Department of Agriculture, University of Reading
This review describes accepted procedures for feed analysis with particular emphasis on rapid analyses. The analysis of individual chemical compounds tends to be easier to standardize than some less well-defined, but nutritionally important parameters, e.g. oil, fibre, starch. Inter-laboratory comparisons have demonstrated unacceptably large variation. A coordinated effort is required to reach consensus procedures amongst feed analysts using quality control measures. Unfortunately, there are few certified reference materials (CRMs) and proficiency schemes for animal feeds. In cases of complex mixtures of pro- or anti-nutrients, e.g. tannins, structure-function relationships have not yet been elucidated and, therefore, no particular assay can be recommended to plant breeders. Finally, the concept of traceability of analytical measurements has been translated to traceability of feeds in the form of a Feed Passport. This will become increasingly important following the meat-and-bone meal issue in cattle feed and new soybean varieties that led to the bovine spongiform encephalopathy (BSE) crisis and the genetically modified organisms (GMOs) disputes.
Most forage and by-product feeds are variable in composition. Only very few, such as dried whole whey, are uniform in composition and do not usually require analysis (Schingoethe, 1991). Feed analysis provides information for:
farmers to optimize nutrient utilization in animal feeds;
feed compounders to prepare feed mixtures suitable for different animal production systems;
researchers to relate animal performance to feed characteristics; and
plant breeders to optimize the nutritive value of new varieties (Madsen et al. 1997; Wrigley, 1999).
Many rapid analytical tests have been developed over the last few years and are of use when faced with a need for quick decisions or when confronted by large numbers of samples, e.g. at entry points of shipments, trading situations, on contamination sites or in plant breeding programmes.
This review will cover the main issues which prompted developments in quality assurance and control of analysis. Information will also be given on accreditation of laboratories, together with useful addresses. Subsequent sections will describe standard and widely accepted methods, highlight areas that require particular attention and refer to recent developments in feed analysis. Topics covered will include: sample preparation, analysis of major components (dry matter, ash and minerals, crude protein, fat, fibers and starch) and of secondary plant products (tannins, mycotoxins and other contaminants). Developments in the analysis of whole samples by near infrared reflectance spectroscopy will be mentioned and the potential of this technique to by-pass traditional feed analysis by directly predicting animal responses.
The reader may consult the following books for general information on feedstuff evaluation and diet formulation in relation to animal production: Wiseman and Cole (1990), Minson (1990), AFRC (1993), Fahey et al. (1994), Givens et al. (2000a). Detailed protocols for analytical methods can be found in MAFF (1986), Watson (1994), AOAC (1995) and on the web (Appendix 1).
This review will only briefly mention a few chromatographic and mass spectrometric techniques in relation to analysis of secondary products. It will not cover the analysis of whole samples by new in vitro digestibility techniques, pyrolysis-mass spectrometry, nuclear magnetic resonance or other spectroscopic techniques as these have been covered elsewhere (Mauricio et al., 1999; Givens et al. 2000a).
2. QUALITY CONTROL, ASSURANCE, ACCREDITATION AND PROFICIENCY TESTING IN FEED ANALYSIS
2.1 Inter-laboratory variation
The need for agreement on methods to obtain comparable, useful data became obvious with the beginning of scientific agriculture in the 19th century (Midkiff, 1984). Different methods led to widely varying results and to regulatory confusion. In 1884, the first meeting of the Association of Official Agricultural Chemists (AOAC) began to tackle fertilizer analysis and soon, 1886, included feedstuff testing. The AOAC president stated in 1896 The matter of the analysis of foods and feedstuffs, as shown by the experience of the association, is one of the most difficult questions connected with the work of this organization. The AOAC was renamed in 1965 to Association of Official Analytical Chemists to take cognizance of the fact that the AOAC now had a wider scope (Midkiff, 1984).
A report in 1985 on the quality of data relating to Pb and Cd analysis in food laboratories concluded that results were inaccurate and the validity of the data was in doubt (Patey, 1996). Similar conclusions have been reached for a wide range of data relating to feed analysis. It would appear that feed analysis is somewhat lagging behind food analysis. Selected examples are given below, in order to illustrate the magnitude of the problem.
Bailey and Henderson (1990) concluded that there was an urgent need to improve oil and sugar determinations, since these methods had relatively poor precision amongst 15 feed laboratories. These data are commercially important as they are used when making labeling declarations and for energy content estimation. Lanari et al. (1991) commissioned a study of brewers grain, dried beet pulp, lucerne and hay with 20 feed analysis laboratories. Unacceptably large coefficients of variation were found for mean oil content (determined as ether extract): 3.5 percent (cv = 17.8); lignin: 5.4 percent (cv = 27.3); neutral detergent fibre (NDF) 55.6 percent (cv = 7.4 percent). Coefficients of variation were 5 percent or less for dry matter (DM), crude protein (CP), crude fibre (CF), ash, acid detergent fibre (ADF), and gross energy (GE). Beever et al. (1996) submitted two contrasting maize silages to 10 commercial feed laboratories. They concluded that current feedstuff analysis provided unacceptable variation and required national standards, as coefficients of variation were 12.7 percent for CP and 16 percent for starch. In addition, Givens et al. (2000b) also list several more references reporting large inter-laboratory variation for several analyses relevant in feed evaluation: organic matter (OM) digestibility, in situ rumen degradation, gas production kinetics, in vitro digestibility, metabolizable energy (ME) and GE.
