Matrix Extension Research Articles

Level 2 Modification (Matrix Extension) Study of the Neogen® Molecular Detection Assay 2 - Salmonella Enteritidis/Salmonella Typhimurium Method: Detection of Salmonella enterica ser. Enteritidis and Salmonella enterica ser. Typhimurium in Cooked Breaded Chicken and Raw Ground Chicken (25 g).

The Neogen® Molecular Detection Assay 2-Salmonella Enteritidis/Salmonella Typhimurium (MDA2-SE/ST) method is a nucleic acid amplification test for specific detection of Salmonella enterica ser. Enteritidis (SE) and Salmonella enterica ser. Typhimurium (ST), including the ST monophasic variant Salmonella enterica 1,4,[5],12:i:-, in select poultry samples. Results for SE and ST are generated separately. The method was previously validated for testing of chicken carcass rinse and raw ground chicken (325 g). The objective of the study was to validate the MDA2-SE/ST method for detection of SE and ST in cooked breaded chicken and raw ground chicken (25 g) as a Level 2 modification for Performance Tested Methods SM certification. Inclusivity/exclusivity testing and independent laboratory testing of cooked breaded chicken and raw ground chicken (25 g) were conducted. In inclusivity testing with BPW-ISO broth at 41.5 °C, all 50 SE strains produced positive results in the SE assay and negative results in the ST assay. All 53 ST strains (including the monophasic variant) produced positive results in the ST assay and negative results in the SE assay. All 35 exclusivity strains produced negative results in both assays. The exclusivity panel included multiple non-SE group D1 Salmonella serovars, multiple non-ST group B serovars, Salmonella spp. from other somatic groups, and other Enterobacteriaceae. In matrix testing, there were no significant differences in the number of positive results obtained with the MDA2-SE/ST and reference methods by probability of detection analysis at the 95% confidence level. Results of the matrix extension study showed that the MDA2-SE/ST method is an accurate method for detection of SE and ST in cooked breaded chicken and raw ground chicken (25 g). Validation of the MDA2-SE/ST method for two additional matrixes provides users with additional capability for specific detection of SE and ST in poultry products.

Linear matrix genetic programming as a tool for data-driven black-box control-oriented modeling in conditions of limited access to training data

In the paper, a new evolutionary technique called Linear Matrix Genetic Programming (LMGP) is proposed. It is a matrix extension of Linear Genetic Programming and its application is data-driven black-box control-oriented modeling in conditions of limited access to training data. In LMGP, the model is in the form of an evolutionarily-shaped program which is a sequence of matrix operations. Since the program has a hidden state, running it for a sequence of input data has a similar effect to using well-known recurrent neural networks such as Long Short-Term Memory (LSTM) or Gated Recurrent Unit (GRU). To verify the effectiveness of the LMGP, it was compared with different types of neural networks. The task of all the compared techniques was to reproduce the behavior of a nonlinear model of an underwater vehicle. The results of the comparative tests are reported in the paper and they show that the LMGP can quickly find an effective and very simple solution to the given problem. Moreover, a detailed comparison of models, generated by LMGP and LSTM/GRU, revealed that the former are up to four times more accurate than the latter in reproducing vehicle behavior.

Enhanced Joint Source-Channel Polarization Effect Based on Polarizing Matrix Extension

Enhanced Joint Source-Channel Polarization Effect Based on Polarizing Matrix Extension

Lattice factorization based causal symmetric paraunitary matrix extension and construction of symmetric orthogonal multiwavelets

In this paper, we propose a lattice factorization based symmetric paraunitary matrix extension method to design a causal symmetric paraunitary multifilter banks(PUMFBs) and construct compactly supported symmetric orthogonal multiwavelets by using the method.First, we transform a Laurent polynomial matrix consisting of polyphase components of a given symmetric orthogonal multifilter into a Laurent polynomial matrix with a simple structure, and then obtain a lattice factorization based symmetric paraunitary extension matrix by factorizing the transformed Laurent polynomial matrix and extending the constant matrix of the factorization. We also construct symmetric orthogonal multiwavelets by the proposed symmetric paraunitary matrix extension method. Finally, some examples are given to illustrate the proposed symmetric paraunitary matrix extension method.

