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Forage Quality: Techniques for Testing

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Forage quality refers to how well animals consume a forage and how efficiently the nutrients in the forage are converted into animal products. Six major factors affecting forage quality: maturity (harvest date), crop species (differences between grasses and legumes), techniques of harvest and storage, environment (moisture, temperature and amount of sunlight), soil fertility, variety or cultivar. Also, weeds, insect pests, plant diseases and presence of bacteria, molds, and/or some of their metabolites, e.g. mycotoxins can negatively affect forage quality. Recommended tests for determining forage quality are: dry matter (DM), pH, crude protein (CP), available protein, amoniacal nitrogen (as % NH 3 /TN), acid detergent fiber (ADF), neutral detergent fiber (NDF), lignin and ash. Energy values such as total digestible nutrients (TDN), net energy (NE) and relative feed values (RFV) can be calculated from these core analyses. There are two methods used to analyse such variables: the traditional chemistry analysis and the newer, near infrared reflectance spectroscopy (NIRS) analysis. Currently, the quality of a forage has been evaluated only through those chemico-fermentative parameters. However, recent studies propose to incorporate the analysis of microbiological parameters such as fungal propagule counts, the presence of Aspergillus fumigatus and mycotoxins (aflatoxins and deoxynivalenol) as decisive parameters of forage acceptability. Forage quality information is important for formulating nutritionally balanced rations, evaluating forage management practices (growing conditions, timing of harvest, and handling from harvesting to utilization) and marketing and pricing forages.
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Received: 12 July, 2007. Accepted: 23 September, 2007. Invited Review
Fresh Produce ©2007 Global Science Books
Forage Quality: Techniques for Testing
Cecilia L. Fulgueira1* Susana L. Amigot1 Mónica Gaggiotti2 Luis A. Romero2
Juan C. Basílico3
1 Centro de Referencia de Micología, Facultad de Cs. Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, S2002LRK Rosario, Argentina
2 INTA Rafaela Ruta 34 km 227, 2300 Rafaela, Argentina
3 Facultad de Ingeniería Química, Universidad Nacional del Litoral, Santiago del Estero 2829, S3000AOM Santa Fe, Argentina
Corresponding author: * cfulgueira@yahoo.com.ar
ABSTRACT
Forage quality refers to how well animals consume a forage and how efficiently the nutrients in the forage are converted into animal
products. Six major factors affecting forage quality: maturity (harvest date), crop species (differences between grasses and legumes),
techniques of harvest and storage, environment (moisture, temperature and amount of sunlight), soil fertility, variety or cultivar. Also,
weeds, insect pests, plant diseases and presence of bacteria, molds, and/or some of their metabolites, e.g. mycotoxins can negatively affect
forage quality. Recommended tests for determining forage quality are: dry matter (DM), pH, crude protein (CP), available protein,
amoniacal nitrogen (as % NH3/TN), acid detergent fiber (ADF), neutral detergent fiber (NDF), lignin and ash. Energy values such as total
digestible nutrients (TDN), net energy (NE) and relative feed values (RFV) can be calculated from these core analyses. There are two
methods used to analyse such variables: the traditional chemistry analysis and the newer, near infrared reflectance spectroscopy (NIRS)
analysis. Currently, the quality of a forage has been evaluated only through those chemico-fermentative parameters. However, recent
studies propose to incorporate the analysis of microbiological parameters such as fungal propagule counts, the presence of Aspergillus
fumigatus and mycotoxins (aflatoxins and deoxynivalenol) as decisive parameters of forage acceptability. Forage quality information is
important for formulating nutritionally balanced rations, evaluating forage management practices (growing conditions, timing of harvest,
and handling from harvesting to utilization) and marketing and pricing forages.
_____________________________________________________________________________________________________________
Keywords: chemico-fermentative evaluation, feedstuffs, fungal contamination, mycotoxins, silages
CONTENTS
FORAGE CONSERVATION SYSTEMS .................................................................................................................................................. 121
Hays....................................................................................................................................................................................................... 122
Silages ................................................................................................................................................................................................... 122
Haylage or round bale silages................................................................................................................................................................ 122
FORAGE QUALITY................................................................................................................................................................................. 122
Factors that influence forage quality...................................................................................................................................................... 122
Forage quality evaluation ...................................................................................................................................................................... 123
Sensory evaluation............................................................................................................................................................................ 123
Forage sampling................................................................................................................................................................................ 123
Chemico-fermentative evaluation ..................................................................................................................................................... 123
Nitrogen values................................................................................................................................................................................. 124
Fibers ................................................................................................................................................................................................ 124
Minerals ............................................................................................................................................................................................ 124
Calculated energy values................................................................................................................................................................... 125
Microbiological evaluation ............................................................................................................................................................... 125
Forage bacteria.................................................................................................................................................................................. 125
Fungal contamination of forages....................................................................................................................................................... 126
Toxic – fungal analysis ..................................................................................................................................................................... 128
Fungal propagule counts – Identification of isolates......................................................................................................................... 128
Mycotoxins ....................................................................................................................................................................................... 129
ACKNOWLEDGEMENTS ....................................................................................................................................................................... 129
REFERENCES........................................................................................................................................................................................... 129
_____________________________________________________________________________________________________________
FORAGE CONSERVATION SYSTEMS
Current systems of dairy and beef production demand
deeper knowledge of the production processes and quality
of every available feed (Bruno et al. 1998). Although they
may vary according to region, cattle-rearing production sys-
tems are based upon the direct grazing of forage resources
with supplementary feeding, such as: grains, crop by-pro-
ducts, and stored forages like hay or silage, etc. These me-
thods make it possible for the feed management of herds to
improve and to become more cost-effective (Taysom 2002;
Beltzer 2003).
Forage conservation arises out of the need to rationally
profit from the excess of pastures – lucerne, winter soilage,
etc. and of annual crops that have been specially grown for
ensilage – maize, sorghum, oat, ryegrass, soya, etc. (Ro-
mero et al. 2003).
These conservation processes had been previously used
Fresh Produce 1(2), 121-131 ©2007 Global Science Books
to store excess forage so as to resort to it during feed shor-
tage periods (winter). Nowadays, they are used all year
round in order to obtain more balanced diets.
Hays
Hay is a stored forage that is essentially characterized by
having low percent moisture content (less than 15%). This
means it can be stored unharmed by fermentation or mold
development (Beltzer 2003; Reboux et al. 2006). Although
most forage crops can be stored as haylages, the nutritional
value of the latter is closely linked to the type of plant or
original forage. Among the substantial benefits brought
about by this forage conservation system, the following can
be mentioned: low farm labor demand (both for forage
harvesting and supply), reduced production costs (Lascano
2002; Romero et al. 2003).
Silages
Fresh forage crops, such as maize, sorghum, wheat and
lucerne, can be preserved by ensiling (Oude Elferink et al.
1999a). Ensiling is a forage preservation method based on a
spontaneous acid lactic fermentation under anaerobic condi-
tions (Whitlow and Hagler 2002; Seglar 2003b). Silage
techniques minimize the loss of nutrients as from harvest
time until storage. Moreover, they also improve the quality
of feed (Beltzer 2003).
