matrix approach. Finally, the extracted features are given to various classifiers such as K nearest neighborhood neural network, back propagation neural network, Naïve Bayesian and multiclass SVM to categorize disease and non-disease plants. Many classification techniques are examined to classify the leaf disease. In experimental result, the proposed work is implemented in MATLAB software and performance of this work is measured in terms of accuracy. It is observed that multi class SVM provides the better accuracy of 98.63% when compared to other classifiers.
Modelling of Mooney viscosity relaxation in natural rubber
Abstract Better assessment of natural rubber (NR) quality and processability, through the identification of new attributes, is still a major challenge. With this scope, 12 model samples of natural polyisoprene and two of synthetic polyisoprene were characterized in terms of Mooney torque relaxation, using the standardized ISO289 method (ML(1+4)100, explained later in the Section 1 ). The main purpose of this study was to identify a model that gave a better fit for the experimental decay of Mooney torque over time (ML(t)=f(t)) than the usual power law model used before (Y=at−b, [G.M. Bristow, A.G. Sears, The use of novel parameters in the assessment of natural rubber processability, NR Technol. 18 (1987); H.G. Burhin, W. Spreutels, J.M. Campbell, MV2000 Mooney viscometer: Mooney relaxation measurements on raw polymers and compounded rubber stocks, Kautsch. Gummi Kunstst. 43 (1990) 431]). The results showed that a generalized Maxwell model, and the Wu–Abbott empirical model ( Y = 1 − a Ln ( t ) − ( b t / ( c + t ) ) ) [T. Wu, J.A. Abbott, Firmness and force relaxation characteristics of tomatoes stored intact or as slices, Postharvest Biol. Technol. 24 (2002) 59–68], recently used for describing stress relaxation of tomato flesh, allowed a better description of the relaxation curve for the samples studied than the power law or stretched exponential traditionally used. Moreover, the total relaxation time (τm) given by the generalized Maxwell model showed good correlation with the total gel content of the samples studied.