HHL algorithm with mapping function and enhanced sampling for model predictive control in microgrids

This paper presents a refined quantum Harrow Hassidim Lloyd (HHL) algorithm for microgrid control. The first novelty of the developed method is that a mapping shift function enables the original HHL algorithm to handle general linear equations with non-singular and indefinite matrix. Second, a method of Matrix Extension for Amplifying Sampling Probabilities of Intended Solution (ME-ASPI) is proposed to design the reformulated linear algebraic equations, allowing for improved sampling efficiency of the quantum tomography in the refined HHL algorithm. Then, we applied the method to solve the model predictive control (MPC) problem in nonlinear dynamical microgrids. Specifically, with the ME-ASPI method, the refined HHL algorithm can effectively obtain the intended partial optimal control inputs for MPC. The optimization of quadratic programming problem in each time step of MPC is transformed into a linear system problem, which is addressed by the proposed quantum solver through using only partial information, with the time complexity improved from O(N2.37286) classically to O(N2logN×plogp) in quantum. Numerical examples have validated the effectiveness of the refined HHL algorithm with the proposed mapping function and the ME-ASPI method. By leveraging quantum properties, the proposed method provides a hybrid quantum–classical framework for microgrid control. This generic method can also potentially tackle many other challenges in analyzing and controlling general complex engineered systems.

Industrial Process Monitoring Based on Dynamic Overcomplete Broad Learning Network.

Most industrial processes feature high nonlinearity, non-Gaussianity, and time correlation. Models based on overcomplete broad learning system (OBLS) have been successfully applied in the fault monitoring realm, which may relatively deal with the nonlinear and non-Gaussian characteristics. However, these models barely take time correlation into full consideration, hindering the further improvement of the monitoring accuracy of the network. Therefore, an effective dynamic overcomplete broad learning system (DOBLS) based on matrix extension is proposed, which extends the raw data in the batch process with the idea of "time lag" in this article. Subsequently, the OBLS monitoring network is employed to continue the analysis of the extended dynamic input data. Finally, a monitoring model is established to tackle the coexistence of nonlinearity, non-Gaussianity, and time correlation in process data. To illustrate the superiority and feasibility, the proposed model is conducted on the penicillin fermentation simulation platform, the experimental result of which illustrates that the model can extract the feature of process data more comprehensively and be self-updated more efficiently. With shorter training time and higher monitoring accuracy, the proposed model can witness an improvement of average monitoring accuracy by 3.69% and 1.26% in 26 process fault types compared to the state-of-the-art fault monitoring methods BLS and OBLS, respectively.

A False Data Injection Attack Approach Without Knowledge of System Parameters Considering Measurement Noise

Due to the potential devastating impact on modern internet-of-things (IoT) integrated power grids, false data injection attack (FDIA) has become a major concern. This paper proposes an FDIA approach against state estimation without the knowledge of system parameters considering measurement noise. The proposed approach is able to mitigate the impact of measurement noise by utilizing the low-rank characteristic of measurement data matrix, and can recover partial singular vectors of state estimation Jacobian matrix (SEJM), based on which an unobservable attack can be launched. Besides, the scenario that only partial sensors can be tampered is investigated, and a matrix extension or split strategy is used to modify the matrix size, which makes the proposed method can be applied into the power grid of arbitrary scale. The presented method is capable of achieving a higher attack successful rate as well as requiring less amount of measurement data. Numerous cases demonstrate the effectiveness and advantages of the proposed method over other FDIA approaches in the scenario system parameters are unavailable.

Sparse Approximate Multifrontal Factorization with Composite Compression Methods

This article presents a fast and approximate multifrontal solver for large sparse linear systems. In a recent work by Liu et al., we showed the efficiency of a multifrontal solver leveraging the butterfly algorithm and its hierarchical matrix extension, HODBF (hierarchical off-diagonal butterfly) compression to compress large frontal matrices. The resulting multifrontal solver can attain quasi-linear computation and memory complexity when applied to sparse linear systems arising from spatial discretization of high-frequency wave equations. To further reduce the overall number of operations and especially the factorization memory usage to scale to larger problem sizes, in this article we develop a composite multifrontal solver that employs the HODBF format for large-sized fronts, a reduced-memory version of the nonhierarchical block low-rank format for medium-sized fronts, and a lossy compression format for small-sized fronts. This allows us to solve sparse linear systems of dimension up to 2.7 × larger than before and leads to a memory consumption that is reduced by 70% while ensuring the same execution time. The code is made publicly available in GitHub.

Extending Conceptual Density Functional Theory toward First-Order Reduced Density Matrices: An Open Subsystems Viewpoint on the Fukui Matrix.