The epiphytic (existing on plants) lactic acid bacteria
(LAB) that are present on forage crops are involved in the
fermentation of water-soluble carbohydrates to lactic acid
and, to a lesser extent, to acetic acid. As a result, the pH
level of the ensiled material is reduced so the activity of
spoilage microorganisms is inhibited. Once the fresh mate-
rial has been stored, compacted and covered to exclude air,
the ensiling process can be broken down into four phases
(Weinberg and Muck 1996; Driehuis and Oude Elferink
2000).
Aerobic phase: In this phase, which only lasts a few
hours, the amount of atmospheric oxygen present in the
forage is reduced due to the respiration of the plant material
and to aerobic and facultative aerobic microorganisms such
as yeasts and enterobacteria.
Fermentation phase: It starts once anaerobic condi-
tions are reached in the ensiled material. It can last for seve-
ral days or for as long as several weeks, depending on the
characteristics of the forage material and the ensiling condi-
tions. If the fermentation is successfully carried out, LAB
will develop and become the predominant population, while
pH will decrease to values around 4.0.
Stable phase: As long as the silo is properly sealed so
that air is not allowed to enter, there are relatively few
changes. Most microorganisms of the previous phase slowly
decrease in number.
Aerobic spoilage phase: It starts when the silo is
opened so that oxygen has unrestricted access to the silage.
However, it can start earlier if the silage covering is da-
maged, for instance, by animals or other agents. Deterio-
ration begins through degradation of forage preserving or-
ganic acids by yeasts and occasionally by some bacteria.
This results in a rise in pH. Then, temperature increases as
well as the activity of spoilage microorganisms such as
some bacilli and other aerobic and facultative microorga-
nisms such as molds and enterobacteria (Driehuis et al.
1999; Driehuis and Oude Elferink 2000).
The advantages of using silage can be summarised as
follows (Cowan 2001; Schroeder 2004e; Romero et al.
2006):
- As a reserve during times of extreme feed shortage peri-
ods, for instance drought seasons, which entails ensiling
pasture or crops under optimal conditions and storing
them for a period of 1 to 20 years.
- To enhance productivity due to the increase of the
amount of feed available to livestock. The storage peri-
od takes less than one year.
- To improve pasture or crop managements where the
silage enables other management practices to be carried
out. For instance, ensiling temperate fodder crops with
increased tiller density at the beginning of the season
when there is excessive growth enables the earlier plan-
ting of a subsequent crop.
- To profit from excess growth. Generally, this excess is
considered to be a waste. Ensiling allows excess growth
to be stored so that losses due to maturation or decay in
situ are avoided.
- To balance the nutrient content of the diet. The silage is
used to provide nutrients whenever the feeds available
are deficient. For instance, the use of legume silage to
complement maize silage, or combining the use of
maize silage with grazed legume pastures, or resorting
to silages of varied fiber contents.
- To enable storage of perishable materials since the en-
siling process ensures the feed can be used over an ex-
tended period of time, for instance, the ensiling of wet
by-products. This method is similar to that of preserva-
tion of feeds through the addition of chemical substan-
ces or the exclusion of air from high-moisture grains.
- To preserve the dry matter content and keep income po-
tential (palatability, consistency and composition) of the
fermented feed.
Haylage or round bale silages
Haylage is a conservation system for wet forages. Feed is
preserved in a combined process of hay and silage making.
Forage containing around 50% moisture content is rolled up
in bales and then wrapped tightly in polythene or bagged in
self-adjustable stretch bags (Lascano 2002). In this way, as
long as air is not allowed to enter, a bale becomes a small
silo where anaerobic fermentation takes place. Although
any forage can be baled, it is advisable to use high quality
pastures such as lucerne, clovers and grasses that have a
high nutritional value since the additional cost associated
with packing should to be taken into account (Beltzer 2003).
The most significant advantages brought about by this
system are related to agronomic and nutritional aspects, for
instance (Schroeder 2004c; Muck and Holmes 2006):
- Weather-related losses are reduced due to shorter air
drying time.
- Since this ensiling process uses wet forage, field losses
(mainly from leaves) that result from production, dis-
tribution and supply are minimized.
- Small pasture areas can be kept. This differs from sila-
ges, since they demand larger areas.
- Since anaerobic conditions are created, the fermentation
process starts quickly.
- Low farm labor demand at baling time.
- It requires a relatively low capital investment.
- No special storage facilities are required.
- It is easy to handle for rationing and it allows for com-
plete mechanization for operations to take place.
- Storage losses are low (3-7%).
FORAGE QUALITY
Forage quality is defined as an expression of the character-
istics that affect consumption, nutritional value, and the re-
sulting animal performance (Amigot et al. 2005). In other
words, forage quality refers to how well animals consume a
forage and how efficiently the nutrients in the forage are
converted into animal products (Twidwell and Wegenhoft
1999; Taysom 2002). Thus, the best measure related to for-
age quality is animal productivity, which can be affected by
nutrient intake, digestibility and utilization efficiency.
Factors that influence forage quality
Six biological and technological factors affecting forage
quality (not yield) have been traditionally recognized: crop
species, soil fertility and variety, maturity stage, harvest and
122
Testing techniques for forages. Fulgueira et al.
storage techniques, environment (Frey et al. 2004; Schroe-
der 2004d; Reboux et al. 2006).
Crop species: There can be substantial differences in
forage quality between grasses and legumes. These distinc-
tions are generally related to differences in fiber and protein
content, digestibility, etc., which have a negative impact on
consumption and animal productivity (Twidwell and We-
genhoft 1999; Cherney JH 2000).
Soil fertility: Soil fertility exerts greater influence on
forage yield than it does on quality. Appropriate soil phos-
phorus and potassium levels not only contribute to keep
legumes in a mixed seeding, but they also reduce weed rela-
ted problems. It is necessary to balance soil fertility to avoid
mineral imbalances in forages. It has been proved that high
levels of fertilization in grasses make dry matter production
increase. However, as non-protein nitrogen values also in-
crease, unbalanced relationship carbohydrates/protein re-
sults. Therefore, the fermentation process may be affected
(Schroeder 2004g).
Variety (cultivar): After decades of enhancing forage
yield and persistence, attention has recently been aimed at
developing or identifying varieties with improved composi-
tional quality. Variety or cultivar can affect the chemical
make-up of forages, but not to the same extent as the other
factors. In lucerne crops, selection processes to improve
quality are being carried out by most commercial compa-
nies (e.g. HQ and multifoliated lucerne), and several firms
have also started to select improved maize and sorghum
hybrids (better stem quality, crops that stay green longer,
grains with higher nutritional value, etc.) for ensiling.
Maturity: It refers to the growth stage of a plant at the
time that it is harvested. Maturity is the most important fac-
tor affecting forage quality. This quality is not static; plants
continually change in quality as they mature. In fact, forage
plants change so rapidly that it is possible to detect signifi-
cant declines in forage quality every two or three days.
Thus, protein, soluble carbohydrate and vitamin contents of
the plant cell wall increase. The amount of lignin, cellulose
and hemicellulose increases as well. While cellulose and
hemicellulose can be partially digested by livestock, lignin
is not digestible. As the amount of structural fiber and lignin
increases, digestibility of the forage and its consumption by
livestock decreases (Twidwell and Wegenhoft 1999).
