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this-is-my-main-i-follow-from · 1 year ago

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Chef WK, lead charcuterie specialist in Alberta Canada

Table of contents

1. Control Program Requirements for Fermented Meat Products

2. Facility and Equipment Requirements

3. Starter Culture

4. Chemical Acidification

5. Water Activity Critical Limits

6. Time and Temperature for Fermented Products

7. Fermentation Done at a Constant Temperature

8. Examples of Degree-hours at constant room temperatures

9. Fermentation Done at Different Temperatures

10. Fermentation done at Different temperatures

11. What happens if fermentation fails to hit critical limit?

12. E. coli and Salmonella Control in Fermented Sausages

13. Options for E. coli validation

14. Option1; Heating

15. Option 2; pH, heating, holding, diameter

16. Safety and consistency

Control Program Requirements for Fermented Meat Products

The producer must have a program in place to assess the incoming product. This program should outline specifications for the incoming ingredients. This may include criteria including receiving temperature, farm/ supplier, lot code or packed on date, species/cut etc.

2. Facility and Equipment Requirements

Equipment used in the fermentation process must be included in the operator's prerequisite control programs. These must include the following elements:

Temperature in the fermentation, drying and smoking chambers must be uniform and controlled to prevent any fluctuation that could impact on the safety of the final product.

Fermentation, drying and smoking chambers must be equipped with a shatter resistant indicating thermometer, (or equivalent), with graduations of 1°C or less. If mercury thermometers are used, their mercury columns must be free from separations. All thermometers must be located such that they can be easily read.

Fermentation and smoking chambers must be equipped with a recording thermometer for determining degree-hours calculations in a reliable manner. Recording thermometers are also preferable in drying and aging rooms but, in these rooms, it may be sufficient to read and record the temperatures 2 times a day.

Drying and aging rooms must be equipped with humidity recorders in order to prevent uncontrolled fluctuations of the relative humidity. The only alternative to an automatic humidity recorder in these rooms would be for the company to manually monitor and record ambient humidity twice a day (morning and afternoon) every day with a properly calibrated portable humidity recorder.

For routine monitoring, accurate measurement electronic pH meters (± 0.05 units) should be employed. It is important that the manufacturer's instructions for use, maintenance and calibration of the instrument as well as recommended sample preparation and testing be followed.

When the aw of a product is a critical limit set out in the HACCP plan for a meat product, accurate measurement devices must be employed. It is important that the manufacturer's instructions for use, maintenance and calibration of the instrument be followed.

3. Starter Culture

The operator must use a CFIA approved starter culture. This includes Freeze-dried commercially available culture as well as back-slopping (use of previously successful fermented meat used to inoculate a new batch). When performing back-slopping, the operator must have a control program in place to prevent the transmission of pathogens from when using the inoculum from a previous batch to initiate the fermentation process of a new batch. These must include:

The storage temperature must be maintained at 4°C or less and a pH of 5.3 or less.

Samples for microbiological analysis must be taken to ensure that the process is in line with the specifications.

The frequency of sampling is to be adjusted according to compliance to specifications.

Any batch of inoculum which has a pH greater than 5.3 must be analysed to detect at least Staphylococcus aureus. Only upon satisfactory results will this inoculum be permitted for use in back slopping.

This can be an expensive and a time exhaustive process and is generally avoided due to food safety concerns. AHS does not allow back-slopping.

[Chef WK was in communication with the U of A to get his method, a starter mix, studied.]

4. Chemical Acidification

If product is chemically acidified by addition of citric acid, glucono-delta-lactone or another chemical agent approved for this purpose, controls must be in place and records kept to ensure that a pH of 5.3 or lower is achieved by the end of the fermentation process. These acids are encapsulated in different coatings that melt at specific temperatures, which then release the powdered acids into the meat batter and directly chemically acidulate the protein.

Summer sausage is a very common chemically acidified product. The flavor profile tends to be monotone and lacking depth.

5. Water Activity Critical Limits

The aw may be reduced by adding solutes (salt, sugar) or removing moisture.