As a matrix extension of the Fukui function, a reactivity descriptor grounded within Conceptual Density Functional Theory, the Fukui matrix extends Frontier Molecular Orbital Theory to correlated regimes with its eigendecomposition in Fukui occupations and Fukui naturals. Despite successful applications, the questions remain as to whether replacing a quantity derived from a purely density-based framework by its matrix extension is theoretically well-founded and what chemical information is contained in the corresponding eigendecomposition. In this study, we show that the matrix extension of the Fukui function is only well-defined if one also generalizes the external potential to become nonlocal, leading to the introduction of Conceptual First-Order Reduced Density Matrix Functional Theory. By interpreting the Anderson impurity model from an interacting open subsystem perspective, we show how Fukui occupations and Fukui naturals reflect the influence of an increasing (static) correlation and which characteristic patterns we should expect within a molecular context. This study represents a step in generalizing Conceptual Density Functional Theory beyond its density-based perspective.

Polar-Coded Cross-Packet HARQ Based On Polarizing Matrix Extension

In this letter, polar-coded cross-packet hybrid automatic repeat request (XP-HARQ) using multilevel coded modulation (MLCM) to improve throughput performance is investigated. Firstly, a novel polar-coded XP-HARQ framework combining polar codes, MLCM, and level-independent XP-HARQ by using polarizing matrix extension is proposed. Then, a two-step throughput-based code design method is developed to generate optimal code rates and corresponding bit protect pairs and new information bit sets in extended codes. Simulation results demonstrate that the proposed scheme outperforms level-independent Turbo-coded XP-HARQ and state-of-art hybrid automatic repeat request (HARQ) using polar-coded modulation.

Determination of Ethanol Content in Water Kefir Using Headspace Gas Chromatography With Mass Spectrometry Detection: Matrix Extension and Methanol Characterization.

Water kefir is a fermented beverage using water, sugar, and cultured microorganism grains as the primary ingredients. Ethanol may be present at varying levels within the final product due to the fermentation process, so it is vital to have a validated method to meet regulatory, quality, and safety requirements. This study describes using water kefir as a matrix for the evaluation of the previously validated method employing headspace gas chromatography mass spectrometry (HS-GCMS) detection for ethanol in kombucha. The study objective is to demonstrate the method originally using kombucha is also fit for the analysis of water kefir. This method will also evaluate the determination of methanol within the water kefir samples. The matrix extension study was performed as per the AOAC INTERNATIONAL guidance documents outlined in Appendix K: Guidelines for Dietary Supplements and Botanicals using HS-GCMS for ethanol determination. Ethanol determination in each water kefir sample is quantified against an external standard calibration curve. The same instrumentation is used for methanol characterization. RSDr and HorRat values obtained for from the study demonstrated acceptable precision with RSDr values of 1.03 to 6.68% and HorRat values determined to be between 0.23 and 1.52 for ethanol determination within kefir samples. Similarly, acceptable values of RSDr ranging from 1.45 to 3.39% and HorRat ranging from 0.25 to 0.49 were observed with methanol determination. For methanol determination, the limit of detection (LOD) and limit of quantification (LOQ) determined for the method in this study to be 16 and 21 ppm, respectively. The methanol spike recovery study gave overall recoveries ranging from 89 to 91%, demonstrating acceptable method accuracy. The results of this study demonstrate the previously validated HS-GCMS method for ethanol determination in kombucha can also be used to quantify ethanol in water kefir samples. The method is also suitable for the determination of methanol within water kefir samples. A straightforward method has been adapted to include the the quantification of ethanol and methanol in fermented beverages such as Water Kefir samples.

3M™ Petrifilm™ Rapid Aerobic Count (RAC) Plate Method for the Enumeration of Aerobic Bacteria on Selected Surfaces: AOAC Official MethodSM 2015.13.

