General Regression Neural Network Model for Behavior of Salmonella on Chicken Meat during Cold Storage

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1 Generl Regression Neurl Network Model for Behvior of Slmonell on Chiken Met during Cold Storge Thoms P. Osr M: Food Miroiology & Sfety Astrt: A study ws undertken to investigte nd model ehvior of Slmonell on hiken met during old storge t onstnt tempertures. Chiken met (white, drk, or skin) portions (.75 m 3 ) were inoulted with single strin of Slmonell Typhimurium DT1 (. log) followed y storge for to d t,,, 1, 1, or 1 C for model development nd t,, 1, or 1 C for model vlidtion. A generl regression neurl network model ws developed with ommeril softwre. Performne of the model ws onsidered eptle when the proportion of residuls (oserved predited) in n eptle predition zone (papz) from 1 log (fil-sfe) to.5 logs (fil-dngerous) ws.7. Growth of Slmonell Typhimurium DT1 on hiken met ws oserved t 1, 1, nd 1 C ndws highest on drk met, intermedite on skin, nd lowest on white met. At lower tempertures ( to 1 C) Slmonell Typhimurium DT1 remined t initil levels throughout d of storge exept t C where there ws smll (. log) ut signifint deline. The model hd eptle performne (papz =.99) for dependent dt (n = ) nd eptle performne (papz =.93) for independent dt (n = 35). Results indited tht it is importnt to inlude type of met s n independent vrile in the model nd tht the model provided vlid preditions of the ehvior of Slmonell Typhimurium DT1 on hiken skin, white, nd drk met during storge for to d t onstnt tempertures from to 1 C. Keywords: hiken, preditive modeling, Slmonell Prtil Applition: A model for prediting ehvior of Slmonell on hiken met during old storge ws developed nd vlidted. The model will help the hiken industry to etter predit nd mnge this risk to puli helth. Introdution During old storge, the numer of Slmonell on hiken met my sty the sme, inrese, or derese depending on time nd temperture of storge nd type of met. For exmple, when Slmonell re inoulted into white nd drk met of hiken nd stored for 1 d t, 5,, or 1 C, there is smller derese in numer in white met thn in drk met nd t C thn t 5,, or 1 C (Foster nd Med 197). The effet of frozen storge on ehvior of Slmonell on hiken skin ws not investigted. Thus, there is need to further investigte ehvior of Slmonell on hiken met during frozen storge s funtion of time, temperture, nd type of met. Severl studies hve investigted ehvior of Slmonell on hiken met stored t refrigertion tempertures. Zher nd Fujikw (11) investigted ehvior of Slmonell Enteritidis in ground hiken stored t to 1 C nd Prdhn nd others (1) investigted ehvior of Slmonell Typhimurium on hiken white met stored for 1 d t,, or C. Osr (11) studied survivl nd growth of Slmonell Typhimurium DT1 on hiken skin stored for to 1 d t to 1 C. However, none MS 1319 Sumitted 1//13, Aepted //1. Author Osr is with U.S. Dept. of Agriulture, Agriulturl Reserh Servie, Residue Chemistry nd Preditive Miroiology Reserh Unit, Room 111, Center for Food Siene nd Tehnology, Univ. of Mrylnd Estern Shore, Priness Anne, MD 153, USA. Diret inquiries to uthor Osr (E-mil: thoms.osr@rs.usd.gov). of these studies investigted the effet of ll types of hiken met on ehvior of Slmonell during refrigerted storge. Models tht predit hnges in numer of Slmonell over time, temperture, nd other independent vriles re routinely used in the hiken industry to predit nd mnge this risk to puli helth. The hiken industry is most interested in models tht predit ehvior of Slmonell in hiken met rther thn in lortory roth. The study of Foster nd Med (197) suggests tht type of hiken met might ffet ehvior of Slmonell during old storge ut thus fr there re no preditive models tht inlude this vrile. Therefore, the urrent study ws undertken to investigte nd model ehvior of Slmonell on hiken met during old storge s funtion of time, temperture, nd type of met. Dt from previous study (Osr 11) were not used in model development nd vlidtion euse they were olleted with different methods (tht is, different inoulum size, different previous history of inoulum, nd different hiken skin model). Mterils nd Methods Orgnism A multiple ntiioti resistnt strin (ATCC 7) of Slmonell enteri serotype Typhimurium definitive phge type 1 (DT1) ws otined from ommeril soure (Amerin Type Culture Colletion, Mnsss, V., U.S.A.). Stok ultures of the orgnism were mintined t C in rin hert infusion roth (BBL TM, Beton, Dikinson nd Co., Sprks, Md., U.S.A.) tht ontined 15% (volume/volume) glyerol Journl of Food Siene C 1 Institute of Food Tehnologists R No lim to originl US government works M97 Journl of Food Siene Vol. 79, Nr. 5, 1 doi: / Further reprodution without permission is prohiited