Harvest and storage conditions: Inappropriate harvest
techniques can seriously reduce forage quality, for instance
the loss of leaves in haying. Both storing a forage crop with
an incorrect moisture content, and improper ensiling can
lower its quality and molds can appear. Fungi generate heat
through respiration. This reduces protein content and forage
digestibility.
Environment: Climatic conditions (moisture, tempera-
ture, and the amount of sunlight) affect both forage quality
and its production. When harvesting is delayed due to bad
weather conditions, forage crops become overmatured so
that their quality is lowered. High temperatures may in-
crease lignin accumulation and decrease quality, but
drought stress may increase quality by delaying maturity.
The amount of rainfall during the harvest period may bring
about losses in forage quantity and quality since dry matter
content and soluble nutrients decrease.
In addition, the presence of weeds, the damage brought
about by insects, bacteria, molds, and/or their metabolites
(mycotoxins) significantly affect forage quality (Cherney
JH 2000).
Other important factors that should also be taken into
account are: type of silo, filling speed, forage density after
packing, sealing technique, feedout speed, amount of forage
extracted, use of additives, forage supply techniques (Bol-
sen 1998; Jahn et al. 2000).
Forage quality evaluation
All forage plants are made up of cells that are composed of
fibrous cell walls used for support and protection. There are
several soluble compounds within the cells. Most of these
compounds are highly digestible. Since the material of the
cell wall is the primary constituent of forages, one of the
main aims of forage analysis is to characterize the cell wall
fiber (Cherney JH 2000).
Sensory evaluation
Forages have been traditionally evaluated according to phy-
sical parameters such as: color, leaf content, maturity, odor,
softness, purity, observations on palatability, etc. Although
these parameters are important in determining forage qua-
lity, there may be some limitations regarding assessment,
since they remain both highly subjective and difficult to
standardize (Schroeder 2004a).
Forage sampling
Accurate findings during the quality evaluation of forages
depend on the implementation of good sampling techniques,
appropriate handling of samples after collection and upon
reliable analytical procedures in the laboratory that carries
out the evaluation (Schroeder 2004a). So as to conduct a
forage quality study, it is important to take into account that
the first major obstacle lies in the collection of samples;
since it has to faithfully represent the type of feed that will
be consumed by livestock (Faithful 2002). Sampling is the
major factor affecting the accuracy of forage quality ana-
lyses. It has been considered variation from sampling pro-
cedures to be 5 up to 10 times higher than that from labora-
tory procedures (Ferret 2003; Macaulay 2003; Schroeder
2004f). The type of sampling depends upon feed character-
istics, establishing a clear difference between hay/haylages
and silages.
Whenever hay samples are collected, it is advisable to
use a probe that is larger than 1 cm in internal diameter and
place it 30 to 45 cm deep. Thus, core samples from the bale
can be extracted without opening it so that mistakes during
sampling can be avoided. It is advisable to collect 20 sub-
samples (1 for each bale) and form a pool of 500 to 1000 g
(Ferret 2003).
There are two different general aims that influence the
collection of silage samples: to make a reasonable predic-
tion of the silage average quality before ensiling or to know
the quality of the forage being fed to animals (Muck and
Holmes 2006). To achieve the first aim, a probe that allows
for the sample to be collected at a certain depth is used. It is
also important to seal the holes created by sampling as
carefully as possible. For a truly representative sample of
silage content to be obtained, it is advisable to take aliquots
of the average points from the 4 segments generated at the
intersection formed by 2 diagonal lines traced in the upper
part of the silage (Faithful 2002; Ferret 2003). So as to
achieve the second aim, sampling will be conducted by
collecting different subsamples (12 to 15) from the front
part of the silage and from the same kind of forage material
being fed to animals. This procedure is to be repeated at
different times as the content of the silage is used. Moldy or
damaged subsamples that are not appropriate to be fed to
animals should be avoided. Thus, it is not advisable to col-
lect subsamples in areas that are too near the plastic cover.
Between 500 and 1000 g of forage material will be collec-
ted during each sampling procedure.
Chemico-fermentative evaluation
Traditional laboratory methods involve various chemical,
drying and burning procedures to determine the major che-
mical components within the forage. Chemical analyses
prove to be fundamental to estimate forage quality (Colom-
batto 2000; Undersander and Moore 2002; Redfearm et al.
2004).
Wet chemistry procedures are presently the most widely
used for forage evaluation. They are based on sound chemi-
cal and biochemical principles and take considerably more
time to complete than the newer electronic methods such as
123
Fresh Produce 1(2), 121-131 ©2007 Global Science Books
near-infrared reflectance spectroscopy (NIRS) analysis
(Schroeder 2004a). This technique combines methods from
spectroscopy, statistics and computing and generates mathe-
matical models that relate chemical compositions (presence
of active chemical groups) with changes in energy in the
area corresponding to the near infrared range (wavelengths
between 800 and 2500 nm) (Deaville and Flinn 2000; Coz-
zolino et al. 2003). The advantages of this technique are as
follows: it provides information on the nutritional value of
feeds within seconds, it is a non-destructive method that
only asks for a minimal requirement or even no requirement
for sample treatment, it minimizes impact on the environ-
ment and it is a multi-analytical technique that allows for
various factors to be predicted at the same time. Once the
spectrophotometer is calibrated with the same forage crops
that come from the same region, the implementation of
NIRS methodology can help conducting cost-effective ana-
lyses. Thus, this method has been internationally accepted
(Reeves and van Kessel 2000; Reeves et al. 2002). It is
more difficult to interpret analyses obtained by NIRS when
feeds are made up of different forage crops (Stokes and
Prostko 1998).
The chemico-fermentative parameters that are generally
evaluated are as follows:
Dry matter (DM): It corresponds to the percentage of
forage which is not water. It has traditionally been deter-
mined by drying forages at high temperatures over short pe-
riods of time. However, other volatile compounds can also
be evaporated during this process. So as to overcome this
problem, regression equations have been developed. They
correct DM values determined by oven-drying through dis-
tillation with toluene (Haigh 1995a, 1995b). The moisture
content of forages varies according to crop species, physio-
logical state and season. Thus, all the results should be ex-
pressed on a DM basis (as it is the most useful factor to per-
form comparisons).
pH: It is considered to be the individual parameter that
best determines the quality, fermentation and conservation
of forages with a high moisture content (higher than 65%).
The method for measuring pH is both fast and simple: a pH-
meter probe is placed into a sample fluid obtained by
pressing or maceration (Ferret 2003; Maculay 2003; Ward
2005a).
Nitrogen values
Crude protein (CP): The term crude protein is used
because it represents all of the nitrogen that is in the form of
non-protein nitrogen (NPN) such as nitrates, ammonia, urea
and single amino acids, as well as the nitrogen present as
true protein. The total nitrogen concentration of a feed sam-
ple is generally determined by resorting to some variant of
the Kjeldhal method (Cherney DJR 2000), but it can also be
measured using a total combustion technique by means of
an autoanalyser (AOAC 1990). Crude protein is represented
by the total amount of nitrogen present when analyzed and
then multiplied by a conversion factor of 6.25. This is based
on the assumption that true protein contains 16% nitrogen.