The 3M™ Petrifilm™ Rapid Aerobic Count (RAC) Plate is a sample-ready culture medium system designed to facilitate colony enumeration in 24 h (48 h for dry powders) for selected food and environmental surfaces. The objective of this study is to evaluate the 3M Petrifilm RAC Plate in a matrix extension study for the enumeration of aerobic bacteria on stainless steel, sealed concrete, and rubber surfaces. The 3M Petrifilm RAC Plate was compared to the U.S. Food and Drug Administration Bacteriological Analytical Manual, Ch. 3 (January 2001): Aerobic Plate Count in a paired matrix study for enumeration of aerobic bacteria on stainless steel, sealed concrete, and rubber environmental surfaces. The 3M Petrifilm RAC Plate showed no statistically significant differences when compared to the reference method for enumeration of aerobic bacteria from stainless steel, sealed concrete, and rubber environmental surfaces. There were no significant statistical differences between the 3M Petrifilm RAC Plate and reference method results for the three matrixes evaluated. The 3M Petrifilm RAC Plate is an effective plating method for aerobic plate count when analyzing stainless steel, sealed concrete, and rubber surfaces. The 3M Petrifilm RAC Plate is robust, quick, and simple to perform, providing enumerable colonies in 22 to 26 h after incubation when compared to the 48 h of the reference method. The small size of the Petrifilm Plate allows for less space to be occupied by plates in the incubators. The visual biochemical and enzymatic indicators make enumeration of colonies a simple task by presenting colonies in either a blue or red color.

3M™ Petrifilm™ Rapid Yeast and Mold Count Plate Method for the Enumeration of Yeast and Mold on Selected Surfaces: AOAC Official Method 2014.05.

The 3M™ Petrifilm™ Rapid Yeast and Mold Count (RYM) Plate contains nutrients supplemented with antibiotics, a cold-water-soluble gelling agent, and an indicator system that facilitates yeast and mold enumeration in 48-60 h. The objective of this study is to evaluate the 3M Petrifilm RYM Plate in a matrix extension study for the enumeration of yeast and mold on stainless steel, sealed concrete, and rubber surfaces. The 3M Petrifilm RYM Plate was compared to the U.S. Food and Drug Administration Bacteriological Analytical Manual, Ch. 18: Yeasts, Molds and Mycotoxins in a paired matrix study for enumeration of yeast and mold on stainless steel, sealed concrete, and rubber environmental surfaces. The 3M Petrifilm RYM Plate demonstrated equivalent performance to the reference method for enumeration of yeast and mold from stainless steel, sealed concrete, and rubber environmental surfaces. There were no significant statistical differences between the 3M Petrifilm RYM Plate and reference method results for the three matrixes evaluated. The 3M Petrifilm RYM Plate is an effective plating method for enumerating yeast and mold when analyzing stainless steel, sealed concrete, and rubber surfaces. The 3M Petrifilm RYM Plate method allows the user to obtain accurate results within 48-60 h in the matrices evaluated for the presence of yeast and mold when incubated at 25 ± 1°C or 28 ± 1°C. Interpretation and colony counting was straightforward and the 3M Petrifilm RYM Plate method required no additional agar or Petri dishes, creating an easier workflow by cutting down on supplies, sample plating time, and most noticeably, occupying less space in the incubator.

Image reconstruction using Z-axis spatio-temporal sampling in 3D electrical capacitance tomography

Three-dimensional (3D) visualization has provoked interest in electrical capacitance tomography (ECT) due to recent progress in the development of capacitance measurement circuits and data-acquisition systems. This paper proposes image reconstruction using spatio-temporal sampling in the Z-axis for 3D ECT to improve spatial image resolution. In a typical application of ECT, multi-phase flow imaging is performed through two-dimensional (2D) data acquisition and 2D reconstruction of image frames over time. In the presented method, a volume of interest (VOI) is reconstructed from several time samples obtained using a 3D sensor. The procedure of Jacobian matrix extension for the spatio-temporal data is described. The experiments were carried out using the EVT4 system and a 32-electrode sensor. The reconstruction results of a VOI from a single 3D measurement and spatio-temporal sampling are compared. A phantom for 3D imaging to assess spatial image resolution using a modulation transfer function is proposed.

Multivariate Symmetric Interpolating Dual Multiwavelet Frames

The construction of symmetric multiwavelets in the multivariate case with useful in applications properties is a challenging task, mainly due to the complexity of the matrix extension problem. Nevertheless, for the interpolating case, a general technique can be developed. For an appropriate pair of symmetry group H and matrix dilation M and for a given H-symmetric interpolating refinable matrix mask, a method for the construction of H-symmetric dual refinable matrix masks with a preassigned order of sum rule is suggested. Wavelet matrix masks are constructed using a certain explicit matrix extension algorithm, and their symmetry properties are studied via its polyphase components. The resulting multiwavelet systems form dual multiwavelet frames, where wavelet functions have symmetry properties, preassigned order of vanishing moments and preassigned order of the balancing property. Several examples are presented.

