| Livestock Research for Rural Development 22 (2) 2010 | Guide for preparation of papers | LRRD News | Citation of this paper |
Livestock production is an integral part of the farming system in Ethiopia. Ruminants in Ethiopia feed mainly on poor-quality plant material, such as crop residues. Crop residues provide large amount of dry matter that can back up the feed shortage, natural pasture, in the dry season of a year. 45 to 131 crop residue samples from crop types were collected and analyzed for the chemical entities (dry matter, ash, crude protein, neutral detergent fiber, acid detergent fiber, lignin) and in vitro dry matter digestibility. NIRS was evaluated by the coefficient of determination in calibration (R2), standard error of calibration (SEC), and standard error of cross validation (SECV).
The results showed NIRS is a method of choice for prediction of chemical composition including in vitro digestibility of crop residues.
Keywords: Chemical composition, crop residue, dry season feed, NIRS, nutritive value
A wide variety of arable crops is grown on subsistence farm holdings. Many of these crops have residues which can form an important source of livestock feed, following the harvesting of grain. Livestock in mixed crop-livestock farming systems two to three months into a dry season feed on cereal straws, stubble or other leftovers such as maize stover. The potential and abundance of crop residues that could be used for livestock feeding in Ethiopia in most cases, drown from grain yield, using multiplier (FAO 1987, Nordbloom 1988, Kossila 1988) is 13.7 million ton (13.6 million ton in the rural area and 136 thousands ton in urban areas) from cereals having CP value ranging from 3.1 - 6.7% with digestibility level about 40.7 - 54.1% and 1.32 million ton (1.31 million ton in the rural area and 6 thousands ton in urban areas) from pulses having CP value ranging from 5.7 - 14% with digestibility level about 34.4 - 52.3%. They are suited for all classes of livestock in the country according to their nutritional characteristics.
Techniques of feed evaluation has been modified and refined since the mid 1980s when Weende method was proposed. Since then various chemical, biological and physical methods have been proposed and applied for feed resource characterization. Near infrared spectroscopy (NIRS) is one of the recent techniques being applied for feed resource characterization. Boever et al 1997 have assessed application of NIRS for predicting in situ degradability feeds in Belgium and reported good prediction potential in favor of NIRS. The predictive accuracy of NIRS in general relies heavily upon obtaining a calibration set which represents the variation in the main population, accurate laboratory analyses and the application of the best mathematical procedures (Park et al 1998). Although the reliability of NIRS has been investigated well for temperate feeds little work has been done for tropical feeds. Moreover, the variation in ecological set up, the biological diversity in feed resources in the country requires quite robust and cost effective method for characterization. This research result meant to fill these gaps with an objective of assessing the potential of this technique in characterizing nutritive value and predicting the chemical composition of crop residues: study reliability of NIRS technique for characterizing and predicting nutritional status of crop residues.
Major crop residues (tef straw, wheat straw, barley straw, maize stover, sorghum stover, pea straw, chick pea straw, lentil straw, bean straw, cowpea straw) were considered.
The procedures for determination of parameters undertaken are chemical entities (DM, Ash, CP, NDF, ADF and lignin) and bio-availability (IVOMD). Chemical analysis (DM, Ash, and CP) determined conventionally using procedures of AOAC (1990) and determination of NDF, ADF, and Lignin using procedure (Goering and Van Soest 1970). In vitro digestibility determined using the two-stage rumen fluid–pepsin technique (Tilley and Terry 1963).
Samples of the crop residues were taken for NIRS analysis of each feed types that are analyzed using conventional analysis. NIRS spectroscopy performed on 3 g of ground sample (1mm sieve) using Foss NIRS 5000 in the 1108-2492 ranges with an 8 nm step. Before scanning the samples pre-dried at 60oC overnight in an oven to standardize moisture conditions. The spectra of each sample taken by scanning (Win Scan version 1.5, 2000, Iintrasoft international, L.L.C). Mathematical and statistical treatments of the NIRS spectra were first treated using ISI. Average spectra for each sample were obtained from the scanning. Calibration equations were calculated by step-wise multiple linear regressions on the samples and 30 samples from each type of crop residue used for validation purposes. The samples for calibrations and validation were selected systematically to cover the range and to fairly represent the population for each feed they are drawn from.