2 Behvior of Slmonell on hiken met... (Sigm-Aldrih Corp., St. Louis, Mo., U.S.A.). This orgnism ws used for model development nd vlidtion euse it hs phenotype tht llows it to e enumerted in the presene of other miroorgnisms nd euse it hs een isolted from hiken (Prveen nd others 7). Preprtion of hiken portions Chiken rests (white met) nd thighs (drk met) with skin were purhsed from lol retil stores. Skin ws removed nd pled on plsti utting ord followed y freezing for 15 min t C. This ws done to filitte utting of irulr portions (.5 m ) with ork orer (#5). Chiken rests nd thighs were deoned nd then white nd drk mets were ground seprtely through the orse plte nd then fine plte of n eletri tletop met grinder (Model 5. Zelmer, The Susge Mker, Bufflo, N.Y., U.S.A.). Ground white met nd ground drk met were pked into seprte plsti petri dishes (1 15 mm) nd frozen t C to filitte utting into equl-sized ylindril portions (.75 m 3 ) with ork orer (#5). White met nd drk met portions were trnsferred to 1.5-mL polypropylene miroentrifuge tues. Skin portions were pled on top of some white met or drk met portions. All hiken met portions were stored t C until used in experiments. Mesurement of ph The ph of rndomly seleted hiken met portions (n = to per type of met) ws mesured using hndheld instrument whose proe ould e diretly inserted into the met portion (ph Sper, Okton Instruments, Vernon Hills, Ill., U.S.A.). Enumertion of ntive miroflor The numer of ntive miroflor of rndomly seleted hiken met portions (n = to per type of met) ws determined y the most prole numer (MPN) method. Individul portions of hiken met were pled in 7-mL plsti gs with filter sreens (Whirl-Pk R, Nso, Fort Atkinson, Wis., U.S.A.). After dding 9 ml of uffered peptone wter (BPW; Difo TM, Beton, Dikinson nd Co.), the smple ws pulsified (model PUL 1, Miroiology Intl., Frederik, Md., U.S.A.) for 1 min to reover ntive miroflor into BPW. The pulsifte ws used to set up 3 (replite) y (dilution [1:1]) MPN ssy in BPW. The MPN ssy ws inuted for h t 3 C nd then 5 μl fromeh MPN tue ws drop plted onto rin hert infusion gr (BBL TM, Beton, Dikinson nd Co.). Drop pltes were inuted for h t 3 C to onfirm the pttern of positive nd negtive tues. The MPN result ws lulted s desried elow. Inoultion nd inution of hiken met portions Stok ulture of Slmonell Typhimurium DT1 ws thwed, resuspended y gentle shking, nd then 5 μl ws inoulted into 9 ml of BPW in glss dilution tue (1 15 mm) with plsti p. The inoulted BPW tue ws inuted for 7 h t C without shking to otin sttionry phse ells for inoultion of hiken met portions. Immeditely efore inoultion of hiken met portions, the 7-h ulture ws serilly diluted (1:1) in BPW to 1. Conentrtion of Slmonell Typhimurium DT1 in the 7-h ulture ws determined y spirl plting (Whitley Automted Spirl Plter, Miroiology Intl.) 5 μl ofthe1 5 nd 1 dilutions in duplite onto XLT gr se medium (Difo TM, Beton, Dikinson nd Co.) supplemented with 5 mm HEPES (Sigm-Aldrih Corp.) nd 5 μg per ml of the following ntiiotis (Sigm-Aldrih Corp.): hlormpheniol (C), mpiillin (A), tetryline (T), nd streptomyin (S); herefter, referred to s XLH-CATS. Spirl pltes were inuted for h t Cnd then typil lk olonies of Slmonell Typhimurium DT1 tht formed were ounted using n utomted olony ounter (ProtoCOL, Miroiology Intl.). Chiken met portions were spot inoulted on their surfe with 5 μl ofthe1 dilution of the 7-h ulture of Slmonell Typhimurium DT1 for n initil inoulum level of. ±.1 (men ± stndrd devition) log per portion. The inoulted hiken met portions in 1.5-mL miroentrifuge tues were inserted into individul wells of heting nd ooling dry lok (Peltier PCH-1, Grnt Instruments, Cmridge, UK or Eppendorf ThermoStt Plus, Hmurg, Germny) nd inuted for, 1,,,, or d t,,, 1, 1, or 1 C for model development or t,, 1, or 1 C for model vlidtion. The heting nd ooling dry lok ws loted in refrigertor for storge tempertures from to C nd t room temperture for storge tempertures from to 1 C. Two to four replite trils with duplite met smples per time were onduted per storge temperture. Enumertion of Slmonell Typhimurium DT1 Duplite hiken met portions were enumerted seprtely for Slmonell Typhimurium DT1 t eh smpling time. Individul portions were onsidered s independent oservtions euse it ws ssumed tht the mironihe of the inoulted ells differed mong portions. The p of the 1.5 ml miroentrifuge tue ws opened nd then mirotue utter ws used to ut off the ottom of the miroentrifuge tue. The hiken met portion ws then pushed out of the tue nd into 7-mL smple g with filter sreen. Nine milliliter of BPW ws dded to the hiken met portion in the g nd then the smple ws pulsified for 1 min to reover Slmonell Typhimurium DT1 into BPW for enumertion y MPN nd spirl plting methods. A 3 (replite) y (dilution) MPN ssy in BPW ws used when the numer of Slmonell Typhimurium DT1 ws etween nd 3. log per portion. After setting up the MPN ssy, 9 ml of BPW ws dded to the residul pulsifte nd hiken met portion in the g. The MPN ssy tues nd g ontents were inuted for h t C ndthen5μl fromehmpntue nd the filter g ws spot inoulted onto XLH-CATS. After h of inution t C, MPN tues nd gs tht were positive for Slmonell Typhimurium DT1 produed lk spot on XLH-CATS wheres MPN tues nd gs tht were