A High-Performance Domain-Specific Processor With Matrix Extension of RISC-V for Module-LWE Applications

The 5G edge computing infrastructure should be empowered with quantum attack resistance by implementing post-quantum cryptography (PQC). Among various PQC schemes, lattice-based cryptography (LBC) based on learning with error (LWE) has attracted much attention because of its performance efficiency and security guarantee. In LWE-based LBCs, the Module-LWE-based schemes gain advantage over the others benefiting from the unique polynomial matrix and vector structure. To provide a high-performance implementation of Module-LWE applications for the edge computing paradigm, we propose a domain-specific processor based on a matrix extension of RISC-V architecture. This custom extension encapsulates the matrix-based ring operations with a high-level functional abstraction. A 2-D systolic array with configurable functionality is proposed to perform matrix-based number theoretic transform (NTT) and other arithmetic operations, achieving high data-level parallelism with support for the variable-sized polynomial matrix and vector structure. As this structure of Module-LWE involves no data dependency between different inner elements, an out-of-order mechanism is further developed to exploit the instruction-level parallelism. We implement the proposed architecture under TSMC 28nm technology. The evaluation results show that our implementation can achieve up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.5\times $ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.3\times $ </tex-math></inline-formula> improvement in cycle count respectively in Kyber and Dilithium, compared to the state-of-the-art crypto-processor counterparts.

Validation of the 3M™ Molecular Detection Assay 2-STEC Gene Screen (stx and eae) for Detection of Shiga Toxin Gene (stx1 and/or stx2) and Intimin Gene (eae) in Dried Cannabis Flower and Dried Hemp Flower: AOAC Performance Tested MethodSM 071902.

The 3M™ Molecular Detection Assay 2-STEC Gene Screen (stx and eae) method is based on gene amplification by the use of real time loop-mediated isothermal amplification when used with the 3M Molecular Detection System for the rapid and specific detection of Shiga toxin gene (stx1 and/or stx2) and intimin gene (eae) from Shiga toxin-producing Escherichia coli (STEC) in enriched products. The 3M Molecular Detection Assay 2-STEC Gene Screen (stx and eae) was approved as AOAC Performance Tested MethodSM Certificate No. 071902. This matrix extension study evaluated the 3M Molecular Detection Assay 2-STEC Gene Screen (stx and eae) method for detection of STECs in dried cannabis flower [>0.3% delta 9-tetrahydrocannabinol (THC)] and dried hemp flower (≤0.3% THC) at a 10 g test portion size. Testing followed procedures outlined in 3M Molecular Detection Assay 2-STEC Gene Screen (stx and eae) product instructions and Standard Method Performance Requirements (SMPR®) for Detection of Shiga Toxin-Producing Escherichia coli in Cannabis and Cannabis Products (AOAC SMPR 2020.012). The method was evaluated at low, high, and non-inoculated levels. Results showed no statistically significant difference between the presumptive positive 3M Molecular Detection Assay 2-STEC Gene Screen (stx and eae) results and the SMPR 2020.012 recommended cultural confirmations. This study provides data that demonstrate the 3M Molecular Detection Assay 2-STEC Gene Screen (stx and eae) is a reliable method for the rapid and specific detection of STEC organisms in dried cannabis flower and dried hemp flower. The 3M Molecular Detection Assay 2-STEC Gene Screen (stx and eae) method is suitable for the rapid and specific detection of STEC organisms in dried cannabis flower and dried hemp flower.

Validation of the 3M™ Molecular Detection Assay 2-STEC Gene Screen (stx) for Detection of Shiga Toxin Gene (stx1 and/or stx2) in Dried Cannabis Flower and Dried Hemp Flower: AOAC Performance Tested MethodSM 071903.