However, as this is not always the case, Cherney DJR
(2000) suggested that when determining crude protein a
correction factor for N content should be included. As
plants mature, the crude protein usually decreases. Although
ruminants can use, to a certain extent, all these types of nit-
rogen compounds (Schroeder 2004a), a crude protein analy-
sis that follows this criterion proves to be inappropriate in
determining the quality of the protein present in the forage
(van Soest 1994). The analysis of the protein fraction of a
feed should include data on how that protein influences
microbial protein formation, on the amount of dietary pro-
tein escaping ruminal degradation, etc. (Broderick 1994;
Beever and Mould 2000).
Available protein: Available protein is the portion of
crude protein that is digestible by the ruminant. It is usually
used in describing protein that is ‘available’. Because of the
feeding rate and rumen retention time, not all of the protein
present can be digested. It is usually accepted that only ~70-
72% of the protein can be assimilated.
Unavailable or bound protein: Unavailable or bound
protein is the portion of crude protein that is not usable by
the ruminant. This is fundamental in describing heat
damaged wet forages, where some of the protein has been
rendered unusable due to excessively high temperatures
reached during fermentation. It is advisable to perform this
analysis in those forages with high-protein content that will
be fed to animals. Whenever its value, regarding the total
nitrogen content of the sample, is higher than 12%, some
overheating of the silage has occurred. Therefore, the diges-
tibility of the available protein in the animal’s rumen dec-
reases.
Ammoniacal nitrogen: A substantial part of the forage
protein fraction is degraded to peptides, amino acids,
amines, and ammonia by plant and microbial enzymes,
which reduces the nutritional value of the feedstuff (Schroe-
der 2004g). Therefore, ammonia concentration (usually ex-
pressed as total nitrogen percentage %NH3/TN) is generally
used as an indicator of the silage protein degradation and,
consequently, of its bad preservation (Driehuis and Oude
Elferink 2000; Ferret 2003). The nitrogen content in a
forage sample can also be determined by fluid obtained by
pressing or maceration.
According to pH and %NH3/ TN values a forage may
be classified as: Very Good (pH < 4 and % NH3/TN 5);
Good (pH 4 and % NH3/TN between 5 and 15), Fairly
Good (pH > 4 and % NH3/TN 15) and Bad (pH > 4 and %
NH3/TN > 15) (Fahey 1994).
Fibers
The ruminants need a minimum amount of fibers to main-
tain a good function of rumen. The vegetal fibers include
cellulose, hemicellulose and lignin.
Detergent or Van Soest Method of Cell Wall Deter-
mination: The detergent analysis system is a wet chemical
method that separates soluble cell contents (starches, pro-
teins, sugars, pectins, fats, vitamins, minerals, etc.) from the
fiber fraction (structural support of the plant). The fiber
fraction of a forage is divided into two components that
nutritionists use to prepare feed rations: neutral detergent
fiber and acid detergent fiber (van Soest 1994).
Neutral detergent fiber (NDF): It estimates the total
fiber content of a forage (cellulose, hemicellulose, lignin). It
is the insoluble part of feed in detergent under neutral con-
ditions (Bruno et al. 1998). NFD is partially digestible de-
pending on forage crop and maturity stage. NDF levels are
used to predict feed intake. High NDF levels in a forage not
only decrease intake, but also limit forage effectiveness in,
for example, high milk production (Stokes and Prostko
1998; Ward 2005b).
Acid detergent fiber (ADF): It measures cellulose and
lignin contents of a plant and shows the animal ability to
digest a forage. It is the insoluble part of a detergent in acid
conditions. ADF is also partially digestible. When ADF
levels increase, forage digestibility usually decreases, so
that low levels of ADF are desirable. Some factors that in-
crease ADF in a forage are as follows: maturity, weathering,
rain damage, high temperatures and weeds (Stokes and
Prostko 1998; Beltzer 2003).
Lignin: It is a non-carbohydrate substance that is the
main factor which influences the digestibility of plant cell
wall material. It is a fiber component with no energetic
value for animals but it can affect the digestibility of other
fiber components. Low levels are desirable. When lignin in-
creases, digestibility, intake and performance usually dec-
rease (Stokes and Prostko 1998; Beltzer 2003).
Minerals
Ash: Forage analyses generally report the content of major
minerals. The total mineral content of a forage is called ash
and it represents 3 to 12% of DM. The minerals typically
124
Testing techniques for forages. Fulgueira et al.
determined are calcium and phosphorus. Laboratory tech-
niques used to determine forage minerals are: wet chemistry,
colorimetric methods and atomic absorption. Minerals can
be divided into two groups: macronutrients (such as Ca, P,
K, Mg), and micronutrients (such as Co, Cu, Mn, Fe, Zn
and Se (Stokes and Prostko 1998).
Calculated energy values
Accurately predicting the digestible energy of forages for
ration formulation and animal performance is important
(Bagg 2004).
Measuring the energy content of a feed requires very
sophisticated equipment and animal metabolism trials.
However, it has been discovered that feed energy content is
inversely related to fiber content. Thus, many equations
have been developed to predict energy value from fiber
content, dry matter, etc. However, there is no one that can
estimate it in all forages (Linn and Martin 1999; Rayburn
2002). Moreover, laboratories have not agreed on standar-
dized formulas. This makes it difficult to perform inter-
laboratory comparisons.
There are different measures to describe the energy
value of a feed. The most popular terms are: net energy
(NE), total digestible nutrients (TDN) and relative feed
values (RFV) that can be calculated from core analyses
(Stokes and Prostko 1998).
Net energy (NE): NE is the energy used for mainte-
nance and for productive purposes, i.e. growth, gestation
and lactation. Net energy is derived from animal studies by
measuring the gross energy minus fecal energy, minus
energy lost in urine and minus combustible gases and heat
loss. Net energy (lactation), however, can also be calculated
on a dry matter basis for hay, haylage and corn silage using
the forage Acid-Detergent Fiber (ADF) analysis (Rayburn
2002).
Total digestible nutrients (TDN): This measure repre-
sents the digestible portion of a feed and it can also be used
to estimate the energy content of a forage (Beltzer 2003). To
calculate TDN contents, previous digestion trials need to be
carried out. Forage components can be analysed both from
the feed of a group of animals or from their feces, the dif-
ference can determine the digestibility of each type of nutri-
ents (Schroeder 2004a). The current formula is: % TDN
= % digestible crude protein + % digestible crude fiber + %
digestible starch and sugars + % digestible fats x 2.25. (Fats
are multiplied by 2.25 because they contain more energy
per unit weight). TDN values for hay, haylage and corn
silage, however, can also be calculated on a dry matter basis
using the forage Acid-Detergent Fiber (ADF) analysis (Ray-
burn 2002).
As forages tend to lose an important part of energy
mainly during ruminal fermentation, the TDN % may be
overestimated (Schroeder 2004a). Therefore, it is advisable
to use net energy values to formulate rations.
