Pendugaan Umur Simpan Produk Pangan dengan Metode Accelerated Shelf-life Testing (ASLT)

Oleh Feri Kusnandar (artikel asli dalam Food Review Indonesia)

Keterangan umur simpan (masa kadaluarsa) produk pangan merupakan salah satu informasi yang wajib dicantumkan oleh produsen pada label kemasan produk pangan. Pencantuman informasi umur simpan menjadi sangat penting karena terkait dengan keamanan produk pangan dan untuk memberikan jaminan mutu pada saat produk sampai ke tangan konsumen. Kewajiban pencantuman masa kadaluarsa pada label pangan diatur dalam Undang-undang Pangan no. 7/1996 serta Peraturan Pemerintah No. 69/1999 tentang Label dan Iklan Pangan, dimana setiap industri pangan wajib mencantumkan tanggal kadaluarsa (expired date) pada setiap kemasan produk pangan.

Informasi umur simpan produk sangat penting bagi banyak pihak, baik produsen, konsumen, penjual, dan distributor. Konsumen tidak hanya dapat mengetahui tingkat keamanan dan kelayakan produk untuk dikonsumsi, tetapi juga dapat memberikan petunjuk terjadinya perubahan citarasa, penampakan dan kandungan gizi produk tersebut. Bagi produsen, informasi umur simpan merupakan bagian dari konsep pemasaran produk yang penting secara ekonomi dalam hal pendistribusian produk serta berkaitan dengan usaha pengembangan jenis bahan pengemas yang digunakan. Bagi penjual dan distributor informasi umur simpan sangat penting dalam hal penanganan stok barang dagangannya.

Penentuan umur simpan produk pangan dapat dilakukan dengan menyimpan produk pada kondisi penyimpanan yang sebenarnya. Cara ini menghasilkan hasil yang paling tepat, namun memerlukan waktu yang lama dan biaya yang besar. Kendala yang sering dihadapi oleh industri dalam penentuan umur simpan suatu produk adalah masalah waktu, karena bagi produsen hal ini akan mempengaruhi jadwal launching suatu produk pangan. Oleh karena itu diperlukan metode pendugaan umur simpan cepat, mudah, murah dan mendekati umur simpan yang sebenarnya.

Metode pendugaan umur simpan dapat dilakukan dengan metode Accelerated Shelf-life Testing (ASLT), yaitu dengan cara menyimpan produk pangan pada lingkungan yang menyebabkannya cepat rusak, baik pada kondisi suhu atau kelembaban ruang penyimpanan yang lebih tinggi. Data perubahan mutu selama penyimpanan diubah dalam bentuk model matematika, kemudian umur simpan ditentukan dengan cara ekstrapolasi persamaan pada kondisi penyimpanan normal. Metode akselerasi dapat dilakukan dalam waktu yang lebih singkat dengan akurasi yang baik. Metode ASLT yang sering digunakan adalah dengan model Arrhenius dan model kadar air kritis sebagaimana dijelaskan berikut ini.

Finger Test for Doneness

With a little practice you can tell when your meat is done with the touch of your finger or tongs. As meat cooks, the proteins contained within it break down and recombine in a process called denaturing.

The texture of the various degrees of doneness of meat correspond closely to the feel of the fleshy part of your palm below the thumb: The more the meat is cooked, the less malleable it becomes. Try this finger test the next time you cook a steak and see how accurate your equipment is!

Rare

Touch your thumb and forefinger together and press on the fleshy part below your thumb (illustrated in the red circle in the photo) -- it should feel soft to the touch with your other forefinger and a little bouncy. This is how a rare steak feels.

Medium

Touch your thumb and middle finger together and press on the fleshy part below your thumb (see photo) -- there's some give and it's springy to the touch. A medium steak will feel the same.

Well Done

Touch your thumb and little finger together and press on the fleshy part below your thumb (see photo) -- there's no give and it's quite firm. This is what a well-done steak feels like.

Sumber:

Perspectives of Starch Functionality and Methods of Analysis in Food Systems

Dr. Ralph D. Waniska, Professor
Cereal Quality Laboratory
Department of Soil & Crop Sciences
Texas A&M University

Introduction

Perspectives on the applicability of analysis methods and how these methods can be used to monitor the critical processing parameters and product characteristics will be discussed. This position paper will review some of the functional properties of starch and how some of these properties are measured. I will not attempt to address all the functional aspects of starch nor all the methods to measure starch functionality.

Starch functions in many ways in food systems. Starch functionality is affected by the type, source, and structure of starch, the matrix of flour particles, pretreatments, processing conditions, storage parameters, etc. Documenting starch structure-process-function relationships are necessary to resolve day-to-day variations that we observe in manufacturing of all starch-based foods.

Review of Starch Functional Properties

Native starch granules function in many food systems by being an insoluble solid (part crystalline, but mostly amorphous solid). Native starch is associated with 0.5-1.0 g water / g starch and enables the preparation of batters and doughs with >50% solids. Some water remains unbound, i.e., mobile or free, even in these high solids mixtures. Starch granules swell reversibly as long as the heat and pressure are lower than gelatinization conditions. As processing conditions, i.e., water content (plasticizer), temperature, and pressure, approach starch gelatinization conditions, molecular motion of starch chains increase. Amorphous regions of starch can begin to be mobile and starch chains can associate to form double helixes, i.e., annealing of starch, as gelatinization conditions are approached. Increased or decreased crystallinity of starch granules can result from annealing depending upon processing parameters before, during and after the gelatinization step (Kuntson, 1990).

Gelatinization of native starch dramatically changes its functionality during processing of foods (Slade and Levine, 1995). Amorphous solids are plasticized (normally with water) and mobilized, crystalline solids are plasticized, melted, and mobilized, and some gelatinized starches are dispersed during the heating process (Table 1)(Waniska and Gomez, 1992). Gelatinization disrupts intra- and inter-molecular associations formed during synthesis and packing of starch molecules in the granule. Gelatinized starch is associated with 5 to 30 times its dry weight with water; it is a hydrated polymer, a hydrocolloid. The rigid, swollen, gelatinized, starch granules cause thickening (sol) or gelling (gel) effects in many food systems.