The 3M™ Molecular Detection Assay 2-STEC Gene Screen (stx) method is based on gene amplification by the use of real-time loop-mediated isothermal amplification when used with the 3M Molecular Detection System for the rapid and specific detection of Shiga toxin gene (stx1 and/or stx2) from Shiga toxin-producing Escherichia coli (STEC) in enriched products. The 3M Molecular Detection Assay 2-STEC Gene Screen (stx) was approved as AOAC Performance Tested MethodSM Certificate No. 071903. This matrix extension study evaluated the 3M Molecular Detection Assay 2-STEC Gene Screen (stx) method for detection of STECs in dried cannabis flower [>0.3% delta 9-tetrahydrocannabinol (THC)] and dried hemp flower (≤0.3% THC) at a 10 g test portion size. Testing followed procedures outlined in 3M Molecular Detection Assay 2-STEC Gene Screen (stx) product instructions and Standard Method Performance Requirement (SMPR®) for Detection of Shiga Toxin-Producing Escherichia coli in Cannabis and Cannabis Products (AOAC SMPR 2020.012). The method was evaluated at low, high, and non-inoculated levels. Results showed no statistically significant difference between the presumptive positive 3M Molecular Detection Assay 2-STEC Gene Screen (stx) results and the SMPR 2020.012 recommended cultural confirmations. This study provides data that demonstrate the 3M Molecular Detection Assay 2-STEC Gene Screen (stx) is a reliable method for the rapid and specific detection of STECs in dried cannabis flower and dried hemp flower. The 3M Molecular Detection Assay 2-STEC Gene Screen (stx) method is suitable for the rapid and specific detection of STECs in dried cannabis flower and dried hemp flower.

Validation of the 3MTM Molecular Detection Assay 2-Salmonella for detection of Salmonella in Dried Cannabis Flower and Dried Hemp Flower: AOAC Performance Tested MethodsSM 091501.

The 3M™ Molecular Detection Assay 2-Salmonella method is based on real-time loop-mediated isothermal amplification when used with the 3M Molecular Detection System for the rapid and specific detection of Salmonella in enriched products. The 3M Molecular Detection Assay 2-Salmonella was approved as AOAC INTERNATIONAL (AOAC) Performance Tested MethodSM (PTM) Certificate No. 091501 and as AOAC Official Method of AnalysisSM2016.01. This matrix extension study evaluated the 3M Molecular Detection Assay 2-Salmonella for detection of Salmonella in dried cannabis flower [>0.3% delta 9-tetrahydrocannabinol (THC)] and dried hemp flower (≤0.3% THC) at a 10 g test portion size. Matrix studies in dried cannabis and hemp flowers followed procedures outlined in 3M Molecular Detection Assay 2-Salmonella product instructions and Standard Method Performance Requirement (SMPR®) for Detection of Salmonella species in Cannabis and Cannabis Products (AOAC SMPR 2020.002). The method was evaluated at low, high, and non-contaminated levels. Results showed no statistically significant difference between the presumptive positive 3M Molecular Detection Assay 2-Salmonella results and the SMPR 2020.002 recommended cultural confirmations. This study demonstrates that the 3M Molecular Detection Assay 2-Salmonella is a reliable method for the rapid and specific detection of Salmonella in dried cannabis flower and dried hemp flower. The 3M Molecular Detection Assay 2-Salmonella method is suitable for the rapid and specific detection of Salmonella in dried cannabis flower and dried hemp flower.

Matrix Extension of the CompactDry™ "Nissui" YMR for Enumeration of Yeasts and Molds in Dried Cannabis Flower: AOAC Performance Tested MethodSM 092002.

CompactDry™ Yeast/Mold Rapid (YMR) is a ready-to-use dry media sheet using a chromogenic medium with selective agents for the enumeration of yeasts and molds in a variety of food products after incubation at 25 ± 1°C for 3 days. The method is certified as AOAC Performance Tested MethodSM 092002. The CompactDry YMR method was validated for a matrix extension to cannabis flower through the AOAC Emergency Response Validation process. The performance of the CompactDry YMR was compared to Dichloran Rose Bengal Chloramphenicol (DRBC) agar for the enumeration of yeasts and molds in cannabis flower. Matrix data were normalized by log10 transformation, and performance indicators included repeatability, difference of means (DOM), and inclusivity/exclusivity. The results demonstrated that the CompactDry YMR method is equivalent to the DRBC agar method at 72 h of incubation. In the independent laboratory validation study, there was no significant difference in detection, enumeration, or repeatability between the CompactDry YMR method and DRBC agar at 72 h. Eighteen inclusivity and 16 exclusivity strains specific to cannabis plant materials that were not evaluated in the original CompactDry YMR method validation were tested in this study. All inclusivity organisms produced typical colonies on the CompactDry YMR. The two exclusivity bacterial strains that showed growth on CompactDry YMR at 72 h were inoculated at a high concentration. CompactDry YMR is equivalent in performance to traditional culture media detection methods of yeasts and molds. CompactDry YMR will streamline dried cannabis flower testing.