The correlation of predicted and conventionally determined values used to assess the reliability of NIRS and residual behavior predicted. Regression analysis of the predicted values and conventionally determined values also undertaken to assess the precision of NIRS.
The feed samples used for calibration and validation varied in their chemical entities (DM, Ash, CP, NDF, ADF and lignin) and bio-availability (IVOMD) as is seen in Table. The mean and range of each entity were seen being similar to previously observed values (Seyoum et al 2007). There were significant differences among the samples for all entities of the feed types which suggest the presence of sufficient variation among the samples of the feed types to develop NIRS equation separately.
|
Table 1. Performance of NIRS calibration |
|||||||
|
Feed type |
Parameters/traits |
N |
Range |
R2 |
SEC |
1-VR |
SECV |
|
Barley straw |
DM |
131 |
87.4 – 93.6 |
0.86 |
0.38 |
0.82 |
0.43 |
|
Ash |
130 |
3.01 – 11.8 |
0.74 |
0.75 |
0.66 |
0.85 |
|
|
CP |
130 |
1.00 – 3.40 |
0.90 |
0.19 |
0.86 |
0.23 |
|
|
NDF |
131 |
65.8 – 75.6 |
0.66 |
0.96 |
0.56 |
1.09 |
|
|
ADF |
131 |
39.9 – 45.3 |
0.64 |
0.88 |
0.43 |
0.94 |
|
|
Lignin |
131 |
3.33 – 8.93 |
0.63 |
0.92 |
0.55 |
0.96 |
|
|
In vitro (DOMD) |
131 |
51.5 – 58.1 |
0.72 |
1.06 |
0.22 |
1.09 |
|
|
Bean straw |
DM |
78 |
91.9 – 92.2 |
0.90 |
0.02 |
0.77 |
0.02 |
|
Ash |
74 |
8.97 – 9.66 |
0.96 |
0.02 |
0.77 |
0.06 |
|
|
CP |
75 |
7.47 – 7.81 |
0.95 |
0.01 |
0.71 |
0.03 |
|
|
NDF |
74 |
61.6 – 63.4 |
0.95 |
0.06 |
0.80 |
0.13 |
|
|
ADF |
78 |
45.0 – 45.9 |
0.96 |
0.03 |
0.54 |
0.11 |
|
|
Lignin |
76 |
8.41 – 8.61 |
0.76 |
0.02 |
0.41 |
0.03 |
|
|
In vitro (DOMD) |
77 |
51.3 – 52.7 |
0.94 |
0.05 |
0.78 |
0.10 |
|
|
Chickpea straw |
DM |
79 |
91.5 – 92.0 |
0.87 |
0.03 |
0.79 |
0.03 |
|
Ash |
79 |
8.67 – 9.00 |
0.83 |
0.02 |
0.46 |
0.04 |
|
|
CP |
84 |
6.19 – 6.37 |
0.80 |
0.02 |
0.35 |
0.02 |
|
|
NDF |
79 |
55.1 – 57.5 |
0.98 |
0.06 |
0.93 |
0.11 |
|
|
ADF |
77 |
40.5 – 41.4 |
0.86 |
0.06 |
0.62 |
0.10 |
|
|
Lignin |
75 |
8.04 – 8.52 |
0.98 |
0.01 |
0.96 |
0.02 |
|
|
In vitro (DOMD) |
80 |
56.0 – 58.4 |
0.92 |
0.12 |
0.80 |
0.18 |
|
|
Cowpea straw |
DM |
47 |
88.5 – 95.9 |
0.99 |
0.03 |
0.99 |
0.04 |
|
Ash |
51 |
9.49 – 19.4 |
0.72 |
1.35 |
0.17 |
1.55 |
|
|
CP |
51 |
7.45 – 28.3 |
0.84 |
2.31 |
0.34 |
2.88 |
|
|
NDF |
45 |
32.0 – 52.5 |
0.99 |
0.17 |
0.99 |
0.21 |
|
|