Table 1. ‘Dispersion’ of Gelatinized Normal Starch During Processing

Process (Sequence)	Amylose* (soluble)	Amylopectin* (soluble)*	Granule
Initially (excess water)	<5%	<2%	Rigid
+ Time + Temp.	30-40%	<10%	Rigid
+ Time + Temp. + Pressure-Shear	40-50%	10-50%	Deformed
+ Time + Temp. +++Pressure-Shear	50-60%	10-90%	Deflated

* Percent (%) of amylose or amylopectin dispersed and soluble in water.

Values in Table 1 vary with source, type and structure of starch and flour particles; but processing parameters correspond to amounts of starch dispersed and granule characteristics. Initially, amylose leaches from the gelatinized granule but amylopectin can be forced out of the gelatinized granule. More time, temperature, plasticizer, and/or pressure--shear are required to weaken the rigid starch granule, to cause deformations in the granule, and to cause granule contents to disperse. [Note: the term ‘pressure--shear’ represents the range of forces affecting starch during processing, where pressure refers to static forces and shear refers to dynamic forces]. More aggressive processing conditions (higher temperature, higher pressure--shear with sufficient moisture (plasticizer) content) cause gelatinized starch granules to disperse their contents (Table 1)(Waniska and Gomez, 1992). Molecular starch, starch dimers, starch aggregates, microgels of starch, and/or chunks of the gelatinized starch granule goes into the liquid phase of the food, when gelatinized starch granules disperse. The dispersion of gelatinized starch granules corresponds to a substantial decrease in viscosity. Hence, retention of the granular structure of gelatinized starch in food systems is the aim of many food processors.

Polymers of gelatinized starch immediately associate with other components in the food system. These associations can be described as tacky, sticky, or rubbery, especially if amylopectin is the principal dispersed polymer (Slade and Levine, 1995). This is the situation in foods prepared from waxy (mostly amylopectin) starches. Normally, some of the amylose leaches out of the granule and is the principal type of starch between gelatinized granules and other food components. Amylopectin, however, does not leach from the granule as quickly; and thereby, it’s concentration is enriched inside of the gelatinized granule during processing in ample water and less aggressive conditions. More aggressive conditions cause more amylopectin to be dispersed yielding products with a sticky or tacky characteristics.

Reassociation (retrogradation) of gelatinized starch occurs almost immediately after gelatinization. Stable hydrogen bonding between linear segments of amylose occurs post gelatinization in most food processes (Wu, et al., 1992). If the temperature is <115>oC , amylose quickly begins the retrogradation process to form an aggregate or a gel network depending upon concentration and amylose size. In many food systems amylose rapidly (within seconds or minutes) forms a gel network that traps amylopectin. The rapid ‘setting’ of the structure of bread, buns, and rolls are examples of amylose retrogradation. Lower temperatures of food during storage decreases the rate of formation of molecular associations between amylose molecules.

Stable hydrogen bonds between amylopectin molecules post gelatinization occur at <>oC. Many short chains of amylopectin slowly (in hours to days) form double helixes that pack into crystalline structures. Retrogradation of amylopectin gels occur at temperatures as low as -28 ^oC during weeks of storage.

All starch transformation mentioned above are ‘non-equilibrium’ processes (Biliaderis, 1991). This means that what occurs to starch does not happen instantaneously, and typical processing times may not be sufficient for an equilibrium to be achieved. Rates of these “non-equilibrium processes depend upon the conditions of time, temperature, plasticizer, and pressure-shear. Starches are very large molecules, i.e., 50,000 to 3,000,000 daltons for amylose and 500,000 to 50,000,000 daltons for amylopectin. Each glucose residue has several potential hydrophilic and hydrophobic interactions which translate to millions of inter- and intra-molecular interactions per starch molecule. Mobilizing a large polymer means disruption of thousands of intermolecular associations at about the same time. This is probably the reason that gelatinized starch granules retain some structure many degrees above their melting temperature even in excess water. Increased temperature, plasticizer, and/or pressure-shear, decrease the time of starch transformations, but a uniform extent of transformation is still not assured. Thus, understanding starch functionality requires information about how starch structures (granular and molecular) are affected by processing conditions to yield desired functional attributes, i.e., starch structure-process-function relationships.

Tools to Measure Starch Properties

What starch characteristics / properties are important? What methods provide information on how to optimize processing conditions and/or to maintain the quality characteristics of the product? These are questions that food scientists and starch chemists regularly address during product development, scale up, and manufacturing, and during storage and distribution of products.

Two categories of measurements, i.e., analytical and functional, provide insight into starch properties. Analytical measurements provide details of the chemical and physical properties of starch, but may not predict functionality in complex food systems during processing. Functional starch measurements can be related to processing parameters and product characteristics and shelf-stabilities. The problem with functional measurements are their interpretation, since conditions of measurement of non-equilibrium phenomena may not replicate processing conditions.

Analytical instruments provide information about fundamental attributes of starch. Differential scanning calorimetry (DSC) yields the temperature range and amount of energy required to melt crystalline regions of starch. Both native and retrograded starch contain crystalline regions which can be quantified by DSC. Gel permeation or size exclusion chromatography (SEC) columns can separate and appropriate detectors quantify amounts of amylose and amylopectin. Starch must be quantitatively extracted into heated methyl sulfoxide or cetyl trimethylammonium bromide solutions to yield analytical results. The molecular size and symmetry of amylose and amylopectin can be determined using viscometry and/or laser light scattering detectors connected to the SEC system. The swelling capacity of starch can be quantified using thermal mechanical analysis or by the concentration of molecules too large to enter the gelatinized starch granules. The viscosity of swollen granules can be determined using cone-and-plate rheometers. Several microscopic analysis methods provide information on size and shape of granules and interactions between granules.

Instruments measuring empirical, dynamic, and/or functional attributes of starch can provide information related to process and product characteristics. Simple measures of water solubility and water absorption using times and temperatures similar to normal processing conditions should relate to starch functionality. Measures of damaged starch by solubility in alkaline solution, susceptibility to enzymes, or change in size or shape using microscopy, relate to extent of processing and nutritional potential. Viscosity of starch (flour) as a function of solids contents can be measured using empirical viscometers at fixed or variable temperatures, i.e., temperatures that mimic cooking and cooling of the food. Modern instruments record viscosity using diverse heating and cooling profiles and stirring rates and yield data that should correspond to thermal treatments, pressures, pumping and shearing actions that occur during food processing. Textural measurements, e.g., adhesiveness, cohesiveness, yield stress, viscous flow, and rigidity, of starch sols and gels yield information about starch functionality during processing. These dynamic, empirical methods substantiate the non-equilibrium nature of starch functionality by yielding statistically different data using different measurement conditions.