Relative feed values (RFV): A number of factors must
be considered to accurately evaluate forage quality. RFV is
an index (not units attached) that combines digestibility and
potential intake into one number. This term is useful for
comparing forages of the same type. It is calculated based
on dry matter and dry matter intake. Digestible dry matter is
a function of ADF, and dry matter intake is a function of
NDF. Therefore, fiber components have an integral effect
on RFV.
Generally, nutritionists will require a larger set of analy-
ses to balance rations than what might be required to iden-
tify the quality of forage in the marketplace. Many nutri-
tionists are interested in a wide range of analyses, from
basic fiber and crude protein to minerals, protein digestion
estimates, ash, and sometimes detailed carbohydrate analy-
ses. However, analyses of forage for marketing purposes
may only be a subset of these, and should have the follow-
ing characteristics: must be rapid, be reliable and utilize re-
cognized methods, be repeatable across labs and across time,
must not change significantly over time or be subject to dif-
ferent interpretations and must be a relatively powerful pre-
dictive tool for nutritionists (Putnam 2004).
Microbiological evaluation
Microbiology of forages: The successful outcome of the
conservation process mostly depends upon the microflora
present on forages. A wide range of microorganisms are
naturally as contaminants found in cereals, oilseeds, their
by-products and other components (Driehuis et al. 1999).
They can be classified into two main groups: desirable
micro-organisms and undesirable microorganisms. As men-
tioned before, the presence of lactic bacteria might be bene-
ficial during forage fermentation. LAB and yeasts have feed
probiotic properties, lowering scouring and stimulating ani-
mal growth performance.
Undesirable microorganisms from soil and animal feces
can contaminate and deteriorate forages (Driehuis and Oude
Elferink 2000). They cause anaerobic deterioration (clostri-
dia, enterobacteria) or aerobic deterioration (yeasts, bacilli,
Listeria sp. and molds). Many of these undesirable orga-
nisms (Listeria sp., clostridia, molds, and bacilli) not only
reduce the nutritional value of the forage, but they may also
affect animal health or alter the quality of milk, meat and
eggs, or both (Oude Elferink et al. 1999b, 2002).
Successful conservation of high moisture forages de-
pends on the control of microbial activity. The preservation
process by acidification, dehydration and/or air exclusion
early during the storing period should restrict the develop-
ment of those undesirable microorganisms. However, oxy-
gen can enter the silo through holes in the polyethylene
cover or during exposure to air once the cover is open
(Driehuis and van Wikselaar 1996). Water activity (aw) can
also increase if hermetical conditions are not kept. In these
situations, undesirable microorganisms can develop in the
forage (Gotlieb 2002).
Forage bacteria
Lactic acid bacteria. The natural population of lactic bac-
teria grows significantly between harvest and silage (Oude
Elferink et al. 2002). Anaerobic conditions should be kept
at each stage of the fermentative process to allow LAB to
proliferate using endogenous vegetable sugars to produce
enough quantities of acid to lower the pH level to 4 (opti-
mum for a successful conservation) (D’Mello 2002). Accor-
ding to sugars metabolism, LAB can be classified as obli-
gate homofermenters, facultative heterofermenters or obli-
gate heterofermenters. Obligate homofermenters, such as:
Pediococcus damnosus and Lactobacillus ruminis produce
more than 85% of lactic acid from hexoses (for instance
glucose) but they can not degrade pentoses (for instance
xylose). Facultative heterofermenters, which include Lacto-
bacillus plantarum, L. pentosus, Pediococcus acidilactici, P.
pentosaceus and Enterococcus faecium, also produce, pri-
marily, lactic acid from hexoses. However, they can also
degrade some pentoses producing lactic acid, acetic acid
and/or ethanol. Therefore, they constitute the group that
converts forage sugars to lactic acid more efficiently
(D’Mello 2002). Obligate heterofermenters, which include
members of the genus Leuconostoc and some Lactobacillus
such as L. brevis and L. buchneri, degrade hexoses and pen-
toses but they degrade the hexoses into equimolar quantities
of lactic acid, CO2, acetic acid and/or ethanol (Schleifer and
Ludwig 1995; Oude Elferink et al. 2002). LAB are non-
proteolytic organisms so they contribute to the preservation
of labile proteins and free amino acids in the forage.
Wet forages are difficult to preserve by acidification and
they provide conditions for the development of undesirable
bacteria such as clostridia and enterobacteria (D’Mello
2002).
Clostridia are anaerobic bacteria that form endospores.
Many of them can ferment carbohydrates and proteins. As a
result, they reduce the nutritional value of the silage and, as
well as enterobacteria, they produce biogenic amines which
125
Fresh Produce 1(2), 121-131 ©2007 Global Science Books
cause several problems. In addition, the presence of clos-
tridia alters milk quality since their spores can survive
throughout the digestive tract of animals. As a result, clos-
tridia can be found in feces and may contaminate the milk
directly or indirectly when udders are not clean. There are
two groups of clostridia: the saccharolytic group (Clostri-
dium butyricum and C. tyrobutiricum) and the proteolytic
group (C. bifermentans and C. sporogenes). The first group
ferments residual sugars such as lactic acid to butyric acid,
increasing the pH level; while the second group ferments
amino acids to different products (butyric acid and acetic
acid, amines, CO2 and NH3) and may also increase the pH
level (D’Mello 2002). Some types of clostridia can cause
serious health problems. The most important species in the
dairy industry is C. tyrobutyricum, an acid-tolerant orga-
nism. It can not only ferment carbohydrates but it can also
degrade lactic acid to butyric acid, H2 and CO2. Butyric
fermentation interferes with the lactic fermentation in sila-
ges and cheese and causes gas production (Oude Elferink et
al. 2002). A usual “clostridial silage" shows large amounts
of butyric acid, high levels of pH (>5 in silages with low
DM content), ammonia and amines. Ensiling techniques
that allow a rapid and significant drop of pH would prevent
this problem since enterobacteria and clostridia are inhib-
ited at low pH values. Moreover, clostridia show more sus-
ceptibility to the absence of moisture (low aw value) than
LAB. Every measure taken to decrease the aw value in a
forage, such as inducing wilting to increase the value of the
DM content, allows for the selective inhibition of clostridia
to take place (Oude Elferink et al. 2002).
Enterobacteria are anaerobic facultative organisms.
Most of the enterobacteria present in the silage are
considered non-pathogenic. Nevertheless, their growth
should be avoided since they compete with LAB for sugars,
fermenting them to acetic acid, ethanol, CO2 and H2.
Besides, they can degrade proteins and catabolize amino
acids to NH3, increasing pH (D’Mello 2002). Protein degra-
dation causes a reduction in the nutritional value of the
silage and leads to the production of toxic compounds such
as biogenic amines and branched fatty acids. Biogenic
amines have a negative effect on silage palatability (van Os
1997; D’Mello 2002). The ammonia generated by proteoly-
sis increases the buffer capacity of a silage; this counteracts
any rapid pH drop. Moreover, enterobacteria can produce
nitrite, nitrogen oxides (NO2), nitrogen monoxide (NO) and
ammonia. NO and NO2 gases produce lung tissue damage
and can cause an illness with symptoms similar to those of
pneumonia, known as the “silo filler’s disease” (O’Kiely et
al. 1999).
