Lipids in rice are found predominantly in the aleurone layer of the bran but are also present in the endosperm, cross-linked with starch. These molecules, present in milled rice, seem to influence the viscoelastic properties of starch by forming complexes with the helical structures of amylose, which affects the swelling ability of starch granules. This grain constituents affects also the nutritional value of rice providing calories and the aroma.

The available modelling approach simulates the total lipid content of brown rice as function of air temperature perceived by the crop during the R8  stage of the ripening period (Counce et al., 2009), when the main culm turns to brown (Lanning et al., 2011) .

In particular the lipid concentration is determined using a linear regression on the 95-th percentile of nighttime air temperature values observed during the above mentioned phenological phase.

The general equation developed for Japonica varieties (Lanning et al., 2012) is given below:

Where:

TLC (%) is the total lipid content of brown rice kernel as percentage of grain dry weight (D.W.);

Tn95th (°C) is the 95th percentiles of nighttime air temperature frequencies that occurred during the R8 phase of rice ripening;

ai, bi (unitless) are the coefficients of the equation, specific for medium and long grain Japonica varieties. 

Basically, once a DVS equal to 2.5 is reached, the model for the simulation of HRY begins to receive as input the hourly values of air temperature. Thus, each day, the HRY model populate a list object by using the hourly temperature data included between Sunset and Sunrise hour. These latter are exogenous variables that vary depending on the latitude of the site where simulations are performed. At last, when physiological maturity stage (DVS = 3) is achieved, the values stored in the above mentioned list object are used to calculate the 95-th percentile of nighttime air temperature, which represents the input of  the equation listed above.

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