negtive for Slmonell Typhimurium DT1 produed no spot on XLH-CATS. The MPN result ws lulted s follows (Thoms 19): MPN portion = log{[(p/ NxT)]xV} (1) where P ws the numer of positive tues, N ws the totl mount of pulsifte (ml) in ll negtive tues, T ws the totl mount of pulsifte (ml) in ll tues, nd V ws the totl volume of BPW (tht is, 9 ml) in the originl smple. It ws ssumed tht the solid met portion (.75 m 3 ) did not ontriute signifintly to the totl smple volume euse it remined ehind the filter sreen when smples were pulled for the MPN ssy. The numer of Slmonell Typhimurium DT1 per portion ws lso determined y spirl plting undiluted or serilly diluted (1:1 in BPW) smples (5 μl) of pulsifte onto XLH-CATS M: Food Miroiology & Sfety Vol. 79, Nr. 5, 1 Journl of Food Siene M979

3 Behvior of Slmonell on hiken met... M: Food Miroiology & Sfety followed y inution for h t C nd utomted ounting of lk olonies tht formed on the spirl plte during inution. Model development A generl regression neurl network (GRNN) model ws developed rther thn regression model sed on primry, seondry, nd tertiry modeling euse GRNN models re more flexile, require less dt, re esier to develop nd vlidte, only require one modeling step, nd they outperform regression models in preditive miroiology pplitions (Hjmeer nd others 1997; Jeymkondn nd others 1; Gri-Gimeno nd others 3; Plnihmy nd others ). To develop the GRNN model, dt set ws reted in omputer spredsheet (Exel 7, Mirosoft Corp., Redmond, Wsh., U.S.A.) with seprte olumns for tg (to designte dependent dt for model development nd to designte independent dt for model vlidtion), type of met (independent tegoril vrile), temperture (independent numeril vrile), time (independent numeril vrile), nd log numer per portion (dependent numeril vrile). The GRNN model (Figure 1) ws developed y the method of Speht (1991) using spredsheet dd-in progrm (industril version 5.7, NeurlTools, Plisde Corp., Ith, N.Y., U.S.A.) nd equtions s previously desried (Osr 9). The model prmeters (tht is, smoothing ftors) re not provided y the softwre for proprietry resons. However, fter pulition the model will e mde ville through the Poultry Food Assess Risk Models wesite ( n/err/poultryfarm). Model vlidtion A onern when using GRNN model to mke preditions is overtrining tht would result in preditions losely mimiking dt used in model development. Thus, it ws importnt to vlidte the GRNN model ginst independent dt. To omplish this, the dt set ws divided into dependent dt (n = ) nd independent dt (n = 35) sets. The independent dt were olleted with the sme methods s dependent dt ut t intermedite tempertures with the exeption of dt olleted t 1 C. This ws done to see how well the model ould interpolte over its entire predition region. Model performne ws evluted using the eptle predition zone (APZ) method (Osr 5). This method hs riteri for test dt nd model performne tht must e stisfied for model to e lssified s vlidted. It involves 3 sequentil steps: (1) goodness-of-fit; () interpoltion; nd (3) extrpoltion. A model is onsidered vlidted in the APZ method when it meets test dt nd model performne riteri for the 1st steps. The 3rd step is optionl nd is performed to see how rodly the model n e pplied to independent vriles (for exmple, other strins) not inluded in model development. Although optionl, the 3rd step is importnt euse it identifies independent vriles for whih new models re not needed, whih sves time nd money. The APZ method n e used to evlute nd vlidte ll types of preditive models (Osr 5). The APZ oundries used for eh type of model re sed on n evlution of experimentl error ssoited with determining dependent vriles (for exmple, lg time). For models tht predit log numer, it ws found tht the solute reltive error mong replite smples ws out.5 log (Osr 5). Thus, predition is onsidered eptle in the APZ method when the differene etween oserved nd predited vlues is <.5 log. This metri is the sme s tht used y Thurette nd others (199) to evlute performne of preditive model for Listeri monoytogenes nd smoked fish produts. When using model to predit food sfety, it is desirle to llow the model to err more in the fil-sfe diretion to provide n extr level of ssurne tht model preditions will protet puli helth. The preedent in preditive miroiology is to llow model to err twie s muh in the fil-sfe diretion (Ross nd others ). Consequently, predition is onsidered eptle in the APZ method when the residul (oserved predited) is in n APZ from 1 log (fil-sfe) to.5 logs (fil-dngerous). There is not preedent in preditive miroiology for wht proportion of residuls must e eptle for lssifition of model s providing preditions with eptle ury nd is. However, in the U.S.A. edution system n estlished performne riterion is tht test sore of 7% orret nswers is the minimum for lssifition of eptle performne. This estlished riterion is used in the APZ method. Thus, when the proportion of residuls in the APZ (papz) is.7, the model is lssified s providing eptle