In vitro and in vivo digestibility measurements have been shown to suffer from similar inter-laboratory variation. Madsen and Hvelplund (1994) sent five feeds to 23 laboratories in 17 countries and found "differences... in protein degradabilities between laboratories too large to be acceptable" when using nylon bags in the rumen of cows or sheep. The within laboratory variation, however, of protein degradation was acceptable. They concluded that sample preparation and processing and the bags themselves varied considerably between laboratories and made detailed recommendations for the nylon bag procedure. Authors also recommend that a standard feed is made available for all laboratories for routine checking of analytical procedure. A small ring test of the Tilley-Terry method between 3 laboratories suggested that it was a robust method for OM digestibility of roughages (Madsen et al., 1997). However, problems were encountered with concentrates and highlights that careful standardization is required. Not surprisingly, feed manufacturers have moved to an enzyme method and such results are expected to be more reproducible (Madsen et al., 1997).
There are large differences between the different in vitro digestibility techniques (rumen fluid versus cellulase based techniques) which are used to predict in vivo digestibility (De Boever et ai., 1994; Aufrère and Michalet-Doreau, 1988). Clearly, such differences in methods need to be resolved.
These data collectively support the introductory statement that feed analysis can be difficult. Strict adherence to method details is important, especially if the method itself defines the component, e.g. crude fat, NDF, lignin, as empirical fractions are chemically not well defined (Bailey and Henderson, 1990). Zeeman and Bonn (1995) have also suggested that there should be an international definition of starch. However, large variation may highlight problems in analytical methods and thus encourage closer investigation. Problems with too high NDF values, for example, are likely to be stem from incomplete solubilization of starch. Recently, Thiex et al. (1996) investigated the observed large variation in reported vitamin A results, which was noted by the American Association of Feed Control Officials (AAFCO) who operate a feed check sample programme. Several recommendations were made to reduce errors of Vitamin A in animal feed and pet food analysis.
2.2 The benefits of quality assurance programmes
A review of the literature for methods of feed grain analysis concluded that it was not possible to assess if variation in reported values was due to genotypic, environmental factors or inter-laboratory differences. Petterson et al. (1999), therefore, recommended the use of quality assurance schemes, inter-laboratory evaluation programmes and reference materials.
The Global Environmental Monitoring Scheme of the World Health Organization (WHO) tested the performance of European Union (EU) laboratories that contribute data on food contamination (Weigert et al., 1997). This involved five proficiency tests, 136 laboratories in 21 countries using their own preferred methods for the analysis of trace metals (Pb, Cd, Hg in milk powder), pesticides (organochlorine, organophosphorus, pyrethroid in spinach powder), nitrate in spinach powder, aflatoxins in nut-based animal feeds. Only 60 percent reported accurate for trace metals, 41 percent for pesticides, 43 percent for nitrate, 88 percent for aflatoxins and 53 percent for patulin (average = 68 percent).
Key et al. (1997) summarized the results of the UK Food Analysis Performance Assessment Scheme (FAPAS) from 1990-1996. For pig feeds (moisture, ash, oil, protein, fibre, Cu), only 76 percent of laboratories achieved satisfactory results and for nutritional analysis 80 percent were satisfactory. The FAPAS study also reveals that some analyses are more difficult than others. 91 percent of aflatoxin data were satisfactory, 81 percent of veterinary drug residues, 86 percent of dichlorodiphenyldichloroethylene (DDE), but only 71 percent of dichlorodiphenyltrichloroethane (DDT) and 65 percent of Ca data. Surprisingly, Ca analysis has shown little improvement over the years. Inter-laboratory comparisons and proficiency testing can highlight inappropriate methods, e.g. analysis of veterinary drug residues using certain immunological tests. However, once laboratories were participating in proficiency tests on a regular basis (e.g. FAPAS) the average percentage for accurate results increased.
Horwitz (1993) observed "most experimentation dealing with analytical methodology in biological sciences has been conducted within a single laboratory. Method validation by other laboratories was considered not only unnecessary but also detrimental because, in the words of one commentator, the results are too variable. Within the last two decades, however, it has become increasingly apparent that a collaborative inter-laboratory study is the only way to estimate the variability characteristics of methods...." and to meet the increasing demand by regulatory programmes for high quality data.
2.3 How to achieve valid data
The UK Department for Trade and Industry launched an initiative in 1994 on Valid Analytical Measurement (VAM) incorporating four main principles.
2.3.1 Principle 1: Measurements should be made using properly validated methods
Properly validated methods will provide information on the performance of an analytical technique, such as accuracy and precision, ruggedness, operating range, selectivity and limits of detection. It is essential when reporting a measured value to also give its uncertainty. Otherwise, it is not possible for users of the data to know what confidence to place in the data. It needs to be recognized that problems of communication can arise from the word uncertainty, as a layperson may misinterpret the statistical term error into inaccurate data! (Williams, 1996).
