INTRODUCTION About 80 per cent of the state population is engaged in agriculture and allied activities. Hence, agriculture plays an important role in the social and economic life of people in Manipur, and will continue to do so in the foreseeable future. The gross cropped area is 350,290 ha, which account for 15. 24 per cent of the total land areas. About 65. 93 per cent of the gross cropped area is under rice cultivation. The mean cropping intensity of the state is 145. 66 per cent. The total food grain production in Manipur during 2014–15 was 594. 28 thousand tonnes from an area of 292,950 ha. However, agriculture sector in Manipur is facing the consequences of climate change (Gommes 2006, Jones et al. 2003). Climate change is a reality and an increasing trend in temperature, precipitation and emission of greenhouse gases has been observed in Manipur. Trend analysis of weather variables in Imphal under National Innovations on Climate Resilient Agriculture (NICRA) revealed that the mean annual maximum temperature (1954–2014) has been increasing (0.1 degree C per decade). The mean annual minimum temperature has also increased significantly (0. 3 degree C per decade).Total annual precipitation is expected to increase throughout the state. As evident from the last 30 years’ climate data analysis, precipitation rate in northern parts is expected to increase by ≥19 per cent. Climatic factors like rainfall and extreme temperature, which are beyond the tolerance capacity of a species, may lead to inevitable distribution changes. Evidences show that many plant species shift their geographical habitats to combat regional climatic variation (Cao Juan, 2021) (Chapagain et al., 2009). Many species are unable to acclimatize to the pace of climatic variations. So, these changes may increase the extinction risk. Climate change alters water availability and the resulting water stress may affect crop productivity. Particularly, under rain-fed ecosystems, altered climatic conditions can expose crops to drought like situation. Timely availability of quality seed/planting material of recommended climate-ready crop varieties and irrigation water are two most important requirements for CRA in hill (Moonena et al. 2002) (Feng, Zhaozhong 2019). Market-driven secondary agricultural activities are of prime importance for sustaining the livelihood of the farming community through additional income generation. Various options for secondary agricultural activities include mushroom production, bee-keeping and honey production, primary processing of horticultural crops, enriched vermin composting, etc. The present investigation was carried out with the following objectives: To find out the effects of area, yield and agro-meteorological parameters in determining the production. To find out the effects of area, production, yield and agro-meteorological parameters in determining farmgate price. MATERIAL AND METHODOLOGY A proper methodology is an inevitable and important component of a research study for getting successful research findings. To fulfill the objectives of the present study, a reasonably appropriate methodology has been adopted. In this chapter, the methodology adopted for the present study has been presented under the following heads. 1. Study area and period of study. 2. Sampling design. 3. Collection of data. 4. Analytical technique. Selection of State. Manipur State of INDIA has been purposively selected. Selection of Region. Valley region have been purposively selected. Selection of Districts. Bishnupur district is selected. Collection of data. Purely time series secondary data have been collected regarding area, production, farm prices and productivity of principal crops and agro-meteorological parameters of Manipur State for a period of last 20 years data (1998-2017). Analytical Techniques. The study is based on Regression Analysis following Multiple Linear Regression Model. Regression. The word regression is used to denote estimations of predictions of the averaged value of one variable of a specific of other variable. The estimations is done by means of suitable equations, derived on the basis of available bivariate data. Such an equation is known as a regression equations and its geometrical representation is called a regression curve. In linear regressions (or simple regressions) the relationship between the variables is assumed to be linear. The estimations of y (say, y¢) is obtained from an equations of the form y¢ - ybar = byx(x-xbar) (1) and the estimations of x(say, x¢) from another equation (usually different from the former of the form x¢- xbar = bxy(y-ybar) (2) equations 1 is known as regressions equations of y on x, and equation 2 as regression equations of x on y. the coefficient byx appearing in the regression equations of y on x is known as regression coefficient of y on x. Similarly, bxy is called the regression coefficient of x on y. the geometrical representations of linear regression equations 1 and 2 are known as regression line these line are best fitting straight line obtaining by the method of least square Multiple Linear Regression Model. In order to find out the major agro-meteorological parameters affecting area, production and productivity of principal crops in the study area, a multiple linear regression model is used. The general model of the Multiple Linear Regression is as follows – General linear regression model for ‘k’ explanatory variables (xi's) and one dependent variable, y for sample is given by y = b_o+∑_(i=1 )^k▒b_i x_i +e_i where b_0is the intercept, b_1, b_2……,b_k are partial regression coefficients of the variablesx_1, x_2, ...., x_krespectively and e_iis the residual which is supposed to follow i.i.d. N(0, σ2). By ordinary least square method one can find the values of a, b_1, b_2…,b_k. Significance of the model The significance of the regression model was tested using F statistic. Here the null hypotheses was set as, H0: β = 0 Test statistic Where, Regression sum of squares (RSS) = Error sum of squares (ESS) = RESULT AND DISCUSSION Bishnupur From Table 1 the main results of the study show that in Bishnupur district in the valley region of Manipur state, when production is considered as a dependent variable, it is observed that both area and yield have a significant impact on production in kharif maize (0.997), kharif oilseeds (0.986), kharif rice (0.964), kharif legumes (0.992), rabi legumes (0.996) total maize (0.994), total oilseeds (0.701), total paddy (0.997), total legumes (0.996), this result was in similar with the finding of Lekshmi et al. (2013); Smith et al. (2018), stated that the accounting for fluctuations in agro-meteorological parameter readings into agriculture, helped to get better yield and quality of produce as well as showed that estimates of likely future adaptations were an essential ingredient in impact and vulnerability assessments impacted system to adapt. Both area and temperature have a significant impact on production in the case of rabi legumes, while looking at the dependent variables on the farm, it is observed that both temperature and production have a significant impact on the farm-gate price for Kharif maize (0.756), and only humidity has a significant impact on the farm-gate -Price in the case of Kharif oilseeds (0.683), Rabi oilseeds (0.782), Kharif legumes (0.775), but the area has a significant impact on the producer price in Case of kharif rice (0.909) and temperature has a significant impact on the producer price in the case of legumes Rabi (0.568) as shown in table 3.2. Liming Ye et al. (2012); Zhou and Ismaeel (2020) also stated that climate change was now affecting global agriculture and food production worldwide, whole rice and legumes and understanding the current relationship between agriculture and climate might help interpret how future climate change will affect local crops and also take necessary measures. Also in Table 2 both moisture and production have a significant impact on the farm price in the case of total corn acreage and temperature has a significant Influence on the operating price in the case of all oilseeds. Similar finding was observed by Lathika et al. (2005); Roy et al. (2018); Rosenzweig et al. (2012); Chattopadhyay et al. (2020) showed that overall climate is changing particularly in respect of temperature over the Indian region. Besides, climatic variability leading to extreme events like drought, flood, occurrence heavy rainfall etc results in decreasing the production yield of various crops throughout the country.