preditions. In ddition to riteri for model performne, riteri for test dt must e met for model to e lssified s vlidted. Tle 1 shows the progression of questions tht must e nswered in the ffirmtive for model to e vlidted y the APZ method. Thus, in the APZ method, it is not possile to vlidte model for extrpoltion if it ws not vlidted for interpoltion nd it is not possile to vlidte model for interpoltion unless it provided eptle preditions of dependent dt. An importnt omponent of the APZ method is plot of residuls s funtion of independent vriles or plot of the dependent vrile s funtion of the independent vriles with the APZ indited on the plot. These types of plots re used to hek for lol predition prolems. Figure 1 Digrm of the GRNN model for survivl, deth, nd growth of Slmonell Typhimurium DT1 on hiken met s funtion of time (t), temperture (T), nd type of met (M). The pttern lyer shows the rnge of log numer dt. Sttistil nlysis To provide n ojetive wy to onlude whether Slmonell Typhimurium DT1 survived, died, or grew on hiken met during old storge nd to ojetively ssess whether type of met M9 Journl of Food Siene Vol. 79, Nr. 5, 1

4 Behvior of Slmonell on hiken met... Tle 1 Progression of questions tht must e nswered in the ffirmtive for model to e lssified s vlidted in the eptle predition zone (APZ) method. Q1 Were preditions for dependent dt eptle (papz.7)? Q Were vlidtion dt for interpoltion independent? Q3 Were vlidtion dt for interpoltion olleted with dependent dt methods? Q Did vlidtion dt for interpoltion provide omplete overge of model preditions? Q5 Were preditions for vlidtion dt for interpoltion eptle (papz.7)? Q Ws vlidtion for interpoltion suessful (yes to Q1 to Q5)? Q7 Were vlidtion dt for extrpoltion independent? Q Were vlidtion dt for extrpoltion olleted with dependent dt methods exept for the new independent vrile? Q9 Did vlidtion dt for extrpoltion provide omplete overge of model preditions? Q1 Were preditions for vlidtion dt for extrpoltion eptle (papz.7)? Q11 Ws vlidtion for extrpoltion suessful (yes to Q1 to Q1)? ffeted ehvior of Slmonell Typhimurium DT1 on hiken during old storge, two-wy nlysis of vrine (version.3, Prism, GrphPd Softwre, Sn Diego, Clif., U.S.A.) ws used within storge temperture to determine effets of storge time, type of met, nd their intertion on log numer of Slmonell Typhimurium DT1 per portion. Dt used in model development nd vlidtion were omined into single dt set for this nlysis. When signifint (P <.5) effet of type of met or intertion of type of met nd storge time ws oserved, mens mong types of met within storge time nd temperture were ompred using Tukey s multiple omprison tests with signifine level of P <.5. One-wy nlysis of vrine (Prism, GrphPd Softwre) ws used to determine effet of type of met on ph nd log numer of ntive miroflor per portion. When signifint (P <.5) effet of type of met ws oserved, mens were ompred using Tukey s multiple omprison tests with signifine level of P <.5. d of old storge t these tempertures. However, t storge temperture of C, the min effet of time nd the min effet of type of met were signifint (P <.5). Here (Figure ), log numer of Slmonell Typhimurium DT1 ws lower (P <.5) on skin thn white met t d of storge, lower (P <.5) on drk met thn white met t d of storge, nd lower (P <.5) on skin thn on drk met t d of storge. Although there ws not onsistent pttern of results mong types of met, results indited tht log numer of Slmonell Typhimurium DT1 per portion deresed slightly (. log) during storge for to d t C. At higher old storge tempertures (1, 1, nd 1 C), log numer of Slmonell Typhimurium DT1 ws ffeted y signifint (P <.5) time y type of met intertion. At 1 C (Figure 3), log numer of Slmonell Typhimurium DT1 ws higher (P <.5) on drk met thn white met nd skin t,, nd d of storge wheres t d of storge it ws higher (P <.5) on skin thn on white met. At 1 C (Figure ), log numer of Slmonell Typhimurium DT1 ws higher (P <.5) on drk met thn on white met nd skin t,,, nd d of storge wheres it ws higher (P <.5) on skin thn on white met Slmonell Typhimurium DT1 1 White Drk Skin,,, Time (dys) M: Food Miroiology & Sfety Results nd Disussion Behvior of Slmonell Typhimurium DT1 on hiken met during old storge Bsed on study y Foster nd Med (197) it ws expeted tht depending on type of met nd time nd temperture of old storge tht the log numer of Slmonell Typhimurium DT1 inoulted onto hiken met would sty the sme, derese, or inrese. To provide n ojetive ssessment of whether Slmonell Typhimurium DT1 survived, died, or grew on hiken met during old storge, results within storge temperture were nlyzed y two-wy nlysis of vrine. A signifint (P <.5) min effet of time or signifint (P <.5) intertion of time nd type of met indited tht Slmonell Typhimurium DT1 either died or grew on hiken met. On the other hnd, when the min effet of time nd intertion of time nd type of met on the log numer of Slmonell Typhimurium DT1 per portion were not signifint (P >.5) this indited