Approximate minimum levels of aw (if considered alone) for the growth of:

molds: 0.61 to 0.96

yeasts: 0.62 to 0.90

bacteria: 0.86 to 0.97

Clostridium botulinum: 0.95 to 0.97

Clostridium perfringens: 0.95

Enterobacteriaceae: 0.94 to 0.97

Pseudomonas fluorescens: 0.97

Salmonella: 0.92 - 0.95

Staphylococcus aureus: 0.86

parasites: Trichinella spiralis will survive at an aw of 0.93 but is destroyed at an aw of 0.85 or less.

The above levels are based on the absence of other inhibitory effects such as nitrite, competitive growth, sub-optimum temperatures, etc., which may be present in meat products. In normal conditions, Staphylococcus aureus enterotoxins are not produced below aw 0.86, although in vacuum packed products this is unlikely below aw 0.89.

6. Time and Temperature for Fermented Products

Certain strains of the bacteria Staphylococcus aureus are capable of producing a highly heat stable toxin that causes illness in humans. Above a critical temperature of 15.6°C, Staphylococcus aureus multiplication and toxin production can take place. Once a pH of 5.3 is reached, Staphylococcus aureus multiplication and toxin production are stopped.

Degree-hours are the product of time as measured in hours at a particular temperature multiplied by the "degrees" measured in excess of 15.6°C (the critical temperature for growth of Staphylococcus aureus). Degree-hours are calculated for each temperature used in the process. The limitation of the number of degree-hours depends upon the highest temperature in the fermentation process prior to the time that a pH of 5.3 or less is attained.

The operator is encouraged to measure temperatures at the surface of the product. Where this is not possible, the operator should utilize fermentation room temperatures. The degree hour calculations are based on fermentation room temperatures. Temperature and humidity should be uniform throughout the fermentation room.

A process can be judged as acceptable provided the product consistently reaches a pH of 5.3 using:

fewer than 665 degree-hours when the highest fermentation temperature is less than 33°C;

fewer than 555 degree-hours when the highest fermentation temperature is between 33° and 37°C; and

fewer than 500 degree-hours when the highest fermentation temperature is greater than 37°C.

This means that as the temperature increases, the amount of time that you have available to reach 5.3 or under is shorter. The warmer the temperature, the sharper the log growth phase of bacteria, which equates to more overshoot in lactic acid production, faster.

8. Examples of Degree-hours at constant room temperatures

Example 1:

Fermentation room temperature is a constant 26°C. It takes 55 hours for the pH to reach 5.3.

Degrees above 15.6°C: 26°C - 15.6°C = 10.4°C Hours to reach pH of 5.3: 55 Degree-hours calculation: (10.4°C) x (55) = 572 degree-hours

The corresponding degree-hours limit (less than 33°C) is 665 degree-hours.

Conclusion: Example 1 meets the guideline because its degree-hours are less than the limit.

Example 2:

Fermentation room temperature is a constant 35°C. It takes 40 hours for the pH to reach 5.3.

Degrees above 15.6°C: 35°C - 15.6°C = 19.4°C Hours to reach pH of 5.3: 40 Degree-hours calculation: (19.4°C) x (40) = 776 degree-hours

The corresponding degree-hours limit (between 33 and 37°C) is 555 degree-hours.

Conclusion: Example 2 does not meet the guideline because its degree-hours exceed the limit

9. Fermentation Done at Different Temperatures

When the fermentation takes place at various temperatures, each temperature step in the process is analyzed for the number of degree-hours it contributes. The degree-hours limit for the entire fermentation process is based on the highest temperature reached during fermentation.

Example 1:

It takes 35 hours for product to reach a pH of 5.3 or less. Fermentation room temperature is 24°C for the first 10 hours, 30°C for second 10 hours and 35°C for the final 15 hours.

Step 1

Degrees above 15.6°C: 24°C - 15.6°C = 8.4°C Hours to reach pH of 5.3: 10 Degree-hours calculation: (8.4°C) x (10) = 84 degree-hours

Step 2

Degrees above 15.6°C: 30°C - 15.6°C = 14.4°C Hours to reach pH of 5.3: 10 Degree-hours calculation: (14.4°C) x (10) = 144 degree-hours

Step 3

Degrees above 15.6°C: 35°C - 15.6°C = 19.4°C Hours to reach pH of 5.3: 15 Degree-hours calculation: (19.4°C) x (15) = 291 degree-hours

Degree-hours calculation for the entire fermentation process = 84 + 144 + 291 = 519

The highest temperature reached = 35°C

The corresponding degree-hour limit = 555 (between 33°C and 37°C)Conclusion: Example 1 meets the guideline because its degree-hours are less than the limit.