Guidelines are now available for the statistical evaluation of analytical tests and laboratory performance (Bailey and Henderson, 1990): the inter-laboratory precisions are generally a function of concentration. Horwitz group found that the within-laboratory variation was approximately one-half to two-thirds of the between-laboratory variation and can be used as a bench mark for judging previously unevaluated methods (Bailey and Henderson, 1990).
2.3.2 Principle 2: Quality assurance protocols should incorporate certified reference materials (CRMs) to ensure traceability of measurements
CRMs are used for:
Calibration and verification of measurements under routine analysis conditions
Internal quality control and quality assurance schemes
Verification of the correct application of standardized methods
Development and validation of new methods of measurement.
Unfortunately, only few CRMs are available for validation of analytical methods for feed analysis, especially for proximate analysis (Crosby, 1995). However, CRMs exist for minerals in two animal feeds: hay powder (Ca, K, Mg, P, S, Zn, I, N, Kjeldahl-N) and rye grass (As, B, Cd, Cu, Hg, Mn, Mo, Ni, Pb, Sb, Se, Zn) (Maier et al., 1990; see Appendix 1 for CRM suppliers). Information on the inhouse production of reference materials can be found in Walker and Brookman (1998). It is good practice to include external CRMs or in-house reference materials into all analytical procedures.
2.3.3 Principle 3: Laboratories should seek an independent assessment of their performance for particular tests, preferably by participating in national and international proficiency testing schemes (PTS)
PTS independently assess the performance of analytical laboratories. The true concentration of an analysis can be determined by addition of a known amount of analyses to a base material or better still through the use of a consensus value produced by a group of analysts. Guidelines exist for organizing a collaborative study to evaluate analytical methods (AOAC, 1988). Appendix 1 lists several proficiency testing schemes.
2.3.4 Principle 4: Laboratories should seek independent approval of their quality assurance arrangements, preferably by accreditation or licensing to a recognized quality standard.
It should be recognized that only certain accreditation schemes are appropriate for laboratories performing chemical analysis, e.g. NAMAS M10, ISO 90025, ISO/IEC 17025, EN 4501. General guidelines have been written on how to prepare for accreditation (EURACHEM/WELAC, 1998). Gangaiya and Morrison (1992) listed general problems of setting up quality assurance in some developing country laboratories. Appendix 1 lists several accreditation organizations.
3. SAMPLE PREPARATION
Good analytical data require that samples be representative of the whole and that their integrity has been ensured during transport to the laboratory and during their preparation (drying and grinding). Relevant guidelines for feeds can be found in Feeding Stuffs (1988), AOAC (1995), Crosby (1995) and Wrigley (1999). Drying may adversely affect the analysis of sugars, vitamins, certain trace elements (F, Se, B), and ammonia and volatile fatty acids (VFAs) in silages (MAFF, 1986). Caution needs to be taken when grinding lupin and chickpea seeds (Petterson et al., 1999).
Several methods exist to determine moisture content of feeds: oven drying at 105o C for 16h, 125o C for 4h or 135o C for 3h (AOAC, 1995). Molasses should be dried at 70o C because of high levels of volatile compounds (Petterson et al., 1999). Oven-drying is problematic with silages and high fat feeds; vacuum-oven drying at 95-100o C (AOAC, 1995) or at <70o C, Karl Fischer or toluene distillation are alternative techniques (Crosby, 1995; Cherney, 2000). Baker et al. (1994) found significant variation in moisture contents between laboratories, which were tracked down to variable temperature gradients in ovens (Givens, pers. communication).
Crude ash is determined either by ashing at 600o C for 2 h or between 500-550o C for 12-16 h (Midkiff, 1984; Petterson et al., 1999). For difficult samples, Crosby (1995) lists some special techniques. Flameless atomic absorption spectrometry on solid feed samples for trace levels of Cu represents an interesting development (Anzano et al., 1994). However, sample size at present is restricted to 2-4 mg. This technique, therefore, requires further development for general applicability in feed analysis.
6. CRUDE PROTEIN
Crude protein data are standard for evaluating the protein value of forages (Cherney, 2000). The historic developments and critical points in Kjeldahl nitrogen measurements (choice of catalyst, temperature and digestion times) have been summarized by Lakin (1978) and Midkiff (1984). The Dumas technique represents an alternative method for total nitrogen. Total nitrogen is determined after combustion of the sample and several commercial instruments are now available for this. The measurements are rapid taking only 25 minutes per sample. The small sample size (20 to 500 mg) is the key problem with the Dumas method. Samples should be finely ground and preferably dry to avoid too frequent changes of costly reagents. Therefore, the best method for some materials, e.g. silages, is still the Kjeldahl procedure as drying would remove ammonia-N.
The need for corrosive and toxic reagents is the main disadvantages of the Kjeldahl method.
Total Dumas nitrogen values can be slightly higher than the Kjeldahl values as Dumas N also includes nitrate and organic compounds that are highly resistant to acid digestion (Lakin, 1978; Petterson et al., 1999). As a result, exceptional differences can occur with some biological matrices, e.g. fruits, vegetables and fish, with Kjeldahl-N:Dumas-N ratios as low as 0.15 (Simonne et al., 1997).
A factor of 6.25 is used to convert total nitrogen in animal feeds into crude protein. However, the amino acid composition varies between foods and therefore different factors have been suggested to convert total N to crude protein (Petterson et al., 1999). It can range from 5.14 for grains and oilseeds to 6.38 for dairy products. As there is some doubt about the universal validity of such factors, authors should report crude protein values together with the factors used in their calculation (Lakin, 1978).