survivl nd not deth or growth. The min effet of time nd intertion of time nd type of met on log numer of Slmonell Typhimurium DT1 per portion were not signifint (P >.5) for storge tempertures of,,,, nd 1 C (resultsnotshown).thus,slmonell Typhimurium DT1 survived nd did not die or grow on hiken met during Figure Effet of time nd type of met on log numer of Slmonell Typhimurium DT1 on hiken met stored for to d t C. Brs re mens ± stndrd devitions. Brs within luster with different supersripts differ (P <.5). Slmonell Typhimurium DT1 1 White Drk Skin Time (dys) Figure 3 Effet of time nd type of met on log numer of Slmonell Typhimurium DT1 on hiken met stored for to d t 1 C. Brs re mens ± stndrd devitions. Brs within luster with different supersripts differ (P <.5). Vol. 79, Nr. 5, 1 Journl of Food Siene M91

5 Behvior of Slmonell on hiken met... M: Food Miroiology & Sfety t,, nd d of storge. At 1 C (Figure 5), log numer of Slmonell Typhimurium DT1 ws higher (P <.5) on drk met nd skin thn on white met t,,, nd d of storge nd ws higher (P <.5) on drk met thn on skin t nd d of storge. Thus, Slmonell Typhimurium DT1 grew on hiken met stored for d t 1, 1, or 1 C nd growth ws highest on drk met, intermedite on skin, nd lowest on white met. Differenes in ph nd ntive miroflor ould help explin differenes in growth of Slmonell Typhimurium DT1 on skin, white, nd drk met of hiken during old storge t 1, 1, or 1 C. One-wy nlysis of vrine indited tht ph differed (P <.5) mong types of hiken met; it ws higher (P <.5) for skin (.1 ±.1) nd drk met (. ±.3) thn for white met (5.9 ±.11). However, initil log numer of ntive miroflor ws similr (P >.5) for skin (. ±.1 log/portion), drk met (.59 ±.1 log/portion), nd white met (.7 ±. log/portion). Thus, differenes in initil level of ntive miroflor did not explin differenes in growth of Slmonell Typhimurium DT1 mong different types of hiken met during old storge t 1, 1, or 1 C. However, the lower ph of white met Slmonell Typhimurium DT1 1 White Drk Skin 1 Time (dys) Figure Effet of time nd type of met on log numer of Slmonell Typhimurium DT1 on hiken met stored for to d t 1 C. Brs re mens ± stndrd devitions. Brs within luster with different supersripts differ (P <.5). Slmonell Typhimurium DT1 1 White Drk Skin Time (dys) Figure 5 Effet of time nd type of met on log numer of Slmonell Typhimurium DT1 on hiken met stored for to d t 1 C. Brs re mens ± stndrd devitions. Brs within luster with different supersripts differ (P <.5). my hve een ontriuting ftor to lower growth of Slmonell Typhimurium DT1 on white met ompred to drk met nd skin, whih hd higher ut similr ph. Bsed on previous study (Foster nd Med 197) it ws expetedtht thelog numerofslmonell Typhimurium DT1 on hiken met would derese during storge t to Cndtht the derese would e greter in drk met thn in white met. Insted, log numer of Slmonell Typhimurium DT1 on hiken met during storge t to C remined the sme throughout d of storge nd ws not ffeted y type of met. The ph of white met ws 5. nd ph of drk met ws. in the previous study (Foster nd Med 197) s ompred to ph of 5.9 for white met nd. for drk met in the present study. Thus, ph of hiken met ws similr mong studies nd therefore does not explin the differene in results. However, other experimentl onditions, suh s strin of Slmonell Typhimurium, previous history of the inoulum, inoulum size, nd ntive miroflor, differed mong these studies nd ould ount for the differene in results. Behvior of Slmonell on hiken met stored t refrigertion tempertures ( to C) is vrile mong studies. Shin nd others (1) report tht Slmonell Typhimurium grow from 3. to logs per grm on hiken rest met during 1 d of storge t C. In ontrst, Cosnsu nd Ayhn (1) found tht the numer of Slmonell Enteritidis deresed on hiken rest met from 5.3 log per m on dy to.1 log per m on dy 1 of storge t C. Shrm nd others (1) oserved tht the numer of Slmonell Typhimurium on hiken rest fillets deresed from.33 to 5.1 logs per grm during 7 d of storge t C. In the urrent study, the numer of Slmonell Typhimurium DT1 on hiken met delined slightly (. log) during storge for d t C. Other studies (Szzwinsk nd others 1991; Nyhs nd Tssou 199; Osr 11; Prdhn nd others 1) report tht the level of Slmonell on hiken met stys the sme during refrigerted storge. Together these studies indite tht ehvior of Slmonell on hiken met during refrigerted storge is omplex nd my depend on multiple ftors whose intertions re not well understood t the present time. Similr to ehvior of Slmonell on hiken met during proper refrigertion ( to C), ehvior of Slmonell on hiken met during improper refrigertion (7 to 1 C) is different mong studies inditing potentil intertion mong multiple ftors. In the presentstudy, Slmonell Typhimurium DT1 did not grow on hiken met stored for d t or 1 C. In ontrst, Bker nd others (19) report tht the numer of Slmonell Typhimurium on mined hiken met (rest nd leg) inreses from. to.1 log fter 5 d of storge t 7 C. Nissen nd others (1) found tht the numer of Slmonell Enteritidis on hiken rest met with skin inreses from 3.5 to 7 log per m fter d of storge t 1 C. Bsed on previous study (Osr 1) it ws expeted tht growth of Slmonell Typhimurium DT1 would e the sme on skin nd white nd drk met of hiken. Insted, growth of Slmonell Typhimurium DT1 ws highest on drk met, intermedite on skin, nd lowest on white met in the present study. One importnt differene etween studies ws the storge temperture, whih ws 3 C in the previous study (Osr 1) nd 1, 1, or 1 C in the urrent study. Thus, the effet of type of met on growth of Slmonell Typhimurium DT1 on hiken met my depend on storge temperture; dditionl studies re needed to lrify this issue. M9 Journl of Food Siene Vol. 79, Nr. 5, 1