10. Fermentation done at Different temperatures

Example 2:

It takes 38 hours for product to reach a pH of 5.3 or less. Fermentation room temperature is 24°C for the first 10 hours, 30°C for the second 10 hours and 37°C for the final 18 hours.

Step 1

Degrees above 15.6°C: 24°C - 15.6°C = 8.4°C Hours to reach pH of 5.3: 10 Degree-hours calculation: (8.4°C) x (10) = 84 degree-hours

Step 2

Degrees above 15.6°C: 30°C - 15.6°C = 14.4°C Hours to reach pH of 5.3: 10 Degree-hours calculation: (14.4°C) x (10) = 144 degree-hours

Step 3

Degrees above 15.6°C: 37°C - 15.6°C = 21.4°C Hours to reach pH of 5.3: 18 Degree-hours calculation: (21.4°C) x (18) = 385.2 degree-hours

Degree-hours calculation for the entire fermentation process = 84 + 144 + 385.2 = 613.2

The highest temperature reached = 37°C

The corresponding degree-hour limit = 555 (between 33°C and 37°C)

Conclusion: Example 2 does not meet the guidelines because its degree-hours exceed the limit.

11. What happens if fermentation fails to hit critical limit?

What happens if the batch takes longer than degree-hours allows? For restaurant level production, it's always safer to discard the product. The toxin that Staph. Aureus produces is heat stable and cannot be cooked to deactivate. In large facilities that produce substantial batches, the operator must notify the CFIA of each case where degree-hours limits have been exceeded. Such lots must be held and samples of product submitted for microbiological laboratory examination after the drying period has been completed. Analyses should be done for Staphylococcus aureus and its enterotoxin, and for principal pathogens, such as E. coli O157:H7, Salmonella, and Clostridium botulinum and Listeria monocytogenes.

If the bacteriological evaluation proves that there are fewer than 104 Staphylococcus aureus per gram and that no enterotoxin or other pathogens are detected, then the product may be sold provided that it is labelled as requiring refrigeration.

In the case of a Staphylococcus aureus level higher than 104 per gram with no enterotoxin present the product may be used in the production of a cooked product but only if the heating process achieves full lethality applicable to the meat product.

In the case where Staphylococcus aureus enterotoxin is detected in the product the product must be destroyed.

12. E. coli and Salmonella Control in Fermented Sausages

Business' that manufacture fermented sausages are required to control for verotoxinogenic E. coli including E. coli O157:H7 and Salmonella when they make this type of product. This includes:

establishments which use beef as an ingredient in a dry or semi-dry fermented meat sausage;

establishments which store or handle uncooked beef on site;

Establishments which do not use beef and do not obtain meat ingredients from establishments which handle beef are not currently required to use one of the five options for the control of E. coli O157:H7 in dry/semi-dry fermented sausages.

Any processed RTE product containing beef or processed in a facility that also processed beef, must be subjected to a heat treatment step to control E. coli O157:H7. Heating to an internal temperature of 71°C for 15 seconds or other treatment to achieve a 5D reduction is necessary. This is a CFIA requirement and is not negotiable.

Uncooked air dried products produced as RTE, must meet shelf stable requirements as detailed for Fermented-Dry products.

13. Options for E. coli validation

Without lab testing, the two main methods of validation are with heat treating by either low temp and a long duration, or various hotter processing temperatures for a shorter timeframe.

A challenge study to validate a process can take 1 year and over $100,000!

14. Option1; Heating

15. Option 2; pH, heating, holding, diameter

16. Safety and consistency

The aw and pH values are critical in the control of pathogens as well as to ensure shelf-stability in all semi-dry and dry fermented meat products. Each batch must be tested for aw and/or pH in order to verify that the critical limits are met.