Analytical methods can be used to measure starch functionality. SEC can quantify amylose and amylopectin solubilized outside of the starch granules (at each step of the food process), yielding amounts and molecular properties of soluble amylose and amylopectin interacting with other food components. DSC (Slade, et al., 1996) and differential mechanical analysis can be utilized in non-theoretical ways to determine pre- and postprocessing effects on starch swelling, melting, dispersion, and retrogradation; and thereby, acquiring functional information about starch functionality in low shear food systems.

Measuring Critical Functional Attributes of Starch

What are the critical functional attributes of starch in the formula, process, and product? Which analytical or functional methods approximate the critical functional attributes of the food system? How should these attributes be measured? I will discuss these concepts using data from several recent papers.

Foods are generally heated to gelatinize some or most of the starch to utilize starch functionalities of increased viscosity and gel formation. Heating foods to temperatures to achieve less than complete melting of starch yields less viscous gels that retrograde slower than foods with completely melted starch (Fig.1)(Fisher and Thompson, 1997). Retorted foods (temperature > 115 ^oC, to completely melt starch (Fan, et al., 1996a)) contain gelatinized starch that is more evenly distributed in the aqueous phase and which initiates retrogradation more slowly (Fig. 1). Rate and type (annealing vs retrogradation) of reassociation of heated starch depends upon extent of melting and dispersion and the process / storage conditions that promote/inhibit polymer mobility.

Many foods achieve temperatures near than the boiling point of water (100^oC). The starch crystals are melted in these foods, but only some of the gelatinized starch is leached or dispersed from the gelatinized granules (Fisher and Thompson, 1997). Hence, the food can contain an amylose enriched aqueous phase and an amylopectin enriched dispersed phase (gelatinized starch granules).

Reassociations of amylose and/or amylopectin occur quite rapidly in many food systems. Starch associations are the structural basis of most bakery products and are considered the cause of staling of these same bakery products. The immediate retrogradation of amylopectin of ae wx corn starch (Fig.1) after cooking (Fisher and Thompson, 1997), suggests that nucleation sites remain in the gelatinized starch or that some chain lengths of amylopectin have a propensity to associate. The rapid association of starch in corn tortillas (Fig. 2) (Fernandez, 1998) causes substantial changes in the swelling potential of gelatinized starch molecules and granules during the first hour after production. The initial viscosity exhibited below 75 ^oC decreased while the viscosity exhibited above 80 ^oC increased immediately out of the oven and during the first 24 hours of storage.

Long linear chains of glucose, e.g., amylose and longer chains of amylopectin, associate quicker to form more stable crystals than do the short chains of amylopectin (Goodfellow and Wilson, 1990; Yuan, et al., 1993). Hence, chain lengths of amylopectin, i.e., the nonreducing ends of branched amylopectin structure, affect local, intermolecular, and macromolecular functionality of the starch-based food.

Rate and extent of starch associations arise from differences in starch structure, i.e., chain length, molecular composition, and branching locations [as well as, the normal time, temperature, plasticizer, and pressure--shear processing conditions]. Different chain lengths are observed between and among (Fig. 3) starch sources (Villareal, et al., 1997). Other necessary aspects are where branches occur (frequency, proximity, and location) in the starch molecule and the 3-dimensional conformation of hydrated starches at different stages of retrogradation.

Molecular composition of starch that leaches from the gelatinized starch granules varies form what is retained within the granules (Bello, et al., 1995; Ong and Blanshard, 1995; Eerlingin, et al., 1997). Hence, functionality of leached starch should change as a function of the amount and type of starch distributed into the aqueous phase during processing. Methods to characterize the different properties of starch inside and outside of the gelatinized starch granules need to be utilized to understand the effects of processing parameters, as well as, ingredient functionality.

Gelatinization and retrogradation properties of starch are modified by chemical modification. Some corn endosperm mutants yield starch that functions like cross-bonded, phosphated starch (Yuan, et al., 1993). These observations support the effects of starch molecular structures on functionality and suggest that intermolecular associations can be increased or decreased by the combination of specific starches. Gel strength and retrogradation (Fig. 4) of some starch mixtures are synergist or antagonistic, not just additive properties (Obanni and Be Miller, 1997). Measurement and application of structure-process-function relationships will provide alternative solutions to chemical modification of starch.

Food ingredients affect the hydration, swelling, leaching, dispersion, granule integrity, pasting viscosity, and retrogradation of starch-based foods. Sucrose and lactose delayed pasting and decreased pasting viscosity more than did dextrose (Kim and Walker, 1992; Eerlingen, et al., 1994; Fan, et al., 1996a,b). Sugars' effects on starch functionality varied with the type of starch. Emulsifiers also delayed pasting but emulsifiers’ effects were modified by the amount of sugar present. Very low levels of sulfite decreases the rigidity of gelatinized starch granules and increases dispersion of starch molecules during processing of foods (Paterson, et al., 1996). Even higher levels of sulfite and lactic acid present during corn wet milling, yielded starch granules that had decreased rigidity of gelatinized starch granules and increased dispersion of starch during processing (Shandera and Jackson, 1996).

Processing conditions affect starch functionality in many food systems since every starch transformation is a ‘non-equilibrium’ process. Moisture content dramatically affects extrusion processing conditions and extrudate properties (Whalen, et al., 1997). Initial viscosity development of extrudates prepared using rice flour increased as moisture content went from 15 to 26%; but the pasting viscosity profile abruptly changed when 29% moisture was evaluated (Fig. 5). Pasting curves of extrudates of other cereals yielded the opposite results, i.e., lower initial viscosity development as moisture content increased (data not shown)(Whalen, et al., 1997). Obviously, starch structure and/or the matrix of particles in rice flour behave differently than those of other cereals. Again, documenting starch structure-process-function relationships are necessary to resolve day-to-day variations that we observe in manufacturing of all starch-based foods.

Vibrations, pulsating pumping action, shearing, etc. occur during most food processes and/or during transport. These dynamic physical motions can affect the dissolution of gelatinized starch or their reassociations (retrogradation), since every starch transformation is a ‘non-equilibrium’ process. Pulsations that occur at about a thousand cycles per minute, causes gently gelatinized amylopectin to increase viscosity (Fig. 6) and to become opaque (Dintzis, et al., 1996). Amylose did not participate in the increase in viscosity or opacity. Hence, dynamic measurement of gelatinized starch viscosities yields process information about product stability (and clarity).

