7 resultados para crop losses

em Cochin University of Science


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Department of Atmospheric Sciences, Cochin University of Science and Technology

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Dept. of Marine Biology, Microbiology and Biochemistry,CUSAT

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In the present investigation, the impacts of the variability of the climatic parameters on the yields of major crops grown in the State are analyzed. In particular, the effects of rainfall variability on the water balances of the different regions in the State have been studied. Through this analysis the drought climatology of the region has been studied along with an overview of the climatic shifts involved in individual years. The relationship between weather parameters and crop yields over the State has been analyzed with case studies of two crops- coconut and paddy. Crop-weather models for forecasting coconut and paddy yields have been developed, which could be used for planning purposes

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Usually, under rainfed conditions the growing period exists in the humid months. Hence, for agricultural planning knowledge about the variabilities of the duration of the humid seasons are very much needed. The crucial problem affecting agriculture is the persistency in receiving a specific amount of rainfall during a short period. Agricultural operations and decision making are highly dependent on the probability of receiving given amounts of rainfall; such periods should match the water requirements of different phenological phases of the crops. While prolonged dry periods during sensitive phases are detrimental to their growth and lower the yields, excess of rainfall causes soil erosion and loss of soil nutrients. These factors point to the importance of evaluation of wet and dry spells. In this study the weekly rainfall data have been analysed to estimate the probability of wet and dry periods at all selected stations of each agroclimatic zone and the crop growth potentials of the growing seasons have been analysed. The thesis consists of six Chapters.

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Aquaculture is a global industry providing food and employment thereby contributing to the economy. For the sustenance of aquaculture, disease management is a major requirement. Among the bacterial pathogens Vibrio harveyi remains to be the major one especially in shrimp culture systems. Rapid and mass mortality of shrimp larvae due to Vibrio harveyi infection is well known, and the pathogen causes serious economic losses in grow out systems as well. It suggests that a well defined management strategy has to be built up to protect the crop from Vibrio harveyi infection in aquaculture systems. Antibiotics have been the choice for quite some times which led to residues in meat and development of multidrug resistant bacteria which invited ban on their application. In this context several alternate options have been thought off such as probiotics, immunostimulants and vaccines. Phage therapy is yet another option. Phages being natural parasites of bacteria and are abundant in aquatic environments their application to control bacterial pathogens in aquaculture has commendable potential in lieu of antibiotics. For that matter the therapeutic effect of phages has been proven in several antibiotic resistant pathogens inclusive of Vibrio harveyi.

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The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production.This paper describes the application of wireless sensor network for crop monitoring in the paddy fields of kuttand, a region of Kerala, the southern state of India.

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Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.