ASTM F2340-05(2021)

Standard Specification for Developing and Validating Prediction Equation(s) or Model(s) Used in Connection with Livestock, Meat, and Poultry Evaluation Device(s) or System(s) to Determine Value

ABSTRACT
This specification covers the standard procedures used to collect and analyze data, document the results, and make predictions for any characteristic used to quantify the value of any livestock, meat, and poultry species as measured by appropriate evaluation devices or systems. The procedures described here shall be used particularly when new prediction equations or models are established, or when a change is experienced that could affect the performance of existing equations.
SCOPE
1.1 This specification covers methods to collect and analyze data, document the results, and make predictions by any objective method for any characteristic used to determine value in any species using livestock, meat, and poultry evaluation devices or systems.  
1.2 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.3 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

General Information

• Status: Published
• Publication Date: 31-May-2021
• ICS: 65.020.30 - Animal husbandry and breeding
• Technical Committee: F10 - Livestock, Meat, and Poultry Evaluation Systems
• Drafting Committee: F10.40 - Predictive Accuracy

Relations

• Refers: ASTM F2463-12b - Standard Terminology for Livestock, Meat, and Poultry Evaluation Systems
• Effective Date: 15-Nov-2012
• Refers: ASTM F2463-12be1 - Standard Terminology for Livestock, Meat, and Poultry Evaluation Systems
• Effective Date: 15-Nov-2012
• Refers: ASTM F2463-12a - Standard Terminology for Livestock, Meat, and Poultry Evaluation Systems
• Effective Date: 01-Sep-2012
• Refers: ASTM F2463-12 - Standard Terminology for Livestock, Meat, and Poultry Evaluation Systems
• Effective Date: 01-Aug-2012
• Refers: ASTM F2463-06 - Standard Terminology for Livestock, Meat, and Poultry Evaluation Systems
• Effective Date: 01-Mar-2006
• Refers: ASTM F2463-05a - Standard Terminology for Livestock, Meat, and Poultry Evaluation Systems
• Effective Date: 01-Dec-2005
• Refers: ASTM F2463-05 - Standard Terminology for Livestock, Meat, and Poultry Evaluation Systems
• Effective Date: 01-May-2005

Standards Content (Sample)