It should be noted that none of the dye-binding methods were universally acceptable between laboratories for protein determinations (Petterson et al., 1999). Recently, Strong and Duarte (1992) described a simple and rapid biuret method for protein determination in wheat, rice and soybeans. This has been applied to a wide range of different grains and only requires a blender, reagents, colorimeter at 550 nm and minimum operator training. The method requires initial calibration against protein values obtained by other techniques. This procedure may be of interest to grain and feed merchants as it can be completed in five minutes.
7. FIBRE ANALYSIS
It is important to recognize that all fibre determination employs empirical methods, i.e. the method determines the final result and any deviation from the analytical protocol will produce a different result (Midkiff, 1984; Crosby, 1995). Midkiff (1984) summarized the history of crude fibre analysis. Cherney (2000) contrasted the Weende proximate analysis system, which originated in 19th century and has hardly changed since then, with the Van Soest system developed in the 1960s. He cautions against the use of CF, nitrogen free extractives (NFE), ether extract (EE) in feed evaluation systems, as they do not sufficiently separate digestible from non-digestible fractions. The Van Soest system is now widely used for forage evaluation as it provides useful measurements for nutritionally important parameters, such as structural carbohydrates (Goering and Van Soest, 1970; AOAC method 973.18).
Several groups have since modified the original manual method (Cherney et al., 1989; Van Soest et al., 1991) and Chai and Uden (1998) have described a simple oven-based procedure. The micro-NDF method by Pell and Schofield (1993) is another modification, which allows NDF to be determined on small sample sizes (10 to 50 mg). Moore and Hatfield (1994) comprehensively reviewed the composition and analytical methods for structural and non-structural carbohydrates citing research involving both ruminants and monogastric animals. Mertens (1997) concluded, "the only fibre method that can be used on all types of feeds is the method recommended by the National Forage Testing Association" (Undersander et al., 1993, Hintz and Mertens, 1996; see also Appendix 1 for Web site).
Starch removal from NDF can be difficult and requires pre-treatment with a-amylase either overnight (McQueen and Nicholson, 1979) or by using heat-stable a-amylase (Sigma product A3306) during the last 30 minutes of NDF extraction and during filtration (Cherney et al., 1989). Difficult samples may also require pretreatment with 8M urea (Van Soest et al., 1991). Filtration problems may be due to incomplete starch removal. However, errors in fibre analysis may also stem from aged crucibles, as crucibles can be damaged at too high temperatures or by rapid rates of heating or cooling in muffle ovens (Crosby, 1995).
Fibretec (Tecator, Hoenganaes, Sweden) and the recent FibreAnalyzer (ANKOM Technology Co., Fairport, NY, USA) are instruments for NDF and ADF extractions. Studies indicated that ADF by Fibretec and FibreAnalyzer are comparable for most feeds. However, in our experience NDF in starch containing feeds is best analysed by the FibreAnalyzer as it removes starch more efficiently (unpublished data).
Starch consists essentially of two components, amylose and amylopectin. Amylose polymers contain up to 2000 glucose units connected through linear 1->4 linkages. Amylopectin is a highly branched polymer containing 2,000 to 220,000 glucose units with 1->4 and 1->6 linkages. Therefore proper extraction techniques are crucial for successful starch analysis (Petterson et al., 1999).
Starch is determined by pre-treating with 80 percent ethanol in boiling water to remove low molecular weight sugars, followed by gelatinization and solubilization, before extracting and hydrolyzing the starch (Faichney and White, 1983; Åman and Graham, 1990; Hall, 1997). Incomplete dissolution and incomplete accessibility to enzymes tend to be the main problems in starch analysis. McCleary et al. (1994; 1997) reported that a ringtest involving 29 laboratories to evaluate the Megazyme enzyme kit for cereal products and some animal feeds produced good agreement for total starch content. This enzyme kit was accepted as an AOAC method (996.11) (Petterson et al., 1999).
The proportion of amylose and amylopectin depends on the source of the starch. Starch digestibility is not necessarily related to total starch content as the amylose: amylopectin ratio and processing affect the extent of starch digestion (Allen et al., 1997; Reynolds et al., 1997). The Rapid Visco Analyser measures pasting properties of starch in grain and Wrigley (1999) speculated that this may be related to starch digestibility, but this awaits further research.
9. CRUDE FAT
Fat in plant-derived feeds consists mainly of mono-, di-and triacylglycerides, free fatty acids and phospholipids. Feeds also often contain fats from animal and other waste products. Depending on the rendering processes used, heating or storing can lead to unsaponifiable matter, oxidized and polymerized fatty acids which will contribute to crude fat values, but not be of nutritional value (Edmunds, 1990). Midkiff (1984) described the history of crude fat analysis and the sample types that caused problems.
