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Because of the mechanical properties of aluminium (Al), an accurate prediction of its properties has been challenging. Researchers are seeking reliable models for predicting the mechanical strength of Al alloys owing to the continuous emergence of new Al alloys and their applications. There has been widespread use of empirical and statistical models for the prediction of different mechanical properties of Al and Al alloy, such as linear and nonlinear regression. Nevertheless, the development of these models requires laborious experimental work, and they may not produce accurate results depending on the relationship between the Al properties, mix of other compositions and curing conditions.

Numerous machine learning (ML) models have been proposed as alternative approaches for predicting the strengths of Al and its alloys. The hardness of Al alloys has been predicted by implementing various ML algorithms, such as linear regression, ridge regression, lasso regression and artificial neural network (ANN). This investigation critically analysed and discussed the application and performance of models generated by linear regression, ridge regression, lasso regression and ANN algorithms using different mechanical properties as training parameters.

Considering the definition of the problem, linear regression has been found to be the most suitable algorithm in predicting the hardness values of AA7XXX alloys as the model generated by it best fits the data set.

The work presented in this paper is original and not submitted anywhere else.

The paper aims to critically review the literature based on the factors identified by the authors to discuss and provide direction for future research. The purpose of this study is to identify and analyze the factors responsible for affecting consumers’ perceptions and purchasing attitudes toward organic food products.

The literature review follows the review methodology elaborating on key factors identified which affect the consumer’s perception and attitude toward organic farming and products. A total of 50 articles are downloaded from different sources such as Google Scholar and Scopus and later the articles were finalized based on core areas and specializations.

The findings reveal that the behavioral aspect plays a crucial role in the adoption of organic products by consumers; also various factors such as customer perspective, demand and supply, health aspect, cost-effectiveness, standard and reliability are responsible in endorsing organic products. The authors also reveal that among the factors mentioned, the lack of a supply chain market for organic products is the prime concern for the non-availability of products.

The lack of effective distribution and promotion system affects the availability of organic food products.

The paper provides a comprehensive review of organic food in terms of highlighting the factors affecting the perception and purchasing attitude of consumers toward organic food products consumption. Also, the present review study gives an idea of organizing the literature on the organic food based on factors influencing the customer responses.