Abstract:
A study was carried out to determine the relative
market prices for grain sorghum and grain pearl millet based on their relative
nutrient content in comparison with traditional grains. Six different grains
including soybean meal, were obtained from Ports of Canada and were analyzed
for their nutrient contents. The current market prices for the control
grains were obtained from various sources. Prediction equations were developed
to see how clearly they predict current market prices of these grains,
based on selected nutrient content. Similarly several other equations developed
by other workers were compared with these equations. The equation using
three regression variables (net energy for lactation, crude protein, and
phosphorus) was very accurate, obtaining an R2 of 0.9846 and
a P-value of 0.02. When the predicted prices obtained from each of the
methods developed by other researchers were compared with the values obtained
from the test equation, prediction error of variance was the smallest for
the equation developed from this study. The prices obtained from other
equations were significantly different (P< 0.01) from the true market
prices, yet the prices obtained from the test equation were extremely close
to the market prices of the grains. Based on this test equation, sorghum
grain had a predicted value of $123.91 per metric tonne, and pearl millet
had a predicted value of $128.91 per tonne on May 24, 1999.
Background:
Dairy farmers, or any farmer for that matter, want decisions on the
feeding value of alternative grains when formulating rations. The most
frequently asked questions are: a) How much should I pay per tonne? and
b) When is this alternative feed (grain) a good buy? Feed costs represent
50-60 percent of variable costs of production for milk, playing a major
role in determining the profitability of a dairy enterprise. Because grain
sorghum and pearl millet are new to Canada, these are pertinent questions
producers may have before they incorporate these grains in their cattle
rations. Therefore, this trial was designed to provide some guidelines
for producers.
Energy and protein are the two major nutrients required by lactating
dairy cows, so feeds are generally selected based on their relative content
of these nutrients. Animal productivity in turn is affected by diet intake,
nutrient content, digestibility of the feedstuffs and efficiency of utilization
of the absorbed nutrients. The best measure of the quality of any feed
is animal productivity. Often, measuring animal productivity entails lengthy,
expensive research to acquire animal data and interpret the results. Choices
of feed ingredients can be made logically if dollar values are placed on
the nutrients of interest.
Feedstuffs differ in their proportions of energy and protein. Thus the
value of certain grains to dairy farmers varies with the nutrient content
and with the productivity of the cows.
Feed analysis laboratories commonly report energy levels as Net Energy
of Lactation (NEL) and protein as levels of crude protein (CP).
Net energy values are derived from using the acid detergent fibre (ADF)
or the total digestible nutrients (TDN) levels in a series of formulas.
NEL is a good indicator of how much energy from a feed can
be used to produce milk. Protein measurement systems on grains are less
sophisticated. At present the percentage of nitrogen in a sample, multiplied
by 6.25 is used to determine the crude protein content. The CP system is
based on an assumption that all feedstuffs have an equal extent of protein
digestion, with CP being converted to metabolizable or absorbed protein
with equal efficiency in all diets (NRC, 1996;1989).
Agriculture Environmental Renewal Canada (AERC) Inc.1, a
Canadian, bio-agro seed company, has successfully developed forage and
grain hybrids of sorghum and pearl millet in Canada. The forage hybrids
are already released in Canada and grain hybrids are due to be released
in 1999. The sorghum grain was 12.21% CP, 2.05 Mcal/kg NEL,
0.34% Phosphorus, and 0.02% Calcium. Similar values for pearl millet were
11.00% CP, 2.08 Mcal/kg NEL, 0.36% Phosphorus, and 0.03% Calcium
(AERC, 1997/982). Typical corn silage usually contains 7.5 to
9% CP, 1.84 to 2.04 Mcal/kg NEL, 0.29% Phosphorus, and 0.01%
Calcium (NRC5, 1996).
Grain sorghum (milo) is the second most common grain fed to pigs in
the United States. The low-tannin varieties are reported to have feeding
value comparable to corn for growing and finishing pigs (Holden et al.4
, 1984). Pearl millet has an excellent amino acid profile and higher crude
protein content than corn or sorghum. When compared to corn on a weight
basis, pearl millet is 8-60% higher in crude protein, 40% richer in lysine
and methionine, and 30% richer in threonine (Burton et al.3,
1972). These alternative Canadian-developed feed sources have not been
evaluated in terms of their feeding values with traditional feed sources.
The objective of this study was to compare the monetary feed value of these
crops with several domestic grains.
Literature Review:
Work has been underway since 1996 at Kemptville College (University
of Guelph) to determine the feeding value of pearl millet (P.H. Sharpe6
et.al. 1996/97). The challenge now is to determine a price for pearl millet
and sorghum as feed grains. Pearl millet and sorghum grains are not commonly
available on the market in Ontario, and therefore do not have established
prices in the market place.