Several official methods exist to determine crude fat in animal feeds (AOAC 945.16 and 920.38; MAFF 1986). Crude fat methods are empirical methods and procedural details must be closely adhered to. They are based on solvent extractions with or without hydrolysis. Crude fat is extracted by the EU procedure A with petroleum ether (40-60o C) and the dried residue weighed (Feeding Stuffs 1988). Acid hydrolysis is used as a pretreatment in EU procedure B. However, it is recommended that animal feeds are first extracted with petroleum ether (40-60o C) (Procedure A) and then subjected to acid hydrolysis, before re-extraction with petroleum ether (40-60o C) (Procedure B). This minimizes losses during filtration of the acid digest, which can occur if protected fats, i.e. Ca and Mg salts of fatty acids are present (Edmunds, 1990; Crosby, 1995).
Neither procedure A nor B will give satisfactory results if feeds contain milk products. The Rose-Gottlieb method is required for such feeds, as the alkaline pretreatment frees occluded lipids from protein capsules (ISO 1211:1984). Similarly, canned dog foods require extraction with a series of solvents after hydrolysis (Budde, 1952; Midkiff, 1984; AOAC 954.02).
Problems may arise if diethyl ether is used instead of petroleum ether as suggested in some methods. Slightly higher values may result if water has not been removed completely from either the sample or the solvent, as some compounds, such as urea and sugars, are slightly soluble in diethyl ether in the presence of small amounts of water (Midkiff, 1984; AOAC 920.39).
Great care is required when performing solvent extractions. Solvent are usually recycled between a lower electric heating source and an upper water-cooling system in a Soxhlet apparatus. Accidents are not uncommon with such a set-up. For this reason, a different type of extractor has been developed recently (Brown and Mueller-Harvey, 1999). The Soxflo instrument requires neither heat nor cooling water and is based on a dry-column procedure. The sample is packed into a column and the extracting solvent drips slowly through it. Crude fat values determined by the Soxflo and Soxhlet procedures were found to be in close agreement. If sample drying and packing procedures are evaluated against the Soxhlet procedure, good and reliable crude fat data can be obtained in 60 to 90 minutes.
10. SECONDARY PLANT PRODUCTS: TANNINS
Although a whole range of different plant secondary products exists, only tannins will be discussed here. The main reason for this is the persistent confusion that surrounds tannins in animal nutrition. Analytical techniques have often been misapplied and data misinterpreted. However, reference will be made to rapid analyses of mycotoxins and other secondary plant products which can contaminate or affected the nutritive value of animal feeds (see Section 11).
Tannins comprise a diverse group of phenolic compounds, varying in molecular size from 500 to possibly 28,000 Daltons (Jones et al., 1976; Mueller-Harvey and McAllan, 1992; Schofield et al., 2001). Some are easily extracted by aqueous solvents, others are not and can be measured as fiber or protein bound tannins (Jackson et al., 1996; Reed, 1986). The naming and thereby classification of condensed (CT) or hydrolysable tannins (HT) is somewhat misleading as some of the condensed tannins are relatively easily degraded oxidatively, whereas some of the hydrolysable tannins will resist all attempts at hydrolysis (Mueller-Harvey, 1999; 2001).
Negative and positive animal responses have been attributed to tannins, i.e. ranging from animal death to increased growth rates (Butter et al., 1999; Mueller-Harvey, 1999). Despite many animal studies involving tanniniferous feeds, little attempt has been made to elucidate the relationship between animal production and tannin structures. Progress is unlikely to be achieved by the continued use of colorimetric tannin assays alone (Petterson et al., 1999). Lowry et al. (1996) put it succinctly: "the simplicity of absorbance measurements masks the problems of extracting meaningful data".
A general reagent produces varying colour yields from different phenolic compounds, which includes tannins (Folin and Ciocalteau, 1927). However, phenolics and tannins tend to occur in mixtures and quantitation is not possible unless isolated standards are used, which are representative of the exact composition of the material being examined. Procedures for colorimetric methods for CT and HT have been described by Graham (1992), Waterman and Mole (1994) and Hagerman (Web site).
Porter et al. (1986) recommended a modification of the butanol-HCl assay. This assay is excellent for detecting the presence of CT. However, for quantization purposes it should only used if isolated tannins are used as calibration standards as tannin structures have a marked effect on colour yield (Giner-Chavez et al., 1997). Even within the same species, there can be sufficient structural variation to warrant isolated tannin standards from different accessions in quantitative work (Stewart et al., 1999). More recently, a CT assay based on acidified 4-dimethylamino-cinnamaldehyde (DMACA-HCl) was described (Li et al., 1996). This assay proved more sensitive than the vanillin-HCl method, which can suffer from interference by water (Terrill et al., 1990). The DMACA assay was also used successfully on thin layer chromatography (TLC) plates and as a histochemical assay. This method has not yet been examined thoroughly against interferences from monomeric flavanols.
The analysis of HT has been reviewed by Mueller-Harvey (2001). Again, assays are best used to detect HT, as accurate quantitation would require isolated standards (Hagerman et al., 1997). Furthermore, there are just a few known species that produce only gallotannins, from which gallic acid can be hydrolysed before detection (Willis and Allen, 1998). More usually, gallo- and ellagitannins occur together as mixtures. Ellagitannins are much more difficult to measure (Wilson and Hagerman, 1990) although the free ellagic acid can be measured by high performance chromatography (HPLC) (Mueller-Harvey et al., 1987). However, as stated above, many other so-called HT does not release gallic or ellagic acid.
