Mulched type

Regression fitting

Mathematical model

Fitting degree R²

Un-mulched

Linear regression

y = 8.592t + 100.769

0.986

Quadratic polynomial

y = 0.025t² + 5.619t + 156.012

0.997

Powers

y = 105.453t^0.437

0.835

Thickness 15 cm

Linear regression

y = 2.663t + 41.480

0.984

Quadratic polynomial

y = 0.004t² + 2.173t + 50.583

0.986

Powers

y = 42.152t^0.387

0.737

Particle 30 - 50 mm

Linear regression

y = 2.184t + 143.667

0.987

Quadratic polynomial

y = −0.006t² + 2.877t + 130.768

0.995

Powers

y = 108.127t0.241

0.851