Although aw measurement is mandatory only for shelf stable products, it is strongly recommended that the producer determine the aw values achieved for each product type they manufacture and for each product. Once this has been established, frequent regular checks should be made to ensure consistency. In the U.S., they rely on moisture to protein ratio and have set targets. This lab-tested value is a direct correlation of the % water to % meat protein and not aw. This gives more consistency to common names. For example, to legally call a product "jerky" it must have a MPR of 0.75:1 or lower. Remember your ABCs:

Always be compliant.

-AND-

Documentation or it didn't happen.

(tags)

Charcuterie,Fermented Meat,Food Safety,Starter Culture,Chemical Acidification,Water Activity,Fermentation Process,Degree-Hours Method,Foodborne Pathogens,Meat Processing Guidelines,Chef WK Alberta Canada,Food Industry Standards,pH Critical Limits,Thermal Processing,Food Preservation,Food Microbiology,Sausage Fermentation,Charcuterie Expertise,Fermented Meats ,Food Safety Standards,Food Processing Guidelines,Starter Cultures,Chemical Acidification,Water Activity (a_w),Critical Limits,Degree-Hours Method,Foodborne Pathogens,Meat Processing Equipment,Processing Facility Requirements,Hazard Analysis and Critical Control Points (HACCP),Food Preservation Techniques,Temperature Control,Pathogen Reduction,Food Industry Compliance,Documentation Practices,Heat Treatment,pH Control,Food Stability,Consistency in Production,Microbial Testing,Real-time Monitoring,Process Validation,Regulatory Requirements,Verotoxigenic E. coli,Lethality Standards,Product Labelling,Spoilage Prevention,Enterotoxin Detection,Shelf-Stable Products,Moisture to Protein Ratio (MPR)

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semcoinfratechworld · 7 months ago

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Advancements in Precise State of Charge (SOC) Estimation for Dry Goods Batteries

In the dynamic world of dry goods batteries, accurately determining the State of charge estimation (SOC estimation for dry goods batteries) is crucial for optimal performance and longevity. This article explores two widely used methods for SOC estimation for dry goods batteries: the Anshi integral method and the open-circuit voltage method. By examining their mechanics, strengths, and limitations, we aim to understand each method's suitability for different battery types clearly, highlighting recent advancements in SOC estimation.

I. The Anshi Integral Method

The Anshi integral method precisely calculates SOC by considering critical variables such as charge and discharge currents, time, and total capacity. This method is a cornerstone of Precise SOC estimation technology and is versatile and suitable for various battery chemistries.

Operational Mechanics

Current Measurement: Accurate measurements of charge and discharge currents using high-precision sensors are fundamental to SOC measurement for dry batteries.

Time Integration: Integrating measured currents over time to determine the total charge transferred utilizes advanced SOC algorithms for batteries.

SOC Calculation: Dividing the total charge transferred by the battery's capacity to obtain SOC ensures Accurate SOC estimation methods.

Strengths

Versatility: Applicable to different battery chemistries, enhancing Dry goods battery SOC improvement.

Robustness: Resilient to noise and parameter variations, supporting reliable Battery state of charge monitoring.

Accuracy: Provides precise SOC estimation when combined with other methods, contributing to Improving SOC estimation accuracy.

Limitations

Sensor Dependence: Accuracy relies on the quality of current sensors, affecting overall Battery management system SOC.

Temperature Sensitivity: SOC calculation can be affected by temperature variations, necessitating adaptive measures.

Computational Complexity: The integration process can be computationally expensive, impacting real-time applications.

II. The Open-Circuit Voltage Method

The open-circuit voltage method estimates SOC by measuring a battery's voltage when no load is connected. This method is particularly effective for ternary and lithium manganate batteries due to their unique voltage characteristics, representing significant Innovations in battery SOC tracking.

Operational Mechanics:

Voltage Measurement: Measuring the battery's open-circuit voltage is a fundamental aspect of State of charge estimation techniques.

SOC Lookup Table: Comparing the measured voltage to a pre-constructed lookup table utilizes Battery SOC prediction advancements.

SOC Determination: Obtaining the corresponding SOC value from the lookup table ensures reliable Real-time SOC estimation for batteries.

