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. 2021 Aug 22;10(8):1950. doi: 10.3390/foods10081950

Table 7.

The Penalty analysis and JAR variables (before tasting) for Medium grain brown and Medium grain white rice.

Rice Variable Sensory Test Correlation Coefficient a Level Selection% b Mean c Mean Drop d Penalty e
Medium Grain Brown Aroma Smell −0.11 Too low 22.30 5.65 0.85
JAR 39.57 6.49 0.96 **
Too high 38.13 5.47 1.02
Colour Visual −0.44 Too light 8.63 5.83 1.02
JAR 48.92 6.85 1.84 *
Too dark 42.45 4.85 2.01
Hardness Handling −0.39 Not hard enough 4.32 6.0 0.70
JAR 41.01 6.70 1.34 *
Too hard 54.68 5.32 1.39
Fluffiness Handling 0.12 Too low 33.09 5.61 0.59
JAR 44.60 6.19 0.51
Too much 22.30 5.81 0.39
Stickiness Handling 0.07 Too low 24.46 5.21 1.18
JAR 50.36 6.39 0.95 *
Too much 25.18 5.66 0.73
Medium Grain White Aroma Smell 0.04 Too low 35.97 6.58 0.28
JAR 39.57 6.86 0.21
Too high 24.46 6.74 0.12
Colour Visual 0.05 Too light 14.39 6.50 0.28
JAR 72.66 6.78 0.20
Too dark 12.95 6.67 0.12
Hardness Handling 0.14 Not hard enough 24.46 6.44 0.30
JAR 57.55 6.74 0.26
Too hard 17.99 7.08 −0.34
Fluffiness Handling 0.08 Too low 23.02 6.34 0.62
JAR 54.68 6.96 0.52 **
Too much 22.30 6.55 0.41
Stickiness Handling −0.13 Too low 7.91 6.64 0.36
JAR 37.41 7.0 0.44
Too much 54.68 6.55 0.45

a The impact of JAR variables for Jasmine brown and white rice on the overall liking (Spearman’s correlation coefficient with a significance level α = 0.05). The correlation coefficients (between JAR attributes and overall liking) show how much JAR attributes have impacted (“low” or “high”) on overall liking for rice samples. When the correlation is positive, the “too little” has a bigger impact than the “too much”, and vice-versa for the negative correlations. If correlation is “0” for a JAR attribute, then that attribute would have a strong impact on overall liking [35]. b Selection % is the percentage of consumers who rate the rice as too low, JAR, or too high on a given attribute. c Mean is the mean overall liking (9-point hedonic scale) of consumers who rated a given attribute as too low, JAR, or too high. d Mean drop is the decrease in liking compared to the mean liking of those who rated the attribute as JAR. e Penalty is a weighted difference between means (mean liking of JAR category minus the mean of liking for other two levels (too low and too high) taken together). * p ≤ 0.001, ** p ≤ 0.05.