Steevens and Garrett8 (1994), from the University of Missouri-Columbia,
used cracked corn, 48% soybean meal (SBM), limestone and dicalcium phosphate
to calculate the unit value of NEL, CP, calcium, and phosphorus.
The method used was simultaneous equations. The result of the analysis
depended on the price of corn, SBM, calcium and phosphorus, and the nutrient
content of alternative feedstuffs.
Rodenburg9 (1997) evaluated feedstuffs with Peterson's Equations
using grain corn as the standard energy feed and SBM as the standard protein
feed.
Procedures:
Samples of (approximately 10 kg each) soybean meal (GrowMark 48%), cereal
rye, grain corn (#3 grade Canada East), wheat feed (Canada East), flaxseed
(#1 grade Canada East), barley (#1 grade Canada East), and oats (#2 grade
Canada East) were obtained from Ports of Canada (Prescott, Ontario) (Table
1). AERC Inc. provided grain pearl millet and sorghum grown in Southwestern
Ontario. The in vitro neutral detergent fibre (IVNDF) and in
vitro protein digestibility (IVPD) were determined for 48 and
30 hours, respectively(Ritchie Feeds, Ottawa, Ontario). The grains were
also analyzed using Net Carbohydrate Protein Systems (NCPS) by Agri-Food
Laboratories (Guelph, Ontario) (Table 2).
Regression analysis (SAS, 1996)10 was used to determine a
value for each nutrient in the feeds. Regression analysis requires two
degrees of freedom (one degree when the y-intercept equals zero). For example,
if protein, energy and phosphorus (three variables) are used to value pearl
millet grain, then nutrient analysis from five other grain sources are
needed.
Requiring so many grain samples can prove to be a problem because a
few grains commonly exist in any one area at the same time. Since corn
is competing with barley, for example, as an energy source, it is preferred
in this method to identify grains in the same market (location) at the
same time. It is the relative price (Table 1) of feed grains that is important.
Regressions were run on numerous combinations of nutrients and all six
competing grains. Some of the price data were not local and may cause distortions.
The choices for the best set of nutrients for dairy rations, and the best
choice of grains competing to supply these nutrients are summarized in
Table 3. The combinations of nutrients and grains were evaluated using
R2 values and P-values. The higher the R2 value for
a regression equation, the better fit of data to the equation, with 1.0
being an exact correlation. P-values <0.05 indicates that significant
differences between the predicted values and the observed values this small
would occur less than 5% of the time by chance.
| TABLE #1 Grain
Prices and Source |
| GRAIN |
GRAIN PRICE |
PRICE SOURCE, May 24,1999 |
| CORN #3 Canada East |
$116.82 |
Chatham track, Ontario |
| WHEAT feed Canada East |
$158.16 |
To Bayports, in store, Ontario |
| BARLEY #1 Canada East |
$146.75 |
To Bayports, in store, Ontario |
| OATS #2 Canada East |
$121.41 |
To Bayports, in store, Ontario |
| SOYBEAN MEAL GM 48% |
$228.51 |
From Hamilton, Ontario |
| CEREAL RYE |
$125.00 |
From Delhi, Ontario |
Results and Discussion:
Table #1 shows the price of grains collected and used for comparison
in this study. Table 2 includes the nutrient composition of each grain.
The numerical results in Table 3 depend heavily upon the nutrient composition
of the various grains collected (Table 2 -- nutrient contents will vary
with each grain sample), as well as the price of each grain being used
(Table 1 -- price will vary from day to day and from one location to the
next), and even the set of grains chosen to compete in the regression.
Table #3 summarizes seven combinations of regression variables and feed
grains. The first observation is that feed grain prices do reflect the
value of their nutrient content. Some nutrients are better indicators of
value than others. Equations 2, 5, and 6 have good R2 values
although their P-values were not significant. Equations 1, 3, and 4 showed
significant P-values as well very high R2, but NEl
was not used as a regression variable. Equation 7 provides the best estimated
value for corn (the real corn price in this instance was $116.82/tonne)
with significant P-value and a very high R2.
The best three-variable model, (equation 7, Table 3), included the regression
variables: NEl , CP, and phosphorus, and produced an R-squared
of 0.9846 (P = 0.02).
Using the three methodologies for determining value, the predicted prices
for eight grains are presented in Table #4.
Steevens and Garrett (1994) used simultaneous equations to value NEl
, CP, calcium and phosphorus, but no statistical analysis was reported.