It is recommended that additional assays be used in tannin analysis to overcome some of the problems of the colorimetric tests, e.g. the Yb-precipitation method (Reed et al., 1985; Giner-Chavez et al., 1997; Krueger et al., 2000a) and/or one of the protein or polymer binding assays (Makkar et al., 1987; Dawra et al., 1988; Makkar et al., 1993) when screening novel fodder plants. If facilities are available to measure radioactivity, tannins can also be measured by binding to 125I labelled BSA (Hagerman and Butler, 1980) or 14C-polyethylene glycol (PEG) (Silanikove et al., 1996). Tannins can be estimated directly in feed samples, without prior extraction in the latter method.
The Yb-method precipitates total phenolics (i.e. tannins, flavonoids and other phenolics) which correlate positively with butanol-HCl CT (Reed et al., 2000). The advantage is that phenolics are determined by gravimetry without the need for standards. Interestingly, the amount of PEG bound per gram of sample correlated highly significantly with in vitro N digestibility and appeared to be a more meaningful measurement than the colorimetric assays (Jones and Palmer, 2000). Correlations with CT measurements by vanillin-HCl were better than by butanol-HCl.
In view of the problems of colorimetric assay, it seems surprising that TLC has not been used more widely. TLC reveals the presence of CT vs HT, low vs high molecular weights of CT, the subclasses of CT or HT (procyanidins or prodelphinidins, gallo- or ellagitannins), plus semiquantitative information based on colour intensity (Mueller-Harvey et al., 1987). Tannins from different species have also been compared by reverse phase HPLC (Mueller-Harvey et al., 1987), size exclusion chromatography (Yanagida et al., 1999; Hedqvist et al., 2000) and normal phase chromatography (Tanaka et al., 1984; Okuda et al., 1989; Hagerman et al., 1992). Okuda et al. (1989) reviewed the mass spectrometric analysis of tannins. More recently, ESI-MS (Guyot et al., 1997; Marais et al., 2000) was used to determine tannin molecular weights. New developments in MALDI-TOF mass spectrometry (Hedqvist et al., 2000; Krueger et al., 2000a and b) succeeded in determining the molecular weights and composition of complex tannin mixtures.
11. IMMUNOASSAY TECHNIQUES: FOR MYCOTOXIN AND OTHER FEED CONTAMINANTS
Mycotoxins pose severe hazards to humans and animals. Mycotoxins in feeds, along with many other organic compounds, can be analysed by either instrumental [HPCL, gas chromatography (GC), capillary electrophoresis (CE)] or biochemical (immunoassays) techniques.
Skerritt and Appels (1995) described the basic principles of enzyme-linked immunoasorbent assays (ELISAs) and illustrated the different forms of techniques (direct or indirect assays, sandwich or competition assays). For example, in the direct competitive ELISA format, enzyme-linked antibodies (E-As) coat the surface of a well plate or test tube, which are supplied in a test kit.The operator extracts the feed sample and places the extract onto the surface. Compounds of interest, i.e. antigens, bind to the E-As thereby releasing them from the surface. E-As are then washed away and an enzyme substrate is added to the remaining, bound E-As. This procedure results in an inverse relationship between antigen concentration and colour production: the higher the antigen concentration, the more E-As have been washed away and the smaller the colour yield of the reaction.
Several commercial kits are available for aflatoxins, zearalenone and other mycotoxins, alkaloids, glucosinolates, insecticides, herbicides, fungicides, various environmental pollutants, vitamins in foods and animal feeds. Morgan (1995) reviewed these ELISA techniques and listed suppliers addresses. Schneider et al. (1991) developed an interesting dipstick technique for the simultaneous detection of several mycotoxins.
ELISAs can be used by regulatory authorities, quality control laboratories and in research laboratories. They require relatively little user training and can be used in small laboratories or under field conditions. Low cost and high speed make ELISAs ideal for on-site monitoring of stored grain and for assessing rapidly if the maximum residue levels of traded animal feeds have been exceeded. They can also be used for checking suspected spillages. High sample throughput facilitates elimination of large numbers of negative, uncontaminated samples. It is, however, recommended that samples giving positive results for a contaminant should be re-analysed by conventional instrumental techniques to ensure absence of matrix interference and accuracy of the data (Petterson et al., 1999).
Some commercial test kits compare well with standard AOAC methods for aflatoxins in animal feeds (Trucksess et al., 1989 and 1990; Cochrane, 1991) and can be used for quantitative or semiquantitative measurements in as little as 3 minutes. Several of these have now obtained AOAC approval (Trucksess et al., 1989). ELISAs can be tailored to be selective for individual compounds or compound classes, parent compounds or metabolites and even for isomers. Highly sensitive ELISAs for M1 in milk samples have been reported (Kawamura et al., 1994). Of interest in the current European BSE crisis is a report by von Holst et al. (2000), who evaluated the applicability of a commercial ELISA method to detect proper heat treatment of pork and beef meals.