This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the
Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
Designation:F2340 −05 (Reapproved 2021)
Standard Specification for
Developing and Validating Prediction Equation(s) or
Model(s) Used in Connection with Livestock, Meat, and
Poultry Evaluation Device(s) or System(s) to Determine
Value
This standard is issued under the fixed designation F2340; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision.Anumber in parentheses indicates the year of last reapproval.A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope istic;accuracyiscontrastedwithprecision,whichisconcerned
with the repeatability of the measurements. Therefore, with a
1.1 Thisspecificationcoversmethodstocollectandanalyze
largebias,ameasurementmaybeofhighprecision,butoflow
data, document the results, and make predictions by any
accuracy.
objectivemethodforanycharacteristicusedtodeterminevalue
3.2.2 calibration data set, n—data set used to develop the
in any species using livestock, meat, and poultry evaluation
initial prediction equations; same as developmental or predic-
devices or systems.
tion data set.
1.2 This standard does not purport to address all of the
3.2.3 coeffıcient of determination, n—percentageofvariabil-
safety concerns, if any, associated with its use. It is the
ity in the response (dependent) variable that can be explained
responsibility of the user of this standard to establish appro-
by the prediction equation.
priate safety, health, and environmental practices and deter-
mine the applicability of regulatory limitations prior to use. 2
y 2 yˆ
~ !
(
R 51 2
1.3 This international standard was developed in accor-
y 2 y¯
~ !
(
dance with internationally recognized principles on standard-
3.2.4 root mean square error for calibration, n—squareroot
ization established in the Decision on Principles for the
of the sum of squared residuals divided by n −(k+1), where
c
Development of International Standards, Guides and Recom-
n is the sample size for the calibration data set, and k is the
c
mendations issued by the World Trade Organization Technical
number of explanatory variables in the prediction equation.
Barriers to Trade (TBT) Committee.
y 2 yˆ
~ !
(
2. Referenced Documents
Œ
n 2 k11
~ !
c
2.1 ASTM Standards:
3.2.5 root mean square error for validation, n—square root
F2463Terminology for Livestock, Meat, and Poultry Evalu-
of the sum of squared residuals divided by n , where n is the
y y
ation Systems
sample size for the validation data set.
3. Terminology
~y 2 yˆ!
(
Œ
3.1 For definitions of terms used in this specification, refer n
v
to Terminology F2463.
3.2.6 validation data set, n—the data set used to test the
predictive accuracy of the equations developed from the
3.2 Definitions of Terms Specific to This Standard:
calibration data set.
3.2.1 accuracy, n—statement of the exactness with which a
measurement approaches the true measure for that character-
3.2.7 value, commerce, n—measure of economic worth in
commerce.
1 4. Significance and Use
This specification is under the jurisdiction of ASTM Committee F10 on
Livestock, Meat, and Poultry Evaluation Systems and is the direct responsibility of
4.1 Theproceduresinthisspecificationaretobeusedbyall
Subcommittee F10.40 on Predictive Accuracy.
parties interested in predicting composition or quality, or both,
CurrenteditionapprovedJune1,2021.PublishedJuly2021.Originallyapproved
for the purpose of establishing value based upon device or
in 2004. Last previous edition approved in 2016 as F2340–05 (2016). DOI:
10.1520/F2340-05R21.
system measurements.Whenever new prediction equations are
For referenced ASTM standards, visit the ASTM website, www.astm.org, or
established, or when a change is experienced that could affect
contact ASTM Customer Service at [e-mail]. For Annual Book of ASTM
the performance of existing equations, these procedures shall
Standards volume information, refer to the standard’s Document Summary page on
the ASTM website. be used.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
F2340−05 (2021)
5. Procedure of these characteristics in references such as the National Beef
Quality Audits. Users are encouraged to work with a statisti-
5.1 Experimental Design:
cian.
5.1.1 Define the Population for Development of a Prediction
5.1.3 Develop an Experimental Process—A clearly defined
Equation:
process must be established and documented. That process,
5.1.1.1 To establish the predictive ability and validity of an
which includes consistent, repeatable methods, should be used
equation(s) using measures (independent variables) from an
toobtainthemeasurementsunderthesameconditionsinwhich
evaluation device or system, it is necessary to define the
the device or system would be expected to operate. In
population on which the prediction model is intended to be
particular, the validity of the approach and the repeatability of
used.
the procedure must be documented and demonstrated. For
(1)Thespeciesonwhichmeasurementswillbemademust
many of the common characteristics to be predicted (such as
be defined.
percent lean), there are a number of reference methods com-
(2)Thepopulationforscopeofusemustbeclearlydefined.
monlyacceptedwithinthediscipline.Whereacceptedmethods
This may include, but is not limited to, factors such as
exist, they should be used and cited. Where accepted methods
geographical location, gender, age, breed type, or any other
do not exist, a sound, science-based process of method
factor that may affect the equation accuracy.
development should be followed. Consideration should be
(3)The characteristic to be predicted must be clearly
given to sources of variation for the measurements and
defined.
strategies to minimize any bias that may exist.
5.1.2 Select a Sample Population for Development of a
Prediction Equation: 5.1.4 Independent Third-Party Consultation—After the ex-
5.1.2.1 The sample size for the calibration data set must be perimental process has been established (but before initiation
at a minimum 10k, where k is the number of variables in the of the sampling), it is recommended that the users obtain an
prediction equation, or 100 observations, whichever is greater. independent third-party consultation to review the procedures
The sample size for the validation data set must be at least for compliance with the guidelines established in the previous
20% of the size of the calibration validation data set. For sections. The consultation should focus on areas such as the
number of samples, the sample selection protocol, and the
example, if the prediction equation has five explanatory
variables, the calibration data set will require a minimum of project procedures to ensure that the process will allow the
userstodetermineeffectivelythepredictiveabilityandvalidity
100 observations and the validation set must have at least 20
observations. These are minimal requirements; larger sample of the equation or model.
sizes are encouraged, keeping in mind that the calibration data
5.1.5 Develop the Model or Equation:
set must be larger than the validation data set.
5.1.5.1 Collect data for the calibration (developmental) data
5.1.2.2 The sample size must be large enough to be repre-
set and develop the model or equation. Report the value of the
sentative of the population; otherwise the resultant equation
coefficient
...