Application of dynamic rheometry to food products has been limited due to the ‘theoretical’ basis of the method and problems of holding solid materials without slippage. Compression of solids along with the application of dynamic, oscillatory motions yields nontheoretical information about breads (Fig. 7) (Weipert, 1997). Apparent storage (E’) and loss (E”) moduli can be obtained over a range of shear rates and deformations. Both moduli increased during storage of bread, while both moduli were lower for softer products, i.e., wheat bread compared to rye bread. These apparent rheological values may not characterize theoretical properties of breads, but their application yields information consistent with empirical data from these samples. Documenting starch structure-process-function relationships yield better understandings of fundamental and empirical properties of ingredients, processes and products.

Summary

Starch undergoes dynamic transformations and interactions during processing into foods Measurement of these dynamic, non-equilibrium characteristics of starch is critical for the understanding of formulation, processing and product characteristics. Every starch transformation is a ‘non-equilibrium’ process and the processing history of the polymer affects its functionality. Rates of these “non-equilibrium processes depend upon the conditions of time, temperature, plasticizer, and pressure-shear.

Starch chemists and technologists apply analytical and functional methods to model systems. Analytical and functional methods , I predict, will be increasingly applied to complex food systems in theoretical and non-theoretical ways. This will generate more and, hopefully, better information about the critical attributes of starch functionality in food systems.

Warner-Bratzler Shear Force Measurement

Dave McKenna

The tenderness of meat is one of the most important factors influencing palatability. Considerable research over the past century has focused on understanding all aspects of meat tenderness. To do this accurately a number of mechanical devices were developed to aid in accurately differentiating tenderness differences.

The Warner-Bratzler shear measurement device is easily the most widely used and accepted method to determine the tenderness of meat. The basic theory and original design for the shear device was developed in 1928 by K.F. Warner, USDA research scientist. The original device was comprised of a thin steel blade with a circular hole in the middle, which would hold a meat sample, and a wooden miter box, which the steel blade would slide through. In 1932, L.J. Bratzler, a graduate student at Kansas State University, made a few modifications to the device to make it what it is today.

Bratzler is credited with standardizing the equipment used for the Warner-Bratzler shear device. The thickness of the steel blade was standardized at 0.04 inches thick, the wooden miter box was replaced with a steel apparatus with a slot that allows the steel blade to pass through with a clearance of 0.005 inches, and the rate at which the sample passes through the device was standardized to nine inches per minute. The shape of the steel blade and the hole in the center were both changed to be triangular, and the points of the triangular hole were rounded. The sample size of the meat product being sheared was standardized to be a cylindrical core with a one-half inch in diameter, and a parallel fiber orientation. Advances in engineering and electronics have allowed the Warner-Braztler shear device to be adapted to computerized devices.

Warner-Bratzler shear force values are the amount of force required to shear a one-half inch core of a meat sample, they are commonly reported in pounds or kilograms. What do these values mean? Initially, Warner-Bratzler shear forces values were used to establish differences in tenderness, that is a loin steak has a lower shear value (requires less pounds of force to shear) than a round steak. However, such comparisons did not determine if the loin steak was in fact “tender,” only that it was more tender than a round steak. Since then much work has focused on correlating Warner-Bratzler shear force values to consumer tenderness perceptions. Research conducted at Texas A&M University established tenderness threshold levels for Warner-Bratzler shear force values. For example, if beef loin samples had shear values of 7.0 lbs. (3.2 kg.) or less, researchers were 95% confident that consumers would find those steaks at least slightly tender. If the beef loin steaks had shear values of 8.6 lbs. (3.9 kg.), researchers were 68% confident consumers would find those steaks at least slightly tender. When these values were compared to consumer sensory data they found that a shear value of 10.1 lbs. (4.6 kg.) was 88% accurate at determining whether consumers would rate a steak at least slightly tough.

http://meat.tamu.edu/

Scanning Electron Microscope (SEM)

What is a SEM?

SEM stands for scanning electron microscope. The SEM is a microscope that uses electrons instead of light to form an image. Since their development in the early 1950's, scanning electron microscopes have developed new areas of study in the medical and physical science communities. The SEM has allowed researchers to examine a much bigger variety of specimens.

The scanning electron microscope has many advantages over traditional microscopes. The SEM has a large depth of field, which allows more of a specimen to be in focus at one time. The SEM also has much higher resolution, so closely spaced specimens can be magnified at much higher levels. Because the SEM uses electromagnets rather than lenses, the researcher has much more control in the degree of magnification. All of these advantages, as well as the actual strikingly clear images, make the scanning electron microscope one of the most useful instruments in research today.

How does a SEM work?

Diagram courtesy of Iowa State University SEM Homepage

The SEM is an instrument that produces a largely magnified image by using electrons instead of light to form an image. A beam of electrons is produced at the top of the microscope by an electron gun. The electron beam follows a vertical path through the microscope, which is held within a vacuum. The beam travels through electromagnetic fields and lenses, which focus the beam down toward the sample. Once the beam hits the sample, electrons and X-rays are ejected from the sample.

Detectors collect these X-rays, backscattered electrons, and secondary electrons and convert them into a signal that is sent to a screen similar to a television screen. This produces the finalimage.

How is a sample prepared?

Because the SEM utilizes vacuum conditions and uses electrons to form an image, special preparations must be done to the sample. All water must be removed from the samples because the water would vaporize in the vacuum. All metals are conductive and require no preparation before being used. All non-metals need to be made conductive by covering the sample with a thin layer of conductive material. This is done by using a device called a "sputter coater."

The sputter coater uses an electric field and argon gas. The sample is placed in a small chamber that is at a vacuum. Argon gas and an electric field cause an electron to be removed from the argon, making the atoms positively charged. The argon ions then become attracted to a negatively charged gold foil. The argon ions knock gold atoms from the surface of the gold foil. These gold atoms fall and settle onto the surface of the sample producing a thin gold coating.

Sumber: Scanning Electron Microspcope

Limiting Growth: Microbial Shelf-Life Testing

By: Michael S. Curiale, Ph.D., 1988

Just about every consumer has encountered spoiled food, whether it was moldy bread, soured milk, bad fish or the things formerly called "leftovers" hiding in the nether regions of the refrigerator. If any of these were eaten, a negative physiological or psychological reaction might have followed. If pathogenic organisms were present, an unforgettable bout with some uncomfortable gastrointestinal malady may have resulted. And in rare cases, foodborne pathogens can prove deadly. However, the presence of pathogens is not always signaled by food spoilage. Still, the risk of an encounter with either spoiled or dangerous foods can be significantly reduced by knowing and understanding shelf life and stability.