A word of caution. ELISA procedures - like any analytical method - need to be carefully evaluated as some solvents used for analyte extraction may adversely affect antibody performance (Morgan, 1995). In an inter-laboratory study, ELISA tests gave good results for ZON, but accuracy with the DON kits was poor (Schuhmacher et al., 1997). Matthews et al. (1996) investigated commercial kits for three organophosphorus pesticides (OP) for laboratory and field use. The authors found good correlation with GC methods (r-values between 88 and 98 percent). However, as the protocols supplied with the kits were somewhat confusing, the authors provided improved protocols for use by grainstore keepers, millers and malsters. It was also found that the operating ranges of the kits were not as wide as claimed by the manufacturer. In addition, some cross-reactivity of the antibodies was observed with structurally related compounds. Nonetheless, the study showed that ELISA tests could be used reliably to measure OP residues on stored grain.
The most common problems encountered in ELISAs are incomplete washing steps, pipetting problems, insufficient temperature control of reagents and plates, degradation of conjugate (may inhibit good binding to antibody) or loss of enzyme activity (Gee et al., 1995). Problems with sample matrices are also common and can be detected by comparison of standards in an uncontaminated or blank matrix. Recovery studies of standard additions may show up matrix problems. Alternatively, a dilution curve with sample matrix solution can be compared against a standard calibration curve. If the slopes are not parallel, a matrix effect is likely.
Finally, when purchasing an assay kit, the following criteria should be considered: price per assay, sensitivity, cross-reactivity, suitability for the chosen matrix, availability of published validation by independent workers and technical support (Gee et al., 1995).
12. NEAR INFRARED REFLECTANCE SPECTROSCOPY (NIRS) FOR WHOLE SAMPLE ANALYSIS
Deaville and Flinn (2000) wrote a brief and clear introduction to the basic principles of NIRS. An accessible and more detailed review of applications and a description of the mathematical treatments of NIR spectra has been given by Shenk and Westerhaus (1995). Givens and Deaville (1999) have also reviewed NIRS in relation to feed analysis and animal nutrition.
The advantages of NIRS (Givens and Deaville, 1999) over traditional techniques are:
Rapid, as minimal or no sample preparation necessary
On-the-spot analysis of the whole sample, i.e. a non-destructive technique, allows simultaneous measurement of several parameters
High throughput makes NIR a cheap technique on a sample basis
Environmentally friendly: no reagents, no chemical waste
The limitations of NIRS are:
Suitable for major feed components, not for minor components
Great care needed in developing calibrations as these are matrix specific
Complexity in choice of data treatment is confusing for the novice
Calibration procedures are time consuming and only worthwhile for subsequent analysis of large sample numbers
High instrument costs
NIRS was developed in the 1950s and 1960s for quantitative analysis and applied to feed analysis in the 1970s (Norris et al., 1976). By the late 1970s, NIRS was routinely used for protein measurements in grain. The NIRS region covers wavelengths between 730 and 2500 nm and is the infrared region that is particularly suited to quantitative analysis (Givens and Deaville, 1999). The main absorption bands of water are at 1940 and 1450 nm, of aliphatic C-H bonds at 2310, 1725, 1400 and 1210 nm, of O-H bonds around 2100 and 1600 nm and N-H bonds at 2180 and 2055 nm. Spectra are depicted in the form of the reciprocal log of reflectance (log1/R) and provide little direct information. Various components in the feed matrix produce a series of overlapping bands, which results in a smooth, rolling line. However, first- and second-order derivatives of the log1/R spectra can be used to resolve these overlapping bands.
NIRS data are generally subjected to a mathematical pretreatment to reduce interferences from light scatter (Barnes et al., 1989). Then one of several different multivariate calibration methods is used to relate the spectral data from a sufficiently large and representative sample set to the primary, wet chemistry, data (Blanco et al., 1997). Finally, calibrations are subjected to validation procedures with an independent set of samples. A simple monitoring procedure has been developed to minimize NIRS analysis errors (Shenk et al., 1989).
Great care should be taken in developing NIR calibrations (references in Deaville and Flinn, 2000). Calibrations should be based on at least 50 samples, but often many more are required (>150). Givens and Deaville (1999) pointed out that NIRS is largely a secondary technique requiring calibration using samples of known composition determined by using standard methods (primary techniques). A problem can arise, when the primary methods do not define well the chemical constituent, e.g. drying at 100oC to determine moisture does not necessarily define water content or 6.25 x total N does not necessarily describe protein content adequately (Shenk and Westerhaus, 1995).
It has been stressed that consistent sample preparation is required, as variations in particle size, residual moisture content and packing density can adversely affect NIR spectra. However, new developments of NIR software, such as the noise repeatability file, have succeeded in reducing the sensitivity to residual sample moisture (Baker et al., 1994; Shenk and Westerhaus, 1995). Alternatively, by using a coarse transport cell, a larger surface area of fresh grass silage can be screened, thus eliminating the need for dry silages (Park et al., 1999a, b).
NIRS has been accepted as an official AOAC method for crude protein and ADF (AOAC 989.03) and for moisture (AOAC 991.01; Barton and Windham, 1998). It has also been used for determining starch and non-starch polysaccharides, fat and oil, metabolizable energy, insect or weed seed contamination in feed grains (Wrigley, 1999) and for the analysis of dried forages (Murray, 1993). It can be used to identify feeds and perform authenticity checks (De Boever et al., 1993). In addition, heat damaged protein, fungal contamination and adulteration can be detected with modern pattern recognition software (Givens and Deaville, 1999).