6 Behvior of Slmonell on hiken met... Model development nd vlidtion Results of two-wy nlysis of vrine indited tht time, temperture, nd type of met were ll importnt vriles ffeting ehvior of Slmonell Typhimurium DT1 on hiken met during old storge. Thus, GRNN model ws developed to predit log numer of Slmonell Typhimurium DT1 on hiken met during old storge s funtion of these vriles. Dt olleted t storge tempertures of,,, 1, 1 (1st storge trils), nd 1 C were used to develop the GRNN model wheres dt olleted t storge tempertures of,, 1, nd 1 C (lst 1 or storge trils) were used to vlidte the GRNN model for its ility to interpolte. After the GRNN model ws developed, residuls (oserved log numer predited log numer) were evluted using the APZ method. A papz of.99 ws otined for dependent dt (Figure ) nd papz of.93 ws otined for independent dt (Figure 7). Beuse the papz for dependent dt ws.7, the GRNN model hd eptle goodness-of-fit (yes to Q1 in Tle 1). In ddition, the GRNN model ws vlidted for interpoltion (yes to Q in Tle 1) euse the papz for independent dt for interpoltion ws.7 (yes to Q5 in Tle 1) nd the vlidtion dt were independent (yes to Q in Tle 1), olleted with the sme methods s dependent dt (yes to Q3 in Tle 1), nd provided omplete overge of model preditions (yes to Q in Tle 1). To further evlute nd vlidte performne of the GRNN model, plots of the dependent vrile (log numer per portion) s funtion of the independent vriles (time, temperture, nd 1 Drk Skin White - º C º C º C 1 º C 1º C 1 º C Figure Aeptle predition zone (APZ) nlysis of GRNN model for ehvior of Slmonell Typhimurium DT1 on hiken met (dependent dt) s funtion of time, temperture, nd type of met. Dshed lines re APZ oundries. Residul (log) -1 M: Food Miroiology & Sfety - Time (dys) Drk Skin White - ºC ºC 1 ºC 1 ºC Figure 7 APZ nlysis of GRNN model for ehviorofslmonell Typhimurium DT1 on hiken met (independent dt) s funtion of time, temperture, nd type of met. Dshed lines re APZ oundries. 1 Residul (log) -1 - Time (dys) Vol. 79, Nr. 5, 1 Journl of Food Siene M93

7 Behvior of Slmonell on hiken met... type of met) were mde nd exmined. These plots ontined oserved dt (symols), predited log numer (solid line), nd APZ oundries (dotted lines). The purpose of the plots ws to look for lol predition prolems. Only plots with lol predition prolems re shown. For dependent dt, ll omintions of time, temperture, nd type of met hd papz.7 exept for skin stored for d t 1 C (Figure ). Here, filure of the GRNN model to provide n eptle predition ws due to vrition of log numer dt. This ould e due to experimentl error or it ould indite tht n importnt independent vrile ws missing from the model. For independent dt, ll omintions of time, temperture, nd type of met hd papz.7 exept for 5. They were storgeonskinfordt1 C (Figure9),storgeonskinfor or d t 1 C (Figure 1), nd storge on drk met for or d t 1 C (Figure 11). Here, lol predition prolems resulted from the GRNN model prediting growth t 1 C when survivl ourred nd in the se of skin t 1 C, limited dt. Nonetheless, in ll ses, the uneptle preditions were lose to the APZ oundries nd thus, not mjor onern. The finl step ws to onstrut user-friendly version of the GRNN model for use y the hiken industry to ssess impt of proess devitions on Slmonell ehvior (Figure 1). The finl model ws designed like the those in the U.S. Dept. of Agriulture, Pthogen Modeling Progrm; it predits log numer of Slmonell Typhimurium DT1 on hiken s funtion of time ( to d), temperture ( to 1 C), nd type of met (white, drk, or skin). As with ll models of this type, it predits pthogen ehvior for onditions used in model development nd for onditions not used in model development ut tht fll within rnges of independent vriles used to develop the model. For exmple, in Figure 1, M: Food Miroiology & Sfety Slmonell Typhimurium DT1 1 Oserved Predited APZ Figure APZ nlysis of GRNN model for ehvior of Slmonell Typhimurium DT1 on hiken skin stored t 1 C. Symols re oserved log numer (dependent dt), solid line is predited log numer, nd dshed lines re APZ oundries. Time (dys) Slmonell Typhimurium DT1 1 Oserved Predited APZ Figure 9 APZ nlysis of GRNN model for ehvior of Slmonell Typhimurium DT1 on hiken skin stored t 1 C. Symols re oserved log numer (independent dt), solid line is predited log numer, nd dshed lines re APZ oundries. Time (dys) M9 Journl of Food Siene Vol. 79, Nr. 5, 1

