Development of local calibrations for the nutritional evaluation of fish meal and meat & bone meal by using near-infrared reflectance spectroscopy

Figures & data

Figure 1. Steps in cross-validation.

Figure 2. Prediction (NIR) vs. true (laboratory), RMSECV, PLS factors (Rank) and correlation coefficient (R²) for the prediction of (a) moisture, (b) CP, (c) EE, (d) Total ash, (e) Ca and (f) P determination in fish meal samples.

Table 1. General and calibration (NIR) statistics for the chemical composition of fish meal.

Nutrients	Sample No.	General statistics (%)			Calibration (NIR) statistics
		Min.–Max.	Mean	SE^a	Rank	RMSECV^b (%)	R^2
Moisture	688	3.40–14.90	7.65	0.088	09	0.387	93.25
CP	944	47.0–70.20	61.21	0.213	13	1.15	91.11
EE	595	4.50–21.50	9.05	0.232	09	0.813	88.45
Total ash	683	12.00–32.65	20.13	0.526	09	1.01	94.10
Ca	338	2.65–10.71	6.00	0.085	11	0.404	91.22
P	140	1.96–5.08	2.57	0.065	08	0.230	75.41

^aSE = Standard error.

^bRMSECV = Root Mean Square Error Cross-Validation; R² = correlation coefficient.

Figure 3. Prediction (NIR) vs. true (laboratory), RMSECV, PLS factors (Rank) and correlation coefficient (R²) for the prediction of (a) moisture, (b) CP, (c) EE, (d) Total ash, (e) Ca and (f) P determination in meat & bone meal samples.

Table 2. General and calibration (NIR) statistics for the chemical composition of meat & bone meal.

Nutrients	Sample no.	General statistics (%)			Calibration (NIR) statistics
		Min.–Max.	Mean	SE^a	Rank	RMSECV^b (%)	R^2
Moisture	618	2.30–10.50	4.90	0.055	08	0.365	90.88
CP	675	34.86–66.18	51.63	0.528	08	1.27	93.81
EE	602	5.98–19.30	11.18	0.088	08	0.617	90.09
Total ash	612	12.02–46.70	28.42	0.812	07	1.32	95.67
Ca	346	2.67–15.06	9.04	0.088	07	0.66	85.84
P	177	2.41–6.52	4.47	0.036	08	0.377	82.23

^aSE = Standard error.

^bRMSECV = Root Mean Square Error Cross-Validation; R² = correlation coefficient.