Dr.T.Geetha Journal of Engineering Research and Application www.ijera.com ISSN : 2248-9622, Vol. 8, Issue 8 (Part -II) Aug 2018, pp 07-10 www.ijera.com DOI: 10.9790/9622-0808020710 7 | Page Fuzzy Logic in Growing Stages of Rice Plant Dr.T.Geetha **And S.Anitha Raj* **Department of Mathemathcs, K.N.Govt Arts College for Women (Autonoums),Thanjavur,Tamilnadu, India. *Research Scholar Department of mathematics, K.N.Govt Arts College for Women(Autonoums),Thanjavur,Tamilnadu, . Corresponding Author: Dr.T.Geetha ABSTRACT This paper deals with the growing stages of the Rice plant. Rice is the most important cereal food crop of the world. It is the staple food for more than half of the world‟s population. Rice is the one of the oldest cultivated crop in china and India for several thousand years .The world cereals has been derived from „ceres‟, name of a Roman Goddess, means „Giver of Grains‟. Most of the rice area lies between stages equator and 40°N. In this paper we described the growing stages with fuzzy logic. Fuzzy ideas and Fuzzy logic are so often utilized in our routine life that nobody even pays attention to them. Fuzzy logic in the narrow sense is symbolic logic with a comparative notion of truth developed fully in the spirit of classical logic. Key Words: Fuzzy Logic, Fuzzy Set, Membership Function, Fuzzy inference system. --------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: 09-08-2018 Date of acceptance: 24-08-2018 -------------------------------------------------------------------------------------------------------------------------------------- I. INTRODUCTION: Fuzzy logic is a method to solve problem in expect system which can be viewed as an extension of the classical set. In sharp contrast to the idealized world of mathematics, our perception of the real world is pervaded by concepts which do not have sharply defined boundaries e.g: tall, fat, many, most, slowly, old, familiar, relevant much larger then, kind etc. A key assumption in fuzzy logic is that the denotation of such concepts one fuzzy sets, that is, classes of objects in which the transition from membership to non membership is gradual rather than abrupt‟(zadeh 1990:99).In cereal food crops Rice is the one of the edible starchy grain and also it the staple food for the world. The family of the Rice is the poaceae and its scientific name is oryza sativa. The crop plant which belong to the family poaceae and are grown for their edible starchy grains / seed called caryopsis (seed coat + pericarp are fused or united) are called as cereals. The word cereals has been derived from „Ceres‟, name of a Roman Goddess, means „Giver of Grains‟. It grows from the tropics to subtropical and warm temperature countries up to 40°S and 50°N of the equator. Highest productivity was recorded between 30° and 45° N of the equator. India, China and Egypt lies between 21° to 30° N. The average yield ranges from 2.0 to 5.7 t ha-¹. The countries near the equator show an average yield of 0.8 to 1.4 t ha-¹. [1] through that south India was the place where cultivated rice is originated [1] suggested that India and Burma should be the origin of cultivated crop. II. FUZZY LOGIC: The term fuzzy logic emerged in the development of the theory of fuzzy set by lotfti zadeh (1965). Fuzzy logic is a super set of Boolean logic that handles the concepts of partial truth, which is truth values between “completely true and completely false”. Fuzzy logic is a form of multi valued logic derived from fuzzy set theory. Fuzzy logic is determined either Yes or No and then fuzzy number is between 0 to 1. For the crisp set it, Characteristic function assigned a value of 1 or 0 to each value 1 indicate that corresponding value belong to the set 0 indicate that corresponding value do not belong to the set. The value between 0 and 1 for corresponding values belong to the set in a certain degree from low, medium to high. In process modeling and control system that are ill defined and with uncertainties can be modeled with fuzzy inference system employing fuzzy ‟ If- then‟ rules to quantify human knowledge and resuming processes without employing précised quantitative analyses the fuzzy inference system should include the following functional blocks. Fig : 1.Fuzzy inference systems RESEARCH ARTICLE OPEN ACCESS