8 Behvior of Slmonell on hiken met... themodelpreditslognumerofslmonell Typhimurium DT1 on hiken skin for d of storge t temperture (15 C) not used in model development. The originl models for predition of food sfety were developed in lortory roth s funtion of time, temperture, ph, nd wter tivity (MClure nd others 199; Whiting 1995). The guiding philosophy ws tht these models would provide filsfe preditions of pthogen ehvior in food. However, roth models do not onsider miroil ompetition nd s result provide overly fil-sfe preditions. As shown in previous study for Slmonell nd hiken met (Osr 7), roth models n overpredit growth of Slmonell on hiken y s muh s 7 logs. Consequently, the hiken industry prefers models developed with hiken met rther thn lortory roth. Investigting nd modeling ehvior of Slmonell on hiken met is different from investigting nd modeling ehvior of Slmonell in lortory roth. In ft, the independent vriles tht hve the most influene on ehvior of Slmonell in lortory roth nd in hiken met differ. Of note, ph nd wter tivity vry little within single type of hiken met nd thus, re not highly influentil independent vriles in preditive models developed with hiken met. Identifying whih independent vriles re importnt to inlude in preditive model for Slmonell nd hiken met is importnt. Thus fr, 3 independent vriles, in ddition to time nd temperture, hve een identified tht re importnt to inlude in preditive models for Slmonell nd hiken met, they re: (1) serotype (Osr 9); () inoulum size (Osr 7, 11); nd (3) type of met (present study). An importnt onsidertion when developing nd vlidting preditive model for food sfety is tht it n err more in the fil-sfe diretion thn in the fil-dngerous diretion (Ross nd others ). However, it should not e llowed to err too muh in the fil-sfe diretion euse models tht provide overly Slmonell Typhimurium DT1 1 Oserved Predited APZ Figure 1 APZ nlysis of GRNN model for ehvior of Slmonell Typhimurium DT1 on hiken skin stored t 1 C. Symols re oserved log numer (independent dt), solid line is predited log numer, nd dshed lines re APZ oundries. M: Food Miroiology & Sfety Time (dys) Slmonell Typhimurium DT1 1 Oserved Predited APZ Figure 11 APZ nlysis of GRNN model for ehvior of Slmonell Typhimurium DT1 on hiken drk met stored t 1 C. Symols re oserved log numer (independent dt), solid line is predited log numer, nd dshed lines re APZ oundries. Time (dys) Vol. 79, Nr. 5, 1 Journl of Food Siene M95

9 Behvior of Slmonell on hiken met... M: Food Miroiology & Sfety fil-sfe preditions prevent onsumption of sfe food tht ould hve enefited puli helth. On the other hnd, model tht provides overly fil-dngerous preditions hrms puli helth y llowing distriution nd onsumption of food tht presents signifint risk. The preedent in preditive miroiology is to llow models to err twie s muh in the fil-sfe diretion (Ross nd others ). Consequently, preditions of the urrent GRNN model were onsidered eptle when they were in n APZ from 1 log (filsfe) to.5 logs (fil-dngerous). Moreover, the GRNN model ws onsidered to provide preditions with eptle ury nd is when the proportion of residuls in the APZ (papz) ws.7. In the urrent study, papz ws.99 for dependent dt nd.93 for independent dt. Beuse the independent dt for vlidtion met the test dt riteri for the APZ method (Tle 1), the GRNN model ws lssified s vlidted mening tht it provided preditions with eptle ury nd is or in other words, preditions tht were neither overly fil-sfe nor overly fil-dngerous. In previous studies (Aou-Zeid nd others 9; Osr 9), the APZ method ws pplied to omplete sets of dt nd more reently (Osr 11, 13) to individul survivl nd growth urves. In the urrent study, the APZ method ws lso pplied to individul omintions of independent vriles. This ws done to etter detet lol predition prolems. Although some lol predition prolems were deteted, s disussed ove, they were not of suffiient onern to wrrnt lssifition of nonvlidtion. However, they do indite tht the model n e improved y olletion of dditionl dt. Most models tht re used to predit food sfety hve een developed using regression methods nd 3 steps: (1) primry modeling, () seondry modeling, nd (3) tertiry modeling (Whiting nd Buhnn 199). Primry modeling involves fitting log numer dt otined under one omintion of independent vriles to mthemtil model tht desries growth, survivl, or deth s funtion of time. Seondry modeling involves modeling fitted prmeters of the primry model s funtion of independent vriles. Sustituting seondry models for prmeters in the primry model forms tertiry model tht predits log numer over time s funtion of independent vriles. The vlue of the tertiry model is tht it n generte predited growth, survivl, or deth urves for omintions of independent vriles tht were used in model development or were not used in model development ut tht fll within rnges of