In addition to being served as a fresh vegetable, tomato is also consumed in the form of various processed products, such as paste, juice, sauce, puree and ketchup. Generally, in processing these products, different by-products including peels, seeds and pulps are produced. The rational disposal of Tomato waste represents not only a resource problem but also an environmental and economic one for the Tomato Processing Industry. Tomato Processing By-Products: Sustainable Applications indicates the alternative sustainable solutions for the recovery of tomato processing by-products as a source for animal feed and valuable components as well as their possible approaches for value-added utilization in energy, environmental and agricultural applications. Aimed at agricultural or food engineers who work in the Tomato processing industry and are seeking to improve their by-products management by actively utilizing them in effective applications. - Includes tomato processing by-products, their quantification and classification - Approaches tomato waste for animal feeding - Brings successful case study of tomato processing by-products valorization

Extract: This study formulates a dynamic econometric model of the U.S. processing tomato industry. The behavioral elements of the model consist of processed product demand equations facing processors, processor market allocation equations, raw product demand equations facing growers, and grower supply equations. The processed product demand and market allocation equations involve a block of five sets of simultaneously determined equations - one set for each of the five major commodity forms. The California processor raw product demand and grower supply equations form another block of simultaneous equations. The Midwest and East grower price and acreage equations are sequentially linked to California adjustments through a price relationship. The estimates of supply and demand equations, which are the basis for the model, are all consistent with theoretical expectations; and the estimates of equation coefficients are generally within acceptable bounds of statistical significance. Altogether, the model consists of 56 endogenous and 14 exogenous variables.