ADF |
47 |
17.8 – 23.5 |
0.95 |
0.21 |
0.94 |
0.23 |
|
|
Lignin |
50 |
2.97 – 3.95 |
0.99 |
0.01 |
0.99 |
0.01 |
|
|
In vitro (DOMD) |
51 |
60.6 – 60.7 |
0.65 |
0.02 |
0.97 |
0.02 |
|
|
Lentil straw |
DM |
67 |
86.2 – 98.5 |
0.68 |
2.05 |
0.01 |
2.05 |
|
Ash |
67 |
2.89 – 13.6 |
0.61 |
1.79 |
0.02 |
1.81 |
|
|
CP |
67 |
5.08 – 11.0 |
0.64 |
0.99 |
0.01 |
1.00 |
|
|
NDF |
67 |
35.5 – 79.6 |
0.67 |
7.33 |
0.01 |
7.46 |
|
|
ADF |
67 |
12.5 – 68.6 |
0.63 |
9.34 |
0.01 |
9.38 |
|
|
Lignin |
67 |
4.41 – 12.6 |
0.66 |
1.37 |
0.02 |
1.39 |
|
|
In vitro(DOMD) |
67 |
39.2 – 70.2 |
0.65 |
5.10 |
0.02 |
5.11 |
|
|
Maize stover |
DM |
72 |
86.0 – 96.6 |
0.92 |
0.51 |
0.89 |
0.58 |
|
Ash |
71 |
2.89 – 14.1 |
0.84 |
0.91 |
0.81 |
1.01 |
|
|
CP |
72 |
1.11 – 4.73 |
0.71 |
0.42 |
0.41 |
0.46 |
|
|
NDF |
72 |
65.7 – 91.5 |
0.86 |
1.61 |
0.65 |
2.53 |
|
|
ADF |
72 |
40.2 – 59.1 |
0.76 |
2.09 |
0.43 |
2.38 |
|
|
Lignin |
72 |
0.85 – 11.0 |
0.60 |
1.72 |
0.72 |
1.77 |
|
|
In vitro(DOMD) |
72 |
44.3 – 66.8 |
0.76 |
2.50 |
0.41 |
2.88 |
|
|
Pea straw |
DM |
106 |
92.3 – 92.7 |
0.85 |
0.03 |
0.75 |
0.04 |
|
Ash |
111 |
7.44 – 8.36 |
0.95 |
0.04 |
0.80 |
0.07 |
|
|
CP |
102 |
6.82 – 7.41 |
0.96 |
0.02 |
0.87 |
0.04 |
|
|
NDF |
106 |
64.4 – 66.4 |
0.74 |
0.17 |
0.34 |
0.28 |
|
|
ADF |
107 |
54.3 – 55.1 |
0.61 |
0.08 |
0.24 |
0.12 |
|
|
Lignin |
105 |
10.0 – 10.4 |
0.88 |
0.02 |
0.59 |
0.04 |
|
|
In vitro (DOMD) |
109 |
53.8 – 54.6 |
0.93 |
0.04 |
0.81 |
0.06 |
|
|
Sorghum stover |
DM |
117 |
84.4 – 96.0 |
0.92 |
0.55 |
0.89 |
0.65 |
|
Ash |
118 |
2.73 – 11.6 |
0.71 |
0.79 |
0.58 |
0.95 |
|
|
CP |
118 |
1.04 - 7.81 |
0.61 |
0.85 |
0.49 |
0.97 |
|
|
NDF |
118 |
57.3 – 83.2 |
0.46 |
3.17 |
0.43 |
3.25 |
|
|
ADF |
118 |
39.0 – 60.4 |
0.57 |
2.34 |
0.44 |
2.68 |
|
|
Lignin |
117 |
4.04 – 9.32 |
0.47 |
0.64 |
0.35 |
0.71 |
|
|
In vitro (DOMD) |
118 |
39.2 – 66.6 |
0.23 |
4.00 |
0.12 |
4.28 |
|
|
Tef straw |
DM |
130 |
88.5 – 95.0 |
0.67 |
0.62 |
0.54 |
0.73 |
|
Ash |
130 |
4.56 – 10.8 |
0.71 |
0.87 |
0.12 |
0.98 |
|
|
CP |
130 |
0.41 – 6.95 |
0.66 |
0.64 |
0.57 |
0.71 |
|
|
NDF |
130 |
70.0 – 86.0 |
0.70 |
1.93 |
0.40 |
2.05 |
|
|
ADF |
130 |
35.1 – 54.3 |
0.64 |
2.97 |
0.06 |
3.12 |
|
|
Lignin |
130 |
2.15 – 9.42 |
0.74 |
1.17 |
0.05 |
1.20 |
|
|
In vitro (DOMD) |
130 |
45.4 – 61.3 |
0.61 |
2.42 |
0.04 |
2.59 |
|
|
Wheat straw |
DM |
95 |
89.5 – 94.1 |
0.86 |
0.28 |
0.81 |
0.33 |
|
Ash |
96 |
