Table 5.

Model performance parameters for predicting above-ground biomass using different vegetation indices (VIs) and raw reflectance bands for the studies conducted in the 2021 and 2022 growing seasons (model equations provided in Supplementary Table 2 ).

Vis	R2	AICc	BIC	R2cv	RMSEcv
MSAVI	0.87	1896.01	1907.75	0.84	240.64
OSAVI	0.87	1895.28	1907.01	0.84	243.22
RVI	0.86	1904.01	1915.75	0.84	246.96
SAVI	0.86	1909.57	1921.31	0.83	251.34
EVI	0.84	1924.82	1936.56	0.82	260.19
EVI2	0.84	1924.57	1936.30	0.82	260.26
WDRVI	0.86	1906.92	1918.66	0.81	263.85
NIR	0.82	1910.56	1922.24	0.79	267.15
NDVI	0.85	1917.75	1929.48	0.79	278.17
NDRE	0.85	1915.79	1927.53	0.79	280.39
VARI	0.80	1958.09	1969.83	0.78	284.61
RECI	0.84	1925.15	1936.89	0.78	286.98
GRVI	0.80	1962.05	1973.78	0.77	290.94
SCCCI	0.84	1928.49	1940.23	0.77	293.92
NIR/G	0.87	1896.81	1908.55	0.76	295.95
RE/R	0.82	1939.01	1950.75	0.76	300.85
RED	0.82	1903.43	1915.11	0.70	303.97
GNDVI	0.86	1910.01	1921.75	0.75	305.15
TCARI	0.82	1942.01	1953.75	0.70	330.58
TCARI/OSAVI	0.82	1944.09	1955.83	0.70	333.46
RGBVI	0.78	1971.23	1982.97	0.69	339.64
BLUE	0.78	1935.68	1947.36	0.62	344.66
REDEDGE	0.77	1943.90	1955.58	0.61	348.08
GREEN	0.78	1938.76	1950.44	0.56	362.22
ExG	0.69	2022.66	2034.39	0.56	405.25

R², AICc, and BIC represent the generalized coefficient of determination, Akaike Information Criterion and Bayesian Information Criterion values, respectively, for the training data (N = 147). R²cv and RMSEcv represent the coefficient of determination and root mean sum square error, respectively, for cross-validation (N = 100).