It is also possible to transfer calibrations developed on an expensive scanning instrument to cheaper filter instruments in a network (Puigdomènech et al., 1997). This ISI cloning software also allowed a successful transfer of NIR calibrations developed for fresh grass silages from a Foss to a Bran & Luebbe instrument (Park et al. 1999b).
Researchers are now aiming to predict directly the functional properties of feeds to animals, i.e. nutrient supply and production responses such as live weight gain, milk fat and protein or meat composition, rather than measuring feed components (Wrigley, 1999). Good predictions have been achieved for organic matter digestibility in vivo (Barber et al., 1990); ME content (Givens et al., 1992) and voluntary feed intake (see references in Deaville and Flinn, 2000). It has also been possible to predict nutritionally relevant products, such as lactic acid, VFAs and cumulative gas volumes with calibrations based on 800 fresh silages (Deaville and Flinn, 2000). The ultimate aim is to formulate diets for optimum animal productivity, cost effectiveness and the least environmental effects (Givens and Deaville, 1999).
This review describes general procedures for feed analysis and includes recent developments towards faster techniques for fibre (FibreAnalyzer) and fat (Soxflo) analysis, new enzyme kits for rapid starch analysis, ELISAs for mycotoxins and other feed contaminants and progress in whole feed analysis by NIR spectroscopy.
It would appear that feedstuff analysis is difficult in comparison with other analyses (Midkiff, 1984; Key et al. 1997). The analysis of an individual, well-defined chemical compound tends to be easier to standardize between laboratories than some of the less well-defined, but nutritionally important parameters, e.g. oil, fibre, starch or digestibility of animal feeds. A better understanding of these parameters would help to improve their measurement.
Several inter-laboratory comparisons have demonstrated that variation tends to be unacceptably large, and that a coordinated effort has to be made to reach consensus procedures amongst feed analysis laboratories. Significant progress has been achieved through international efforts in producing CRMs for minerals, pesticides and pollutants in a range of environmental and food matrices. However, there are fewer CRMs for feeds, with still no CRM for NDF, and a dearth of proficiency schemes for animal feeds.
Plant breeders have access to several assays that determine levels of single, simple constituents responsible for beneficial or harmful effects (amino acids, n-3 fatty acids, minerals, mycotoxins, glucosinolates, alkaloids) (Wrigley 1999).
However, in cases of more complex mixtures of pro-or anti-nutrients, e.g. starches, tannins, lectins, structure-function relationships have not yet been elucidated and, therefore, no particular assay can be recommended for use in breeding programmes (Caygill and Mueller-Harvey, 1999). Similarly, tests for biologically active compounds, e.g. phytoestrogens or antioxidants, could be used more widely by plant breeders once the beneficial target compounds have been clearly identified.
Finally, the concept of good analytical practice, that ensures traceability of measurements through use of validated methods and CRMs, has also been translated to traceability of feeds by a feed manufacturer in the form of a Feed Passport. This is likely to become increasingly important following recent experience with meat and bone meal in cattle feed and new soyabean varieties that led to the BSE crisis and GM disputes.
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1. USEFUL WEBSITES FOR FURTHER INFORMATION (TEACHING AND TRAINING)
Accreditation and Quality Assurance - a journal for quality, comparability and reliability in chemical measurement.
2. WEB SITES FOR ANALYTICAL METHODS
Methods for forage testing: http://www.dfrc.wisc.edu/foragetesting_nfta.html
Methods for tannin analysis: http://miavx1.muohio.edu/~hagermae/
2.3 Addresses and Web sites for Certified Reference Materials
National Institute of Standards & Technology
Standard Reference Materials Programme
Building 202, Room 204
Gaithersburg, MD 20878-9950, USA
Fax: +1 301 948 3730
Community Bureau of Reference
Commission of the European Communities
Rue de la Loi 200
B-1049 Brussels, Belgium
Fax: +32 2 295 8072
The Office of Reference Materials
Laboratory of the Government Chemist
Middlesex TW11 0LY, U.K.
6 South Mundells
Haslemere Industrial Estate
Welwyn Garden City
Herts AL7 1EP, U.K.
Fax: +44 1707 396 677
Breitlaender Eichproben und Labormaterial
4700 Hamm 3, Germany
Fax: +49 2381 403 189
National Institute for Environmental Studies
Japan Environment Agency
P O 16-2 Onogawa
Ibaraki 305, Japan
Fax: (0298) 51 6111
2.4 Addresses for RING TESTS or Proficiency Schemes
National Forage Testing Association, USA:
Dr V Houba
Department of Soil Science and Plant
Wageningen Agricultural University
P O Box 8005
6700 EC Wageningen/The Netherlands
Fax: +31 8370 83766
Dr A. Eijgenraam
Bedrijfslaboratorium voor Grond- en
6860 Oosterbeek, The Netherlands
Fax: 0031 26 333 7831
(Please note: two feed samples per year for
non-commercial laboratories only)
P O Box 14105
Republic of South Africa
Fax: +27 12 664 1431
Dr A.L. Patey
Ministry of Agriculture, Fisheries and Food
Food Science Laboratory
Norwich Research Park
Norfolk NR4 7UQ, U.K.
Fax: +44 1603 501 123
2.5 Web sites for Accreditation