Escherichia coli O157 belongs to the group of Gram
negative bacteria. It is closely associated with human patho-
logies, for example: hemolytic-uremic syndrome. However,
it has not been associated with animal pathologies. O157 is
widespread in nature. Besides cattle, it is ubiquitous in birds,
deer and other wildlife. Thus, eradication is not possible.
Ecological control measures focus on control of bacterial
intake in feed and water (Teplitski 2006).
Salmonella also belongs to the group of Gram negative
bacteria. It contains many serotypes involved in human and
animal pathologies. Among them, S. typhimurium is univer-
sally distributed and S. enteritidis has appeared as a patho-
gen agent in birds and as egg and chicken meat contami-
nator. Salmonellosis is one of the most important features in
cattle biosecurity. The risks for salmonellosis are minimised
if the right practices are implemented when handling feed
and following disinfection and vaccination protocols. Cattle
feed is frequently contaminated with Salmonella. The inten-
sive use of contaminated pastures with infected animal
feces and the use of poultry slurry provide additional sour-
ces of illness (D’Mello 2002; Winfield and Groisman 2003).
Animals with subclinical infection are more frequent
than ill animals and they are more susceptible to other in-
fectious processes. However, asymptomatic carriers elimi-
nate millions of these microorganisms through their feces.
Vir ule nt E. coli strains can survive for a few months in ani-
mal waste, and Salmonella can persist in untreated farm
waste for up to two years (Winfield and Groisman 2003).
Proper utilization and composting of animal wastes are im-
portant steps for reducing Salmonella and E. coli contami-
nation, and breaking the cycle of reinfection (Teplitski
2006).
Listeria monocytogenes is a pathogenic facultative an-
aerobic organism to several animals and to men. It is widely
distributed in nature and can contaminate forages. Animals
with temporary inhibited immune systems (pregnant fe-
males and neonates) are susceptible to L. monocytogenes
infections. The L. monocytogenes contaminated silage has
been associated with fatal cases of listeriosis in sheep and
goats and it has been one of the main sources of raw milk
contamination by L. monocytogenes. The increase in the
incidence of listerosis in sheep and cows has been related to
the usage of big bale silages, a kind of low density and
limited fermentation forage that favours the growth of L.
monocytogenes. Growth and survival of Listeria spp. in the
silage are determined by the failure of keeping anaerobic
conditions and by the pH value of the silage. L. monocyto-
genes can tolerate low pH levels, between 3.8 and 4.2, for
long periods as long as there is oxygen even in minimum
concentrations. However, they die in a strictly anaerobic
environment with low pH value (Oude Elferink et al. 1999a,
1999b). This microorganism can contaminate animal pro-
ducts destined for human consumption.
Fungal contamination of forages
Fungal contamination of cereals, oilseeds and forages repre-
sents a major risk for human and animal health in the world.
Both yeasts and filamentous fungi can contaminate forages.
Yeasts mainly include Candida and Saccharomyces species.
Yeasts are frequently the most numerous isolates. They are
eukaryotic, facultative anaerobic and heterotrophic micro-
organisms. Yeast population can reach 107 CFU/g during the
first weeks of the ensiling process; however long-term
storage gradually reduces the presence of yeasts. Available
oxygen facilitates the growth of yeast during storage where-
as a high level of formic acid or acetic acid reduces survival
(Driehuis and van Wikselaar 1996; Oude Elferink et al.
1999b). Under anaerobic conditions yeasts ferment sugars
to ethanol and CO2. The production of ethanol decreases the
amount of sugar available to produce acetic acid and affects
milk taste (Randby et al. 1999). With the introduction of
oxygen in the silo, a large amount of yeast species aerobic-
ally degrade lactic acid to CO2 and H2O. The degradation of
lactic acid increases the pH level of the silage and allows
the growth of other undesirable organisms such as filamen-
tous fungi (Seglar 2003a).
Molds are eukaryotic organisms that grow in any part of
the silo where there is oxygen, even in small amounts. In a
good silage that happens at the beginning of the storage
period and it is restricted to the surface of the ensiled mass.
But during aerobic deterioration all the silage can be in-
vaded by molds (Rankin and Grau 2002).
The most significant factor that determines fungi
growth in hays is moisture. Hence, molds are mostly found
in hays that are stored wet. Whereas, the factor that deter-
mines fungi growth in silages is pH. If the silage is stored
too dry or not compacted enough or uncovered, air infiltra-
tion will produce microbial activity which, in turn, will deg-
rade the acids of the silage while increasing the pH level,
and promoting mold growth (Whitlow and Hagler 2000).
Filamentous fungi more frequently identified in forages
belong to the genera Aspergillus, Eurotium, Penicillium,
Fusarium, Mucor, Byssochlamys, Absidia, Arthrinium, Geo-
trichum, Monascus, Scopulariopsis and Trichoderma (Oude
Elferink et al. 2002). Molds not only decrease the nutri-
tional value and palatability of the forage but also represent
a risk for animal and human health. Inhalation or intake of
fungal propagules may cause diseases collectively known as
mycosis (Di Costanzo et al. 1995; D’Mello 2002). Mold
growth in forages expose animals to respiratory problems,
126
Testing techniques for forages. Fulgueira et al.
allergies, abnormal ruminal fermentation, diminished repro-
ductive function, reduced production, renal damage, skin
and eye irritation (Scudamore and Livesey 1998; Gotlieb
2002). Fungal contamination affects both the organoleptic
characteristics and the alimentary value of feed, and ex-
poses animals to the potential risk of toxicosis. Mycotoxins
are fungal secondary metabolites that are produced accor-
ding to a wide range of genetic and environmental factors
(D’Mello 2002; Amigot et al. 2005).
Mycotoxin contamination of forages and cereals fre-
quently occurs after plants are infected with specific patho-
genic fungi or symbiotic endophytes. Moreover, contami-
nation may occur during feed processing and storage, when-
ever environmental conditions (moisture content and am-
bient temperature) are appropriate for fungal colonization
and mycotoxin production (Rankin and Grau 2002). Fungal
growth and mycotoxin production are related to extreme
weather conditions, inadequate storage practices, bad forage
quality and faulty feeding conditions (Whitlow and Hagler
2000; Lanyasunya et al. 2005). Conventionally, toxigenic
fungi have been devided into “field” organisms (or vegetal
pathogens and “storage” organisms (or saprophytic/spoil-
age organisms). Claviceps, Fusarium and Altrernaria are
usual field fungi; Aspergillus and Penicillium are examples
of storage organisms. When field fungi are isolated from
forages they indicate poor preservation conditions because
these fungi need a higher aw to develop, and they are often
absent from adequately stored silos (Scudamore and Live-
sey 1998; Akande et al. 2006; Amigot et al. 2006).
Although there are over 100000 species of known fungi,
the majority of the known toxigenic species fall into three
recognized genera. These genera are Aspergillus, Penicil-
lium, and Fusarium. Also, most of the known mycotoxins
are elaborated by these genera.