6.20 – 17.4 |
0.67 |
1.06 |
0.57 |
1.23 |
|
|
CP |
93 |
0.94 - 6.60 |
0.79 |
0.62 |
0.71 |
0.73 |
|
|
NDF |
96 |
40.5 – 86.2 |
0.89 |
3.09 |
0.85 |
3.60 |
|
|
ADF |
88 |
26.8 – 69.0 |
0.92 |
2.01 |
0.88 |
2.39 |
|
|
Lignin |
91 |
2.37 – 10.4 |
0.78 |
0.63 |
0.72 |
0.71 |
|
|
In vitro (DOMD) |
93 |
42.2 – 77.0 |
0.83 |
2.37 |
0.78 |
2.72 |
|
|
DM = Dry matter, CP = Crude protein, NDF = Neutral detergent fiber, ADF = Acid detergent fiber, DOMD = Digestible organic matter in the dry matter, SEC = standard errors of calibration, 1-VR = coefficient of determination of cross validation, SECV = standard errors of cross-validation |
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The table shows the calibration and external validation statistics for the various classes of feed resources and their traits considered. The calibration equations for DM, Ash, CP, NDF, ADF, Lignin and in vitro show relatively high determination coefficient, and low standard errors of calibration (SEC) and standard errors of cross-validation (SECV)and hence, these traits could be predicted with good precision. Moreover, the predicted means for each trait were similar to the means based on conventional chemical analyses. Higher SEC value was recorded for the feed types of each class may be due to the broader range of variation for the trait.
SECV is a basic statistics to measure accuracy for a calibration equation (Shenk and Westerhaus 1993). Accordingly, the calibration error should be comparable to the sampling error and this value is similar to SEP (standard error of performance). Thus, the best performance in calibration equations for individual traits corresponded to those traits for which the variability in the calibration set was wider (see table), indicating that successful calibration equations using NIRS depend on the variability of constituents under investigation.
The result indicated NIRS is a method of choice for prediction of chemical composition including in vitro digestibility of organic matter in the dry matter of crop residues. Hence, the technique is noted to be one of the more multifaceted robust applications to estimate chemical entity and parameters like digestibility of organic matter in the dry matter which is usually estimated by bioassays.
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Received 23 November 2009; Accepted 21 December 2009; Published 7 February 2010