A method for managing ripening conditions of climacteric fruit, comprising: obtaining levels of environment condition parameters associated with ripening of the climacteric fruit over time at periodic intervals by using an enclosure enclosing the climacteric fruit, via one or more hardware processors, the environment condition parameters comprising CO2 emitted, O2 consumed, Ethylene emitted, temperature and relative humidity measured within the enclosure, wherein the enclosure is integrated with mutually exclusive sensors for periodic and synchronized data logging corresponding to the climacteric fruit; computing, via the one or more hardware processors, a respiration rate of the climacteric fruit based on the levels of the environment condition parameters and Michaelis Menten coefficients, wherein the Michaelis Menten coefficients comprise a Michaelis constant for O2 consumption (%), a Michaelis constant for competitive inhibition of O2 consumption by CO2 (%) and a Michaelis constant for the uncompetitive inhibition of O2 consumption by CO2 (%), wherein the respiration rate is expressed in terms of O2 consumption rate and CO2 production rate, the O2 consumption rate and CO2 production rate varying depending on environment and presence of inhibitors within the enclosure; monitoring, via the one or more hardware processors, a level of Ethylene emitted in the enclosure to determine a climacteric peak of Ethylene for the climacteric fruit, the climacteric peak indicative of complete natural ripening of the climacteric fruit; predicting, by a pre-trained artificial neural network model, optimal ripening condition of the climacteric fruit in real time based on the respiration rate of the climacteric fruit and the climacteric peak of ethylene, via the one or more hardware processors, wherein the optimal ripening conditions comprises a number of days remaining to complete natural ripening of the climacteric fruit, wherein predicting the optimal ripening condition of the climacteric fruit comprises identifying stage of ripening of the climacteric fruit associated with a co-occurrence of the climacteric peak of ethylene emitted and a zero rate of change of the respiration rate; and altering the environment condition parameters within the enclosure, based on the predicted optimal ripening condition, such that ripening kinetics of the climacteric fruit changes and the number of days remaining to complete natural ripening of the climacteric fruit is altered. obtaining levels of environment condition parameters associated with ripening of the climacteric fruit over time at periodic intervals by using an enclosure enclosing the climacteric fruit, via one or more hardware processors, the environment condition parameters comprising CO2 emitted, O2 consumed, Ethylene emitted, temperature and relative humidity measured within the enclosure, wherein the enclosure is integrated with mutually exclusive sensors for periodic and synchronized data logging corresponding to the climacteric fruit; computing, via the one or more hardware processors, a respiration rate of the climacteric fruit based on the levels of the environment condition parameters and Michaelis Menten coefficients, wherein the Michaelis Menten coefficients comprise a Michaelis constant for O2 consumption (%), a Michaelis constant for competitive inhibition of O2 consumption by CO2 (%) and a Michaelis constant for the uncompetitive inhibition of O2 consumption by CO2 (%), wherein the respiration rate is expressed in terms of O2 consumption rate and CO2 production rate, the O2 consumption rate and CO2 production rate varying depending on environment and presence of inhibitors within the enclosure; monitoring, via the one or more hardware processors, a level of Ethylene emitted in the enclosure to determine a climacteric peak of Ethylene for the climacteric fruit, the climacteric peak indicative of complete natural ripening of the climacteric fruit; predicting, by a pre-trained artificial neural network model, optimal ripening condition of the climacteric fruit in real time based on the respiration rate of the climacteric fruit and the climacteric peak of ethylene, via the one or more hardware processors, wherein the optimal ripening conditions comprises a number of days remaining to complete natural ripening of the climacteric fruit, wherein predicting the optimal ripening condition of the climacteric fruit comprises identifying stage of ripening of the climacteric fruit associated with a co-occurrence of the climacteric peak of ethylene emitted and a zero rate of change of the respiration rate; and altering the environment condition parameters within the enclosure, based on the predicted optimal ripening condition, such that ripening kinetics of the climacteric fruit changes and the number of days remaining to complete natural ripening of the climacteric fruit is altered.