The genus Aspergillus is within a large, very diverse
family of fungi that are world-wide in distribution but
primarily occupy subtropical and warm temperate climates.
They are generally regarded as saprophytes that are impor-
tant in nutrient cycling. Their growth at high temperatures
and low water activity allows for their involvement in the
colonization of a variety of crops, sometimes with limited
parasitism especially under favorable conditions. Some of
the most economically important toxigenic species of fungi
belong to this genus. Four species are responsible for the
production of mycotoxin with larger incidence: A. flavus
and A. parasiticus that synthesize aflatoxins, and A. ochra-
ceous and A. carbonarius that produce ochratoxins (Moss
2002b). Aflatoxins include: aflatoxins B1, B2, G1 and G2.
Moreover, aflatoxin M1, the result of the hepatic biotrans-
formation of aflatoxin B1, may be present in the milk of
dairy cows that eat feed contaminated with aflatoxin B1.
When cows consume aflatoxin B1, it can not only be toxic
to the cow but also it appears in the milk within 24 hours.
Generally, the levels of aflatoxin M1 appearing in milk are 1
to 2 percent of the aflatoxin B1 content of the feed. Research
data indicate aflatoxins will clear the system of dairy cows
within 48 to 96 hours after the contaminated feed is re-
moved from the ration (Waldner and Lalman 1998). Afla-
toxin contamination is predominant in maize and tropical
feeds such as oilseed by-products derived from groundnuts,
cottonseed, and peanut (D’Mello 2002).
Ochratoxins are known to be produced by Penicillium
verrucosum and species of the Aspergillus ochraceus group
(Moss 2002b). However it has been recently reported that
black Aspergilli: A. carbonarius, A. japonicus, as well as
other species that belong to the A. niger species complex
(Samson 2000) also produce these toxins. Ochratoxins A
and B are present as natural contaminators mainly in cereal
seeds and in tissues of animals fed with contaminated
forage (Heenan et al. 1998).
Members of the genus Penicillium generally grow and
can produce mycotoxins over a wider range of temperatures
than those of the genus Aspergillus (Ominski et al. 1994;
Moss 2002b). The Penicillium spp. are more abundant in
temperate climates. Members of this genus are more com-
monly associated with storage than with preharvest conta-
mination of grain (CAST 2003).
Fusarium is a large complex genus with species adapted
to a wide range of habitats. They are worldwide in distribu-
tion and many are important plant pathogens. However,
many species are soil borne and exist as saprophytes impor-
tant in breaking down plant residues. A few species are sig-
nificant mycotoxin producers and some of them are present
preharvest in contaminated grains as well as in other plants.
Toxigenic Fusarium include: F. graminearum, F. culmorum,
F. sporotrichioides, F. poae, F. verticillioides, F. prolifer-
atum (Moss 2002c). These species produce a wide range of
mycotoxins. Trichothecenes, fumonisins and zearalenone,
are relevant to human and animal health. Trichothecenes are
subdivided into 4 basic groups: the most important are
groups A and B. Group A trichothecenes include toxins T-2
and HT-2, neosolaniol and diacetoxyscirpenol. Group B tri-
chothecenes include: deoxynivalenol, (also known as vomi-
toxin or DON), nivalenol and fusarenon-X. Some Fusarium
produce zearalenone together with some trichothecenes.
Fumonisins are synthesized by a particular Fusarium group
(F. verticillioides, F. proliferatum). Three related com-
pounds are generally present in maize: fumonisins B1, B2
and B3 (Moss 2002c).
Mycotoxins that are most frequently found in forages
are: aflatoxins, zearalenone, ochratoxin, fumonisins, T-2
toxin and deoxynivalenol (Akande et al. 2006). Contamina-
tion with aflatoxins in cattle feed has been mainly registered
in seeds stored in warm climates (Hell et al. 2000; da Silva
et al. 2000; Whitlow 2005). However, most published arti-
cles on forage mycotoxin contamination come from mild-
cold regions where the use of silages is indispensable to
reinforce pastures. In these regions, Fusarium mycotoxins
prevail. Among them, DON, a Fusarium graminearum
mycotoxin, is the most commonly reported. The co-occur-
rence of various mycotoxins (aflatoxin and some Fusarium
mycotoxins such as DON, T-2 toxin, zearalenone or/and
fumonisins) has been also registered in feeds (Dairy Busi-
ness Communications 2004; Amigot et al. 2005, 2006).
The biological effects of mycotoxins depend on the
ingested amounts, number of occurring toxins, duration of
exposure to mycotoxins and animal sensitivity (D’Mello
2002; Yiannikouris and Jouany 2002a, 2000b). Taking these
factors into account, health problems may range from mild
digestive disturbances, decrease in feed intake, weight loss,
reduced milk production, minor fertility problems and a
decrease in natural defenses – generally related to the lack
of response to diet change and therapies, to serious damage
(even cancer) to the liver, kidney and abortions (Scudamore
and Livesey 1998; Moss 2002a; Amigot et al.2006). Myco-
toxin effects are cumulative over a period of time (di Cos-
tanzo et al. 1995). Chronic effects on human and animal
health are more often noted than acute ones. Often animals
do not die or show acute signs early in a mycotoxicity. It
may take several days to several weeks to cause market
changes in performance or acute symptoms (Adams et al.
1993; Bhat and Vasanthi 2003). The presence of more than
one mycotoxin may increase their effects. The co-occur-
rence of several mycotoxins, even in low concentrations
(lower than the stipulated limits in the countries with regu-
lations) is of great importance (Rankin and Grau 2002).
Due to the possibility of addition, synergism or potentiation,
the effect of the mixtures cannot be predicted solely on the
basis of the effect of the individual toxins (Yiannikouris and
Jouany 2002a). A review of the literature on mycotoxin
interactions indicates that additive or less than additive
effects were the predominant interactions observed. Syner-
gistic interactions are the least frequent (CAST 2003).
Because of mycotoxin presence in commonly ensiled
forages and their potential for affecting dairy cattle produc-
tion and health, mycotoxin analysis should be part of the
routine evaluation of silages (Díaz 2006).
127
Fresh Produce 1(2), 121-131 ©2007 Global Science Books
Toxic – fungal analysis
As mentioned before, the quality of a forage is currently
evaluated only through chemico-fermentative parameters,
among them pH and % NH3/TN (McDonald et al. 1991).
Although these parameters are sufficient to evaluate forage
nutritional quality and its potential bacteriologic contamina-
tion, they fail to predict the presence of fungi and/or myco-
toxins.
High fungi concentration records, identification of spe-
cies pathogenic to humans and animals and/or potentially
toxigenic and the identification of mycotoxins in forages
destined for animal feed indicate that many times the tech-
nology applied during the development of crops, their har-
vest and the preparation and conservation of forages should
be improved. Moreover, this information acts as a warning
on the need to evaluate, not only chemico-fermentative
parameters but also toxic fungal parameters to determine
the acceptability of a forage. Recent studies suggest that a
count of fungal propagules, some fungi species in particular
(such as Aspergillus fumigatus) and some mycotoxins (de-
oxynivalenol, aflatoxins or both), should be included as de-
cisive parameters to evaluate forage quality and, therefore,
its acceptability (Amigot et al. 2003, 2005, 2006; Diaz
2006; Gaggiotti et al. 2007).