The value of Corn and SBM is the exact market price, which is expected
because their market prices were what the simultaneous equations were based
on. The value of wheat, barley, oats and rye had predicted mrket values
significantly different from the market price. Pearl millet had a predicted
value of $107.80 per tonne and sorghum had a predicted value of $110.45
per tonne.
Rodenburg (1997) used Peterson's Equations with corn as the standard
energy feed and SBM as the standard protein feed. No statistical analysis
was reported. Corn and SBM again had predicted values the same as market
price, as would be expected. Wheat, barley, oats and rye had closer predicted
price values than did Steevens & Garrett. Pearl millet had a predicted
value of $124.00 per tonne and sorghum had a predicted value of $126.00
per tonne (Table 4).
The predicted values were very close to market price. Statistical analysis
shows very high correlation and significance. Pearl millet had a predicted
value of $128.91 per tonne and grain sorghum had a predicted value of $123.91
per tonne (Table 4).
When predicted prices obtained from the three calculation methods were
compared, the predicted error of variance was smallest for regression equation
#7. The predicted prices from other methods were significantly different
from the observed market price.
It should be noted that corn is not the yardstick when using regression
analysis as it was in previous studies. Regression equation #7 is based
on competition between corn, wheat, barley, oats, SBM and rye.
The result that pearl millet and sorghum have higher values than corn
contradicts Steevens & Garrett (1994). Also, the result that pearl
millet has a higher value than sorghum grain contradicts Steevens &
Garrett, and Rodenburg (1997).
Regression analysis using SAS provided data on the value of nutrient
contents and the relative importance of each nutrient in the feeds. It
is interesting to note that in general, feeds are being valued based on
their nutrient content. Table 3 demonstrated this general observation if
it is noted that all seven equations have fairly high R2 values.
Several other factors should be considered in the final decision making
process before producers incorporate alternative feeds into dairy rations.
Besides energy and protein contents, factors such as palatability, starch
digestibility, presence or absence of some anti-nutritional factors, degradable
or undegradable protein contents, etc., should be considered.
The report is limited at this point to the findings that regression
analysis worked well for this set of data. Several parameters will change
the regression equation, and so the equation itself is not robust. If grain
price were to change, especially if the changes were not relative to each
other, and if the nutrient content of grains were to change, and is the
mix of grains were to change, then so would the equation. It is hypothesized
that within a competitive market for grains, a new regression equation
would still provide a better estimate of price than the methods of Steevens
& Garrett or Peterson's equations.
Conclusions:
Regression analysis provided closer predicted values for price of the
six grains used, than did three alternative methods. The statistical analysis
reported here is a critical finding, in that other researchers have not
reported statistical analysis with their methods, so it is unknown if they
are reflecting significant results.
The best regression equation was
Price=-49.83+0.53*NEL+0.46*CP+216.05*P.
This equation provided high correlation and statistical significance.
The general price relationship of pearl millet and sorghum grain to
other feed grains is an important result. The best estimate of the value
of pearl millet was $128.75 and that for sorghum grain was $123.91 (May
24/99) .
For this information to be of use, it must be put in a format that is
up to date. As the price of grains change, the value of NEl ,
CP, and P will also change, and so will the regression equation.
The next step is to define regression equations for poultry, swine and
beef using feed grains, and then define regression equations for dairy
and beef using forages.
Acknowledgments:
Funding for this study is gratefully acknowledged from OMAFRA , the
University of Guelph and AERC. Thanks to 'Ports of Canada' for supplying
the samples of grains. The efforts of Jordan Jarjour, my summer research
assistant, are very much appreciated.
References:
-
Agriculture Environmental Renewal Canada (AERC) Annual Report, 1997.
-
Agriculture Environmental Renewal Canada (AERC) Annual Report, 1998.
-
Burton, G.W., A.T. Wallace, and K.O.Rachie, 1972. Chemical composition
and nutritive value of pearl millet. Crop Sci. 12:187.
-
Holden, P.,L. Frobish and J. Pettigrow, 1984. Energy for Swine. Pork Industry
Handbook (PIH-3), Purdue University, West Lafayette, IN.
-
NRC. 1996. Nutrient Requirements of Beef Cattle (6th Revised Ed.). National
Academy Press, Washington, D.C.
-
Sharpe, P.H., McDonald D., McKnight D., Dow B. 1997. Pearl Millet as an
Alternative Silage for Growing Cattle in
-
Steevens, B.J. and J.L. Garrett (1994). Comparative values calculated from
crude protein , NE lactation, calcium and phosphorus. University of Missouri-Columbia,
Missouri.
-
Rodenburg, J. (1997). Boosting the Protein Content of Corn Silage. Ontario
Ministry of Agriculture, Food and Rural Affairs, Ontario.