Shelf life represents the useful storage life of food. At the end of shelf life, food is developing characteristics -- changes in taste, aroma, texture or appearance -- that are deemed unacceptable or undesirable. The underlying cause for the change may be microbiological, chemical or physical. Microbiological spoilage is exemplified by the above attributes. Examples of chemical and physical deterioration include rancidity and freezer burn.

Establishing the microbiological shelf life for many foods becomes important at some point in their history. The determination may be required during product development, after they have been established on the market, or at some time in between. The reasons behind determining shelf life range from product design goal, to formulation change, to packaging or storage change, to changes in microbiological criteria, or a simple desire to know. Regardless of the when or why, numerous variables must be considered in the experimental design of the shelf-life study to approach a useful result.

Spoilage susceptibility

Microorganisms possess specific growth requirements for temperature, moisture, acidity, nutrients and time. For microorganisms to grow, cultural conditions must be within a certain range. If minimum conditions are not satisfied, growth will not occur.

In general, organisms grow at temperatures between 0° and 55°C, at pH values between 2 and 10, and at water-activity levels greater than 0.6. These limit ranges are not absolute, and the boundaries around them are not usually sharply defined. Optimal growth generally occurs in the middle region of the various ranges, and slows as the boundaries are approached. Nutrients are not limiting in most foods, but inhibitory substances may block proper utilization of the food. Oxygen is required for the growth of some organisms. For others, it is optional, and for still others, it is a poison. Oxygen and other gases are available from the atmosphere or from air trapped in the product. By manipulating the food's composition, pH, water, etc., different groups of organisms are either activated or inactivated, and their growth rates are either accelerated or slowed.

Assessing a food item in terms of its microbial growth requirements makes it possible to determine its potential for spoilage. However, studies are generally required to confirm expectation.

Qualifying criteria

The taste, odor and appearance of a food are the ultimate criteria used by consumers to judge a food's acceptability. In the laboratory as well, organoleptic evaluation of a food is a direct method for determining shelf life. The food is prepared and periodically examined for changes in appearance, aroma, texture and taste until it becomes unacceptable. The organoleptic determination is easily accomplished by those familiar with the product's desired characteristics. Shelf life based on organoleptic analysis, however, may vary significantly from consumer to consumer, since tastes, expectations and ability to detect changes differ greatly.

The organoleptic quality of food changes as its micro-flora -- bacteria, yeast and mold -- grow and metabolize available nutrients. The sensory changes at first might be subtle, but they eventually make the food unacceptable. Generally, sensory changes are not detectable until the microbial population is high. The number of organisms required to cause spoilage varies with the food item and the type(s) of microorganisms growing in it. Shelf life may be estimated on the basis of microbial density. As a rule of thumb, 10 million bacteria per gram, 100,000 yeast per gram, or visible mold, signal the end of microbiological shelf life. Noticeable degradation of the product is likely at these levels. Whether the changes are acceptable is determined by the organoleptic evaluation.

High numbers of microorganisms are normal in certain foods, but indicate deterioration in other foods. Therefore, it is desirable to know, even in the absence of objectionable organoleptic changes, the microbiological state of food as it nears the end of shelf life. For the delivery of a product with maximum quality, the shelf life of a product should be determined by organoleptic and microbiological examination.

Designing a study

Many factors must be considered when designing a microbiological shelf-life study. Among these are: temperature, water content, time, types of microorganisms, suitability of analyses, sampling and replication. Shelf-life studies for each product should be designed specifically for that product because of the number of variables that must be considered.

Temperature. Of the factors influencing microbial growth -- water, acidity, temperature, nutrients, preservatives and atmosphere -- all but temperature become essentially fixed at the time of product formulation, processing and packaging. Normally, these factors are not intentionally altered in a shelf-life study. Storage temperature usually determines the length of microbiological shelf life of perishable foods.

In general, as the temperature increases, the microbial growth rate increases. At temperatures near freezing, organisms either grow very slowly or not at all. As the temperature increases toward the optimum, metabolic activity and growth rate increase. At this temperature, growth is fastest. As the temperature increases beyond the optimum, the growth rate begins to slow. At some maximum temperature, growth stops and higher temperatures begin to kill the cells. Each species of organism has a different minimum, optimum and maximum growth temperature range. Moreover, differences may be observed among isolates of the same species. The important point about temperature and growth is that when the storage temperature of a product changes, not only does the shelf life change, but the types of spoilage flora also will likely change.

Because of the important relationship between growth rate and storage temperature, the most useful shelf-life information is obtained for product kept at its intended storage temperature. Refrigerated products are stored in the refrigerator, and room temperature products are stored at ambient conditions. Small changes in storage temperature may have a significant effect on shelf life. A few degrees may determine the difference between good shelf life and premature spoilage.

Unfortunately, in the real world, refrigerator and room temperatures are not standardized. Refrigeration can mean anything from 28° to 55°F, and room temperature might fall anywhere between 60° to 95°F. Shelf life at 30°F may be very different from that at 50°F, although both temperatures may represent refrigeration conditions. To produce a meaningful study and to compare different studies, temperatures used must be known. This is most easily accomplished if the study temperatures are fixed and not varied. Temperatures of 40°F (4°C) and 75°F (24°C) are commonly used for refrigerator and room temperature storage, respectively.

In the real-world conditions of refrigeration during distribution and retail presentation storage of perishable foods, temperatures often cycle between low and high temperatures. Temperature cycling in laboratory studies of shelf life introduces conditions that make data interpretation difficult, and temperature cycling usually is not recommended. A significantly better understanding of shelf life can be obtained when several storage temperatures are used. For refrigerated foods, studies may be conducted at fixed temperatures in each of three ranges (38° to 40°F, 45° to 50°F, and 50° to 55°F). Useful room temperatures are 75°, 85° and 95°F. From the information gained, inferences can often be made about other temperatures.

Water. Water level determines the characteristics of many foods. Some foods are expected to be dry, some appear moist, and others obviously contain water. Water is essential for microbial growth, and if the amount of free water changes, a food's susceptibility to spoilage may change. For example, if a dry product that is resistant to spoilage becomes damp, it will likely spoil. In contrast, a moist food will not spoil if it dries. Food packaging plays an essential role in the control of moisture, and has a significant effect on shelf life. There is exchange of moisture between the atmosphere and the food. This exchange continues until the food reaches equilibrium with the atmosphere.