independent vrile omintions used in model development. In the urrent study, GRNN model ws developed for ehvior of Slmonell Typhimurium DT1 on hiken met during old storge. The GRNN model ws developed in one step using ommeril softwre nd funtions like tertiry model in tht it provides preditions of survivl, deth, nd growth urves for omintions of independent vriles tht were nd were not used in model development. Development of tertiry or tertiry-like models in one step, s ws done in the present study, sves time nd money, is simpler thn 3-step modeling proess, nd s shown in previous study (Mrtino nd Mrks 7) redues predition error of the finl model. Colletion of dt for development of preditive models for Slmonell nd hiken met is time onsuming nd expensive. Smll hiken met portions (.75 m 3 ) in 1.5 ml miroentrifuge tues tht were inuted in tletop heting nd ooling dry loks were used in the present study to mke it less time Figure 1 GRNN model for prediting survivl, deth, nd growth of Slmonell Typhimurium DT1 on hiken met s funtion of time ( to d), onstnt temperture ( to1 C), nd type of met (white, drk, or skin). M9 Journl of Food Siene Vol. 79, Nr. 5, 1

10 Behvior of Slmonell on hiken met... onsuming nd expensive to ollet dt for model development nd vlidtion. In ddition, use of smll met portions filitted enumertion of low levels of Slmonell. One finl issue to ddress is why the predition is (B f )nd ury ftor (A f ) method (Ross 199; Ross nd others ) ws not used to evlute nd vlidte the present GRNN model. The B f nd A f method ws originlly used to evlute performne of seondry models for genertion time (GT): B f = 1 ( log(gt predited/gt oserved)/n) () A f = 1 ( log(gt predited/gt oserved) /n) (3) The performne indies re men vlues of normlized predited vlues. However, when the B f nd A f method re pplied to GRNN models tht predit log numer of Slmonell on hiken met (Osr 9), for the sme log differene etween oserved nd predited vlues (for exmple, 1 log), normlized predited vlues re lrge (for exmple, 1.1/.1 = 11) when oserved vlues re smll nd they re smll (9.5/.5 = 1.1) when oserved vlues re lrge. Thus, B f nd A f were not used to evlute nd vlidte the urrent GRNN model euse of systemti predition is error in their omputtion when pplied to models tht predit log numer. Conlusions A GRNN model for survivl, deth, nd growth of Slmonell Typhimurium DT1 on hiken met during old storge ws suessfully developed nd vlidted ginst independent dt. Results indited tht during improper refrigertion (1 to 1 C) growth of Slmonell Typhimurium DT1 ws highest on drk met, intermedite on skin, nd lowest on rest met. Thus, it ws importnt to inlude type of met s n independent vrile in the model to otin relile preditions of Slmonell ehvior on hiken met during old storge. How rodly the model n e pplied to other strins of Slmonell, other inoulum sizes, other previous histories, nd flututing tempertures remins to e determined in future vlidtion studies for extrpoltion. Aknowledgments The uthor ppreites the tehnil ssistne of Mrgo Wright (U.S. Dept. of Agriulture, Agriulturl Reserh Servie) nd Moir Imegwu (Univ. of Mrylnd Estern Shore). Mention of trde nmes or ommeril produts in this pulition is solely for providing speifi informtion nd does not imply reommendtion or endorsement y the U.S. Dept. of Agriulture (USDA). The USDA is n equl opportunity provider nd employer. Referenes Aou-Zeid KA, Osr TP, Shwrz JG, Hshem FM, Whiting RC, Yoon K. 9. Development nd vlidtion of preditive model for Listeri monoytogenes Sott A s funtion of temperture, ph, nd ommeril mixture of potssium ltte nd sodium diette. J Miroiol Biotehnol 19:71. Bker RC, Qureshi RA, Hothkiss JH. 19. Effet of n elevted level of ron dioxide ontining tmosphere on the growth of spoilge nd pthogeni teri t, 7, nd 13 C. Poult Si 5: Cosnsu S, Ayhn K. 1. Effets of lti nd eti id on survivl of Slmonell enteritidis during refrigerted nd frozen storge of hiken mets. Food Bioproess Teh, doi: 1.17/s x. Foster RD, Med GC Effet of temperture nd dded polyphosphte on the survivl of slmonelle in poultry met during old storge. J Appl Bteriol 1:55 1. Gri-Gimeno RM, Hervs-Mrtinez C, Bro-All E, Zurer-Cosno G, Snz-Tpi E. 3. An rtifiil neurl network pproh to Esherihi oli O157:H7 growth estimtion. J Food Si :39 5. Hjmeer MN, Bsheer IA, Njjr YM Computtionl neurl networks for preditive miroiology II. Applition to miroil growth. Int J Food Miroiol 3:51. Jeymkondn S, Jys DS, Holley RA. 1. Miroil growth modelling with rtifiil neurl networks. Int J Food Miroiol :33 5. Mrtino KG, Mrks BP. 7. Compring unertinty resulting from two-step nd glol regression proedures pplied to miroil growth models. J Food Prot 7:11. MClure PJ, Blkurn CW, Cole MB, Curtis PS, Jones JE, Legn JD, Ogden ID, Pek MW, Roerts TA, Sutherlnd JP, Wlker SJ Modelling the growth, survivl nd deth of miroorgnisms in foods: the UK Food Miromodel pproh. Int J Food Miroiol 3:5 75. Nissen H, Mugesten T, Le P. 1. 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