Strengths:

Simple Implementation: Requires minimal hardware and computational resources, making it an Accurate SOC estimation method.

High Accuracy: Provides precise SOC estimates for specific battery chemistries, enhancing SOC measurement for dry batteries.

Temperature Independence: Relatively unaffected by temperature variations, improving overall SOC estimation accuracy.

Limitations:

Limited Applicability: Effective only for batteries with well-defined voltage-SOC relationships, restricting its use.

Lookup Table Dependence: Accuracy depends on the quality and completeness of the lookup table, highlighting the need for comprehensive data.

Dynamic Voltage Fluctuations: Self-discharge and other factors can affect open-circuit voltage accuracy, challenging State of charge estimation.

III. Suitability for Different Battery Types

The open-circuit voltage method is generally applicable, but its accuracy varies depending on the battery chemistry:

Ternary Batteries: Highly suitable due to distinct voltage-SOC relationships.

Lithium Manganate Batteries: Performs well due to stable voltage profiles.

Lithium Iron Phosphate Batteries: Requires careful implementation and calibration for accurate estimation within specific SOC segments.

Lead-Acid Batteries: Less suitable due to non-linear voltage-SOC relationships.

IV. Factors Affecting State of Charge Calculation

Several factors influence SOC estimation accuracy:

Current Sensor Quality: Accuracy depends on high-precision sensors, critical for Battery state of charge monitoring.

Temperature Variations: Battery capacity changes with temperature, affecting SOC calculation.

Battery Aging: Aging reduces capacity and increases internal resistance, impacting SOC accuracy.

Self-discharge: Natural discharge over time can lead to underestimation of SOC.

Measurement Noise: Electrical noise in the system can introduce errors in SOC calculation.

V. Enhancing SOC Estimation Accuracy

To achieve accurate SOC estimation, several strategies can be employed:

Fusion of Methods: Combining the Anshi integral method with the open-circuit voltage method improves accuracy by leveraging dynamic and static information, representing key Advancements in SOC estimation.

Adaptive Algorithms: Real-time data-driven algorithms compensate for changing battery parameters and environmental conditions, enhancing SOC algorithms for batteries.

Kalman Filtering: Advanced filtering techniques reduce measurement noise, enhancing accuracy and reliability.

VI. Impact of Accurate SOC Estimation

Accurate SOC estimation has significant implications across various applications:

Optimized Battery Usage: Avoiding overcharging and deep discharging extends battery life and enhances performance, contributing to Dry goods battery SOC improvement.

Improved Safety: Reliable information on remaining capacity prevents safety hazards associated with improper charging or discharging.

Extended Battery Lifespan: Minimizing stress on batteries prolongs their lifespan, reducing costs and environmental impact.

Efficient Battery Management: Accurate SOC information enables optimized charging, discharging, and prevention of premature failure, integral to Battery management system SOC.

VII. Applications in Various Industries

Accurate SOC estimation finds applications beyond dry goods batteries:

Renewable Energy Systems: Optimizes energy storage in solar and wind power installations.

Electric Vehicles: Predicts driving range and optimizes battery performance, leveraging Battery SOC prediction advancements.

Portable Electronics: Provides reliable information on remaining battery life in smartphones and laptops.

Medical Devices: Ensures reliable operation of battery-powered medical devices for patient safety.

VIII. Future Development

Advancements in SOC estimation can be expected in the following areas:

Advanced Machine Learning Techniques: Analysing data patterns for even greater accuracy.

Battery Health Monitoring Integration: Comprehensive insights into battery performance and failure prediction.

Wireless Communication: Real-time monitoring and remote battery management, enhancing Real-time SOC estimation for batteries.

Conclusion

Accurately estimating State of charge estimation is crucial for optimizing dry goods battery performance and lifespan. Understanding the mechanics, strengths, and limitations of the Anshi integral method and the open-circuit voltage method allows informed selection and implementation for different battery types. As technology progresses, further advancements in SOC estimation techniques will enhance the efficiency and reliability of dry goods batteries across diverse applications, driving forward Innovations in battery SOC tracking and Battery SOC prediction advancements.

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