English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Rice when harvested normally has a high moisture content of 20–25% which requires immediate drying, reducing its mass loss and preventing it to spoil. This situation is more crucial with the areas under humid tropical conditions, where moisture and temperature mainly play an important role in deteriorating the quality of rough rice. Keeping the importance of quality attributes of rough rice, the study was carried out to assess the effects of low-temperature drying and suggest an optimum condition. Response surface methodology (RSM) with a central composite design was employed to study the effects of variables, i.e., temperature (X1), time (X2), and air velocity (X3) on responses, i.e., head rice yield (HRY), hardness, lightness, and cooking time. The experimental data were fitted to the quadratic model, studying the relationship between independent and dependent variables. The results revealed that the HRY, hardness, lightness, and cooking time increased with increasing variables, whereas for HRY, it particularly increased and then decreased. It was observed that temperature had more influence on the quality of rough rice followed by time and velocity. Results for analysis of variance revealed that the quality aspects of rough rice were significantly ()  affected by temperature and time, whereas for velocity, it only significantly affected hardness. The optimal drying conditions predicted by RSM for variables were 25°C, 600 min, and 1 m·s−1, and the optimal predicted HRY, hardness, lightness, and cooking time were 73.93%, 38.28 N, 71.40, and 27.58 min respectively. Acceptable values of R2, Adj R2, and nonsignificance of lack of fit demonstrated that the model applied was adequate and can be used for optimization. The study concluded that the RSM with a central composite design was successfully used to study the dependence of quality aspects of rough rice at low temperature and can be utilized by the rice processing industries.

Mathematical Modelling and Optimisation of Low-Temperature Drying on Quality Aspects of Rough Rice