-
SAS (1996). The SAS System for Windows, Release 6.123. SAS Institute Inc.,
Cary, NC.
| TABLE #2 Nutrient
Composition of Selected Grains |
|
Dry Matter (%) |
Crude Protein(%) |
Total Digestible Nutrients (%) |
NEl
(MCAL/KG) |
Calcium (%) |
Phosphorus (%) |
IVNDFD (%) |
IVPD (%) |
ADF (%) |
NDF (%) |
| CORN #3 Canada East |
90.2 |
8.82 |
91.87 |
1.83 |
0.01 |
0.29 |
50.00 |
93.25 |
4.40 |
11.10 |
| WHEAT feed Canada East |
90.0 |
17.66 |
91.51 |
1.83 |
0.06 |
0.48 |
44.70 |
94.44 |
4.80 |
15.50 |
| BARLEY #1 Canada East |
90.2 |
13.15 |
88.41 |
1.77 |
0.07 |
0.41 |
36.36 |
95.29 |
8.20 |
23.80 |
| OATS #2 Canada East |
88.4 |
12.68 |
79.84 |
1.61 |
0.08 |
0.38 |
32.93 |
91.58 |
17.60 |
35.00 |
| SOYBEAN MEAL GM 48% |
90.6 |
53.32 |
90.41 |
1.81 |
0.28 |
0.73 |
95.01 |
95.39 |
6.00 |
11.00 |
| RYE cereal |
87.4 |
11.62 |
91.51 |
1.83 |
0.05 |
0.37 |
55.84 |
91.26 |
4.80 |
17.80 |
| PEARL MILLET GRAIN |
83.7 |
12.44 |
89.68 |
1.79 |
0.03 |
0.36 |
69.67 |
88.47 |
6.80 |
19.00 |
| SORGHUM (milo) GRAIN |
84.9 |
13.60 |
88.68 |
1.77 |
0.02 |
0.34 |
56.12 |
83.18 |
10.70 |
23.20 |
| TABLE
#3 Regression Equations |
|
Equation |
Regression
Variables |
P-Value |
R2
|
Predicted Value $ / tonne
|
| Sorghum |
Pearl Millet |
Corn |
| #1 |
Price = - 358.62+3.89*CP%+4.75*IVPD% |
CP, IVPD |
0.04 |
0.9618 |
89.39 |
110.00 |
118.63 |
| #2 |
Price = - 400.94+4.05*CP%+0.27*IVNDF%
+5.06*IVPD% |
CP, IVNDFDIVPD |
0.18 |
0.9789 |
90.18 |
115.28 |
120.13 |
| #3 |
*Price = - 433.26+2.07*CP%+5.80*IVPD% |
CP, IVPD |
0.03 |
0.9815 |
77.33 |
105.62 |
125.85 |
| #4 |
*Price = - 427.63+0.083*TDN%+2.07*CP%
+5.66*IVPD% |
TDN, CP, IVPD |
0.03 |
0.9811 |
78.68 |
106.3 |
126.06 |
| #5 |
Price = - 216.34+3.39*TDN%+1.81*CPD%
+565.14*Ca% |
TDN, CPD, Ca |
0.11 |
0.9930 |
120.21 |
127.15 |
116.71 |
| #6 |
Price = - 12.57+47.40*NEL(mcal/kg)+5.21*CPD% |
NEL, CPD |
0.11 |
0.8917 |
130.26 |
129.64 |
117.00 |
| #7 |
*Price = - 49.83+53.12*NEL(mcal/kg)+0.46*CP%
+216.05*P% |
NEL, CP, P |
0.02 |
0.9846 |
123.91 |
128.75 |
114.10 |
* Soybean Meal Included
| TABLE #4
CALCULATED GRAIN PRICE PER TONNE, BY
METHOD
|
| FEED GRAIN |
STEEVENS & GARRETT |
PETERSON'S EQUATIONS |
REGRESSION EQUATION #7 |
MARKET PRICE |
| CORN |
$116.82 |
$116.82 |
$114.10 |
$116.82 |
| WHEAT |
$133.32 |
$138.94 |
$159.20 |
$158.16 |
| BARLEY |
$118.26 |
$124.28 |
$138.80 |
$146.75 |
| OATS |
$106.50 |
$114.28 |
$123.60 |
$121.41 |
| SOYBEAN MEAL |
$228.51 |
$228.51 |
$228.40 |
$228.51 |
| RYE |
$106.89 |
$123.57 |
$132.60 |
$125.00 |
| PEARL MILLET |
$107.80 |
$124.00 |
$128.75 |
unknown |
| SORGHUM |
$110.45 |
$126.00 |
$123.91 |
unknown |