Control Charting Mississippi Style ASHLI BROWN, GALE HAGOOD, DONGPING JIANG MISSISSIPPI STATE CHEMICAL LABORATORY GOVERNMENTAL FOOD AND FEED LABORATORIES ACCREDITATION MEETING FEBRUARY 2016

5.9 Assuring the quality of Test and calibration results  The laboratory shall have quality control procedures for monitoring the validity of tests and calibrations undertaken. The resulting data shall be recorded in such a way that trends are detectable a) regular use of certified reference materials b) participation in interlaboratory comparison or proficiency-testing programs. QM Quality Control Policy and Procedure: Quality control procedures are utilized to monitor the validity of test results. QP-026 defines the specific QC procedures used.  Quality control data shall be analyzed and, where they are found to be outside pre-defined criteria, planned actions shall be taken to correct the problem and to prevent incorrect results from being reported. QM Correction and Prevention Policy and Details: As specified in QP-026

QP-026 Quality Control  Scope: * This procedure applies to all personnel within the laboratory * To ensure the accuracy and validity of test results  Definitions * Quality Control Sample (QCS): Matrix match; Known value * Control Chart: QCS data over time to show current results against acceptance criteria and trends of data over time.

 Mentor Lab(s)  Accrediting Body courses  Weekly lab meetings  Webinar (Control Chart and Trend Analysis by NY State Food Lab)  Quality Control Questionnaire  Individual one-on-one training Training

Quality Control Questionnaire

Overview of the MSCL Control Charts  Regulatory control charts Protein; Fat; Fiber; Dry Matter; Moisture; ADF; NDF; NIR protein, fat, fiber  Mercury and Inorganics control charts  Aflatoxin control charts  Total solids control chart  Residue control charts DEQ water, PAH and DOSS animal tissue  Petroleum products control charts

Mercury High Level Note: When two or more consecutive values fall outside 2 SD, it indicates it is time for recalibrating the instrument. Preliminary TestsDaily Tests STATISTICS for Preliminary tests Std Dev Mean UAL UWL LWL LAL

Mercury Low Level Preliminary TestsDaily Tests STATISTICS21 for Preliminary22 tests23 24 Std Dev Mean UAL UWL LWL LAL Note: Certified values were used to calculate the control limits.

Types of Data Plotted in Control Charts  Running a Quality Control Sample  Using Matrix Spikes  Proficiency Testing

Proficiency Testing Participation  AAFCO The Association of American Feed Control Officials  State Alflatoxin Share Program  AOAC International  FERN Food Emergency Response Network  Association of American Pesticide Control Officials Check Sample Program  Magruder  American Oil Chemists’ Society  National Forage Testing Association  ASTM International  Round Robin(s) with other State and Federal agencies  USDA FSIS  ERA

Control charts have improved the MSCL Quality Control  Control charts are monitored by the analyst entering data. “Out-of-control signals” on the control charts are investigated. * A single point outside 3 SD. * Two points outside 2 SD on the same side of the mean. * A run of eight points in a row are on the same side of the mean. * An increasing or decreasing trends  Initiate a corrective action according to the technical procedure.

Feedback from the Analyist I plot my QC standard with each sample set. The control chart is helpful in seeing the trends before I have a failure. I started plotting my instrument responses because it helps determine the need for maintenance or new commodities (columns, capillaries, standards or solvents Very helpful in determining steps to prevent inaccurate data. I plot the Standard Reference Material that is used for QC. Although, I still compare the measured results to the Certificate of Analysis in addition to the control chart. When reviewing sets of data the control charts are an easy reference to ensure the set of samples has passing QC. By implementing control charts as a preventive measure fewer sample sets have to be repeated and there has been a decrease in the number of CARs related to PT failures.

If the Quality Manager ain’t happy nobody’s happy!!!

Crude Fiber Preliminary TestsDaily Tests STATISTICS216.5 for Preliminary226.6 tests Std Dev Mean UAL UWL LWL LAL Note: 20 data points were used to calculate the control limits.

Crude Fiber Continued Preliminary TestsDaily Tests STATISTICS for Preliminary tests Std Dev0.425 Mean6.526 UAL7.627 UWL7.228 LWL5.729 LAL5.330 Note: Use the same control limits as the previous control chart.

Aflatoxin Level 1 Preliminary TestsDaily Tests STATISTICS21 for Preliminary22 tests23 24 Std Dev1.825 Mean UAL UWL LWL8.529 LAL6.730

Aflatoxin Level 2 Preliminary TestsDaily Tests STATISTICS21 for Preliminary22 tests23 24 Std Dev4.725 Mean UAL UWL LWL LAL17.230

Total Solids Preliminary TestsDaily Tests STATISTICS21 for Preliminary22 tests23 24 Std Dev2.725 Mean UAL UWL LWL LAL Note: There are two data points out of 3 SD, but they are within acceptable limits.

Herbicide: Atrazine Percent of spike recovery Preliminary TestsDaily Tests TestB A STATISTICS21 for Preliminary22 tests23 24 Std Dev Mean UAL UWL LWL LAL Note: Percent of spike recovery within 60 – 130%.

Anthracene Percent of spike recovery Preliminary TestsDaily Tests TestB A STATISTICS21 for Preliminary22 tests23 24 Std Dev4.025 Mean UAL UWL LWL LAL Note: Percent of spike recovery within 80 – 100%.