Hermetically sealed packages contain a limited amount of air, and the smaller the head space, the quicker equilibrium is attained between food and air. For hermetically sealed samples, humidity control need not be considered as a study variable as long as the package remains intact.

Most foods are packaged to limit the rate of water exchange so that little moisture exchange occurs during the life of the product. Thus, humidity control and/or monitoring is required mainly for foods that are: subjected to temperature extremes; exposed to the atmosphere (such as cakes, pies and pastries); or packaged in air-permeable containers. Relative humidities of 40%, 60% and 80% represent a practical range for experimentation.

Duration. A study's duration should at least match the target shelf life for the food being considered. If a 60-day shelf life is desired for a refrigerated item stored at 40°F, the study should be designed for a minimum of 60 days. Similarly, if six months is expected at room temperature, then the study should be at least that long. A study may be designed to exceed the shelf-life goal if expectations are met and the point of spoilage needs to be determined.

If a product fails halfway through a designed shelf-life study, there is little point in continuing the analysis. On the other hand, if the product is stable during one segment of a study (for example, no microbial activity is observed), the study should be continued to the next segment. Sterile products do not require repeated testing beyond the time expected for outgrowth of any contaminating microorganisms. It is not unusual for microbial levels to stay constant, and even decrease, over a period of hours, days or weeks before beginning to increase.

The microbiological shelf life of a food designed to be stored at one temperature cannot be confidently determined more quickly by storing the food at a higher temperature because microbial growth is influenced by temperature. While it is true that organisms grow faster when warmer, it is not yet possible to predict the result for another incubation temperature. For rough estimation, a two- to four-fold increase in growth rate is estimated for an 18° to 20°F temperature increase.

If the shelf life was found to be 10 days at 60°F, at 40°F, it is estimated to be 20 to 40 days. This broad range for a prediction is not very useful. Moreover, it is entirely possible that the organisms that grew at the elevated temperature (60°F) do not grow, or are not the main spoilage organism, at the desired storage temperature (40°F). For these reasons, accelerated microbiological shelf-life predictions are not useful.

Methodical approach

Microbial growth in foods for estimation of shelf life is most commonly monitored using agar plating procedures. The procedures are quantitative for the number of viable organisms present at the time of analysis. Because of differences in growth requirements among the different types of microorganisms that may be found in food, no single procedure is available to enumerate all microorganisms. However, a simple, useful procedure is the aerobic plate count, which detects organisms that form colonies on plate count agar usually incubated at 35°C for 48 hours.

Many organisms are not detected using mesophilic incubation of the aerobic plate count. These include: organisms that grow only at low or high temperatures; most lactic acid bacteria; strict anaerobes; and yeast and mold. Thus, the plating procedures are usually selected on the basis of the type or types of organisms anticipated or known to be present in the food. If the "right" procedures are not selected, it is very possible to have obvious microbiological spoilage, but no experimental data to support the organoleptic observations.

Sensible sampling

How often a food is analyzed for microorganisms during the shelf-life study must be decided with care in order to detect significant microbiological events. To better understand why this is important, the typical growth cycle of a population of microorganisms should be understood. The growth cycle consists of four phases. The beginning of the cycle is the "lag phase." Increases in cell numbers are not observed during this time. In the second phase, the cell number increases exponentially: one cell becomes two, then four, and so on. In the stationary phase, neither the rate of growth nor the number of cells continues to increase. Growth stops at a density usually not exceeding 1,010 bacterial cells or 106 yeast cells per gram. The final phase of the cycle is aptly called the "death phase," since cell viability decreases. Another cycle will not begin until the cells are diluted into a fresh growth medium, such as food.

During the time the microorganisms in food are in the lag phase, the food appears to be microbiologically stable. Once the cells enter into the growth phase and begin to multiply, the product begins to change and is considered unstable. At some point along the microbial growth curve, the food usually will spoil. Therefore, for shelf life, the significant points concerning the microbial growth cycle are: the duration of the lag phase; the growth rate; and the microbial count at the end of the growth phase. The end of shelf life -- 10 million bacteria or 100,000 yeast per gram -- usually occurs near the end of the growth phase.

To identify the different transition points along the growth path, the food is sampled periodically to quantify the number of organisms present. An excessive period between samplings increases the risk of under- or over-estimating shelf life. The more analyses that are completed, the more accurate will be the shelf-life determination. For most foods, the anticipated shelf-life time is divided into five to 12 intervals for sample collection and analyses. The number of intervals chosen is generally an estimation based on experience with similar foods.

The distribution of microorganisms in a sample of food, or even between samples of food from the same production lot, is not necessarily uniform. For example, if one in five bottles of food solution contains a spoilage organism, then only one of five may display evidence of spoilage. In another example, a spoilage organism present in a solid or viscous food may exhibit localized spoilage while another area without the organism is free of spoilage. Sampling plans must take into account the possible distribution of microorganisms within the lot. This is especially critical when the initial levels are lower than 10 cells per gram, which is the normal sensitivity of the agar plating procedures used for analysis. Single packages represent the most easily distinguishable analytical unit.

Conducting a meaningful study requires fewer samples if an even distribution of organisms exists in the product. For the homogeneous product, each analytical unit is more likely to be identical to the next. For example, liquids are homogeneous if carefully mixed each time before sampling. Each unit of liquid will represent the content of the whole. However, in an unmixed sample, the distribution from top to bottom or side to side might be uneven. In a viscous sample, thorough mixing may not be possible, resulting in a non-uniform distribution of organisms. Any one sample may not be typical of the whole product lot. For these products, multiple subsamples need to be analyzed to represent the whole. Generally, at least three carefully selected samples of a heterogeneous product are needed to obtain an acceptable representation of microbiological activity in the product.

A shelf-life study conducted on a single batch of food is valid for that food and any other production lot that is identical. If the microorganism type or number differs significantly among batches, shelf-life duration may differ. Replication of the study always will enhance the accuracy of the prediction. Periodic determinations of shelf life help to provide assurance that the product remains consistent over time with respect to spoilage rate. Changes in formulation, processing and packaging conditions call for reevaluating a product's shelf life.