Fungal propagule counts – Identification of
isolates
Both yeasts and filamentous fungi can contaminate forages
exposing humans and animals to different diseases (Gotlieb
2002). It has been determined that fungal concentrations
higher than 106 CFU/g in a forage may be the reason for
these problems. The following interpretation levels for mold
counts in feed have been proposed: 103 CFU/g - Relatively
Safe, 103–105 – Transition Zone, 105–106 – Caution Advised,
> 106 – Recommended not to feed (Taysom 2002). There-
fore, fungal propagule count should be considered a toxic-
fungal parameter to determine forage quality. Although
counts of fungi on feed are essential, qualitative inves-
tigations that provide additional information about the kind
of fungi (harmless or dangerous) contribute to know the
product’s mycoflora.
Even though mold counts may be low, identification of
the isolated mold is highly recommended. These data are
indicative of the potential toxicity and pathogenity of for-
ages and they become very important if producers do not
pay special attention to proper handling and storage of feed
(Whitlow and Hagler 2002). In many studies, it has been
reported that potentially toxigenic species represent the
larger percentage of the isolated fungi (Amigot et al. 2006).
Apart from finding potentially toxic fungi, it is impor-
tant to evaluate the presence of other species such as Asper-
gillus fumigatus (important human and animal pathogen)
which is considered as the pathogenic agent associated with
mycotic hemorrhagic bowel syndrome (HBS) in dairy cattle
mainly in immunosuppressed animals (Puntenney et al.
2003; Tekaia and Latgé 2005). A. fumigatus has been found
both from dehydrated and fermented forages (Whitlow and
Hagler 2002). It produces gliotoxin, a mycotoxin that can
suppress immunity, therefore increasing the infectivity of
the fungus (Melo dos Santos and Dorner 2002; Whitlow
2005). It has often been associated with forage putrefaction
and heating (Scudamore and Livesey 1998). As a result, A.
fumigatus has been proposed as another forage quality indi-
cator (Amigot et al. 2006).
MAIZE
SORGHUM
LUCERNE
CHEMICO
CHEMICO-
-FERMENTATIVE ANALYSIS
FERMENTATIVE ANALYSIS
VERY GOOD - GOOD FAIRLY GOOD BAD
RISK
ACCEPTANCE
MAIZE
LUCERNE
AFLATOXINS
DON
SORGHUM
FUNGAL CFU/g COUNT
A.fumigatus
AFLATOXINS
TOXIC
TOXIC-
-FUNGAL
FUNGAL
ANALYSIS
ANALYSIS
FORAGE SAMPLE
RISKACCEPTANCERISKACCEPTANCE
Fig. 1 Protocol to be followed for a quick and safe evaluation of a forage sample.
128
Testing techniques for forages. Fulgueira et al.
Mycotoxins
Mycotoxin analysis can be used as an indicator of manage-
ment problems, and thereby, it may be a useful diagnostic
tool (Thomas et al. 1998). The isolation of potentially toxi-
genic fungi cannot be considered a per se indicator of for-
age contamination with those mycotoxins (Magan et al.
2003) and, therefore, some toxin analyses must be carried
out. Amigot et al. (2006) have suggested that the quality of
maize, sorghum and lucerne forages should be evaluated as
follows: those forages with bad chemical quality would be
considered risky, since they do not provide adequate
nutritional value for cattle feed regardless of their toxic-
fungal evaluation. Those forages with a Very Good, Good,
or Fairly Good chemical quality, would need, as a
complimentary tool, microbiological assessment, such as
fungal propagule counts and the presence of A. fumigatus
and mycotoxins (aflatoxins and deoxynivalenol). The feed
which does not present any altered toxic-fungal parameters
would be considered acceptable. If the forage presents some
altered toxic-fungal parameters, it would be considered
risky (Amigot et al. 2006).
However, in order to reduce costs and time while
maintaining the integrity of the results, several research
studies were driven to determine if one or more of the
studied variables (or a combination of them) could be taken
as markers of storage quality, without having to evaluate the
rest of the variables. Thus, DON has been employed in
mild-cold climate regions as a marker of feed exposed to
favourable conditions for fungal growth and production of
other mycotoxins (Whitlow and Hagler 1998; Seglar 2004).
It has been proposed that a positive DON analysis suggests
the possible presence of other mycotoxins more toxic than
DON itself. However, other research determined that the
forage samples which did not contain DON, contained afla-
toxins (Gaggiotti et al. 2003, 2007). Moreover, studies car-
ried out recently established that for lucerne and maize for-
ages, aflatoxin and deoxynivalenol determination provides
enough information to be a marker of feedstuff final
evaluation (Amigot et al. 2006). However, for sorghum for-
ages, it could be concluded that it is necessary to determine
fungal CFU/g counts, the presence of Aspergillus fumigatus,
and the aflatoxin concentration to evaluate silage quality
(Fig. 1). Fig. 1 summarizes the protocol that should be fol-
lowed to evaluate the quality of maize, sorghum and lucerne
forages, using the stated parameters (Amigot et al. 2006).
It is important to develop other protocols that allow
quick, economic, simple, safe decision-making as regards
the acceptability of other forages for their use as animal
feed.
For animal production to be both efficient and profit-
able all the tools and information available should be used.
The production of high quality forage is one of the most
significant management tools to increase animal perfor-
mance, reduce feed costs and allow for time/money invest-
ment to pay off (Schroeder 2004b, 2004d).
Forage quality is highly variable among and within for-
age types for nutrient composition as well as digestibility.
Routine and accurate forage testing is critical to the success
of dairy cattle feeding programs (Allshouse et al. 1998;
Shaver 2001).
The reports presented in this review also illustrate the
importance of monitoring forages in order to have an ac-
curate diagnosis of their quality. The rejection of a forage is
related to extreme climatic conditions, inadequate storage
practices, low nutritional value, and faulty feeding condi-
tions (Whitlow and Hagler 1998). That is why finding vari-
ables that indicate food quality is a very useful tool to per-
form a rapid evaluation of a production chain (Rayburn
2002).
Both dairy and beef producers as well as forage manu-
factures should clearly understand how important forage
quality analysis is. Dairy-beef producers must know the
nutritional content of forages so as to develop the best feed
strategy available for them. Forage manufacturers must get
acquainted with quality analyses to produce forages dairy-
beef producers would be willing to pay for (Stokes and
Prostko 1998).
ACKNOWLEDGEMENTS
We would like to address special thanks to Rocío Gómez and
Cecilia Martínez, English <> Spanish translators, for their help in
the achievement of this work.
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... Quality assessment of forage is crucial, focusing on the types and quantities of nutrients present, which determines how effectively animals can utilize the forage and how efficiently the nutrients are converted into valuable animal products (Fulgueira et al., 2007). The Ministry of Agriculture and Rural Affairs (MARA) of China and the American Feed and Grassland Council have established general Days from emergence to harvesting (DEH), dry matter yield (DM), crude protein yield (CPY), and dry matter accumulation rate (DMAR). ...
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