Making a challenge

A food may exhibit an exceptionally long shelf life even though the temperature, pH, water and nutrient levels permit microbial growth. The long shelf life may result from the absence of microorganisms in the samples tested, or it may occur because the contaminating organisms will not grow in the particular product formulation. Understanding the stability of these foods in the event of a chance contamination requires a microbiological shelf-life study in which a product is challenged by inoculating it with appropriate spoilage organisms.

In a challenge study, the product is inoculated with known spoilage microorganisms. The inoculated samples are then treated and stored in accordance with the shelf-life study guidelines. Adding organisms to the foods adds several more variables to the study. The types of organisms and the number of strains of each type to be used need to be decided. In addition, an inoculation level must be selected. The spoilage organism used in the challenge study is usually one that has been isolated previously from similar foods that have spoiled. For example, lactobacilli and yeast are the most common spoilage organisms of salad dressings and sauces. The more isolates included in the challenge study, the greater will be the confidence in the accuracy of the shelf-life assessment. In practice, five isolates of lactobacilli, five of yeast, and five of mold represent a reasonable selection for a salad-dressing challenge study.

The number of organisms added to the food is generally significantly higher than what would normally be found as a result of contamination during processing. The inoculation levels used are generally greater than 10 per gram, offering easy observation of the presence of the challenge organisms; 10 organisms per gram represents the limit of sensitivity of the agar plate count procedures normally used for enumeration. Lower levels can be detected, but usually at significantly greater expense and with lower accuracy.

When the level of the challenge organisms does not increase during shelf-life storage, the product formulation is resistant to microbial growth. It is stable in the sense that the number of microorganisms does not increase. However, if the organisms are present in sufficient number, it is still possible that the metabolic activity of the nongrowing cells will cause undesirable changes in the product.

In most foods susceptible to spoilage, the organisms do not begin to multiply immediately. Instead, the count remains relatively constant for a period of time before growth is observed. The period of no growth is analogous to the lag phase of the microbial growth cycle. A fraction of the challenge organisms may die soon after being added to the test sample.

If the sample has a low initial inoculation level and die-off occurs, one might incorrectly conclude that the product is stable. Using high inoculation levels will prevent this error. A level of about 10,000 cells per gram is useful for observing either decreases or increases in levels, even if an initial 100-fold die-off is observed.

Die-off after inoculation most likely results from shock caused by an abrupt change in environment for which the cells are not preconditioned. The die-off can sometimes be avoided or reduced by first adapting the organisms to the product's nutrients, acidity or water activity. In the real world, contamination of product by both unadapted and adapted organisms occurs. The use of organisms that are not specifically adapted for growth in the product simulates organisms originating in the environment and entering the food through contact. Adaptation simulates product-to-product contamination.

Challenge studies using pathogens are conducted to measure the behavior of those microorganisms in foods and formats similar to studies in which spoilage microorganisms are used. The purpose for using pathogens is to measure their growth, inhibition or die-off in a food. Commonly used pathogens are Salmonella, Listeria monocytogenes, Staphylococcus aureus, Bacillus cereus, Clostridium perfringens, Yersinia enterocolitica, Clostridium botulinum, and Escherichia coli. If the pathogens do not grow, the food is considered stable with respect to the ability of the food system to inhibit their growth.

Inhibiting changes in the organism's environment influences the duration of the lag phase of the pathogens. The greater the inhibition, the longer the lag phase. Even shifts in incubation temperature between that used to propagate the organism for the study and the storage temperature of the product may change the length of the lag period. Therefore, the organisms' preparation conditions must be carefully chosen to account for a study's specific needs.

Mathematical modeling

The influences of atmosphere, temperature, water, pH, preservatives and nutrients on the microbial growth are easily measured. Collecting sufficient data makes it possible to derive a mathematical equation of growth. This could allow a quick estimation of shelf life by plugging the required variables for the food into the equation. Mathematical models that include some of the growth-controlling variables for bacterial pathogens are available. The models are interesting, but not necessarily accurate when applied to foods. They are useful for playing "what if" games, such as: "How much longer is the growth of Salmonella delayed by decreasing the pH of the food from 5.6 to 5.4?" Future refinements will most certainly make models more useful. However, a long time will pass before they can reliably replace experimental shelf-life studies.

Accurate prediction of shelf life necessitates a carefully planned and executed series of experimental studies. Shelf life should be reevaluated in the event ingredient, formulation, processing, packaging or storage changes are anticipated. The knowledge gained from these studies reliably promotes confidence that the product delivered to the customer is safe and of high quality.

Website: www.foodproductdesign.com

Sensory Analysis and Shelf-Life Testing

Lynn A. Kuntz, 1993

If there is one thing everyone agrees on regarding the use of sensory analysis in shelf life testing, it's that sensory is one of the best tools available. From there, the paths of the experts may diverge in the search to implement the best program. However, ultimately they all reach the same place: assurance that the products tested will meet a high level of consumer acceptance for a specified period of time.

Begin Communications

Before the paths diverge, the experts all concur on the place to start. Communication between sensory, product development, analytical, marketing, packaging and other pertinent groups is crucial.

"The more information sensory has about a product and the purpose of a project, the better they can design a test which answers the correct questions in the most efficient manner," states Rebecca Newby, manager of sensory projects, Tragon Corp., Redwood City, CA. It is important to know the objectives of the project -- whether it's the development of a new product or process, seeking an alternate ingredient or determining the best packaging material."

Follow Procedures

"Almost all forms of sensory evaluation methods can be used in shelf life evaluation," says Gail Vance Civille, president, Sensory Spectrum, Chatam, NJ. Specifically, the appropriate methods include:

-- Discrimination Tests. These can be performed by untrained panelists or by those specifically screened for an ability to detect a specific difference. "We use people who are sensitive to off-flavors and have good color perception," notes David Ash, vice president of research and development, Del Monte Foods, Walnut Creek, CA. "They can identify things that become the limiting factor in a product's shelf life. No one is on a panel unless they like that type of product."

These tests are used when it is obvious what product characteristic has changed, since the method gives no information regarding the type of difference.

Difference panels require approximately 30 to 50 panelists. According to Dr. Susan Cuppett, associate professor at the University of Nebraska's Department of Food Science, Lincoln, NE, "too high a number of panelists can bias as well as too low. If you have more than a hundred people, statistically the numbers begin to skew one way or another. It's a misconception that the higher the numbers, the better the results."

-- Duo/Trio tests use three samples, one of which is different. One of the matching samples is labeled as the reference, and the panelist is asked which of the two other samples matches the reference sample.

-- Triangle tests use three samples, one of which is different. The panelist must determine which one of the three samples is the different one. This test enjoys a slight advantage over the duo/trio as it requires a smaller number of tests to achieve statistical significance.

-- Descriptive Tests. Quantitative descriptive analysis (QDA) or flavor profile analysis (FPA) must be performed by a trained panel so that the terms mean the same thing to each of the panelists. The training can be costly in terms of time -- an expert panel has to be trained for a specific type of product.

"If you require detailed information -- what attributes have changed with time and how -- descriptive techniques are extremely valuable," says Cuppett.

Panel sizes are small, typically around ten. Cuppett recommends training one or two additional people as alternates in cause they're needed.

"Sometimes panelists get off track and must be retrained. If they are unable to retrain, you might drop their evaluations and go to an alternate."

-- Affective tests. Hedonic scales -- which indicate acceptance on a nine point numerical scale labeled from "dislike extremely" to "like extremely" are typically used for shelf-life evaluations. These tests can be worded to not only show the overall acceptance of the product, but that of specific characteristics such as flavor and texture. Trained panels can also use this technique on a line scale which can be converted to numerical equivalents.

Paneling the tests

The evaluation technique may vary, depending on the resources available and the information needed. The panelist contingent can vary according to the requirements of the test and the evaluation itself: experts, employees, consumers. However, another point of agreement shows up regarding the panelists.

"We make a point not to have project people on the panel to limit the bias," states Ash. Newby agrees, "People are biased when they know something about the product; the only way to remove the bias is to test on a blind basis. But you can use a pragmatic approach -- sensory testing is expensive. Tabletop panels can be used for screening and if the product is obviously unacceptable you can avoid unnecessary testing."

Using your control

There are various camps when it comes to using a control product. Some sensory experts prefer a physical control; others are satisfied to just use the numbers obtained in the zero time evaluation. According to Civille, there are three alternatives when using a physical sample as a control.

-- Making the control from scratch each time using the same ingredients, procedures, etc. if it's a simple mix.

-- Freezing the control and accepting that it might have changed slightly, but minimally compared to the product in shelf life.

-- Using a fresh batch of product which may not be identical.

Civille believes that one of the problems with doing a shelf life without a control is that "consumers may be rating it in the context of a similar product on their shelf which may not be fresh either. They may not be as critical as if there was a control to evaluate."

Ash suggests that the best conditions for preserving control product is to hold frozen product at a constant -10 degrees F temperature and shelf-stable products at 35 degrees F. This limits any product changes due to phase changes, such as water or fat crystallization, and in general, retards product deterioration.

The age of the control or zero-time product for evaluation varies with the product. The product may be freshly prepared or manufactured. However, the persons with the responsibility of defining the product concept may choose to set the "zero-time" evaluation at the time at which a product reaches equilibrium. This is possible with a multiphase product subject to water, oil or flavor migration. The zero-time can also be established at the time the product typically reaches the consumer to avoid testing against a product, that in reality, the consumer will never see.

Moving and Storage

The storage conditions for an ambient shelf-life study should mimic those it will encounter in real life. That includes not only temperature and freeze/thaw cycles, but also factors such as humidity, light, packaging and handling.

"It's impossible to mimic every condition the product will ever encounter," notes Peter Putnam, sensory analyst, McCormick & Company, Inc., Hunt Valley, MD. "Therefore, it's important to test the range of conditions they're likely to encounter. Then anytime the product actually falls into that set of conditions, you can be fairly certain that it won't fail."

Deciding what the proper storage conditions entail should be the responsibility of the product development person or team, not just the sensory analyst, offers Civille. Accelerated conditions may be helpful, if there is a good correlation between shelf-life curves under those conditions and those under ambient conditions for similar products.

"But don't assume that every line extension will have the same shelf life as the original," warns Civille.

Another point to which everyone readily agrees is to store more product than you think you'll need for the study. Estimates range from 25 to 50% more. This is to provide product for retest or other emergencies, and to provide a pool of product to insure random selection. Make certain that each single unit put into storage is properly labeled to avoid sample mix-ups.

Finding the End

When a product is no longer considered acceptable, it has reached it's endpoint. But where is that point set?

"There's no government regulation defining the product endpoint," explains Newby. "There's a microbiological shelf life, but you must be much more stringent than that. At what point does consumer acceptance decrease or does the product change so that there is a noticeable difference? These are dependent on your corporate objectives and how much risk the company is willing to take with the brand."

Rarely does a company use the criterion of no detectable change. Often the endpoint is established at a certain number or a specific drop in consumer acceptability. The product should fail when it no longer represents the product concept.

The Replacements

Because of the scope of product development at most companies, the sensory department could devote 110% of its time to shelf-life studies. To relieve the burden of continuous shelf-life studies, there are a few remedies. If the shelf life can be estimated with any accuracy, the test intervals can be lengthened and clustered around the expected failure period. Most of the experts only require about six evaluations to provide reliable results. In some cases, four may be adequate. Monthly evaluation of a product with an estimated shelf life of one year can be overkill unless there is a valid reason for closely studying the changes in product characteristics, such as the establishment of an accelerated shelf life curve.

Another way to cut the through the sensory/shelf-life log jam is to rely on chemical or instrumental analyses that closely relate to sensory analysis. Moisture, free fatty acids or color measurement can supplement the sensory techniques.

"If you have developed a relationship between an instrumental method and the shelf life of a product, use it!" urges Newby. "They're usually less expensive and time consuming than sensory."

Putnam notes that a correlation between a physical or chemical test can increase the confidence level of the sensory results. Most sensory experts agree that analytical methods should complement the sensory tests. If not used as a complete substitution, the baseline and endpoint evaluations should be confirmed by sensory techniques. Still, analytical techniques often are overlooked.

"Things that are not sensory attributes are often overlooked," observes Putnam. "Functionality of the product or the packaging may not be examined if shelf life is considered solely a sensory function."

For example, if the whipped topping mix still has favorable sensory scores, but only whips to half of its expected volume, it may have reached a functional endpoint rather than a sensory one.

Used correctly, sensory can measure how a product changes over time.

"It's better not to conduct a shelf life study than to conduct a poorly designed one. You can spend a lot of time and resources and come up with nothing, or worse yet, the wrong answer," says Putnam.

And that can result in more than wasted time, it may produce a marketplace embarrassment. So, make sure you're headed down the right path.

Website: www.foodproductdesign.com