李汴生,彭紅梅,張德潤,阮 征
基于感官品質(zhì)的油梨常溫后熟進程預(yù)測模型
李汴生,彭紅梅,張德潤,阮 征※
(華南理工大學食品科學與工程學院,廣州 510640)
針對中國油梨市場油梨進口儲運過程中儲藏時間和品質(zhì)變化難以把控及油梨損壞嚴重等問題,對常溫常濕 ((25±1 )℃、75%相對濕度) 條件下果皮色澤、果肉硬度及感官品質(zhì)指標進行測定,監(jiān)測其在常溫后熟過程中的內(nèi)在變化規(guī)律,對色差、硬度、呼吸速率、質(zhì)量損失率與果肉受喜愛程度進行皮爾遜相關(guān)性分析,利用無損檢測指標色差*值與儲藏時間之間logistic方程,建立油梨后熟時間預(yù)測模型。結(jié)果表明:油梨平均單果質(zhì)量隨儲藏時間的延長而減少,每日質(zhì)量損失率和呼吸速率均呈現(xiàn)先增加后減少的趨勢,果皮色澤在儲藏時間小于3 d時顯著增加,其后趨于平衡,而果肉硬度表現(xiàn)相反的趨勢,干基質(zhì)量損失率、色澤(L,a和b值)和硬度均與感官喜愛度呈顯著相關(guān)性(<0.01)?;谏顪y定的無損、快速、便捷,選取色差*值進行預(yù)測模型的建立,色差*值的logistic方程擬合效果較好,2為0.993。模型的檢驗發(fā)現(xiàn),在色差*值<4時,模型預(yù)測值與實測值有很好的線性相關(guān)性,決定系數(shù)為0.996,說明該模型在果皮色差*值<4時可以用于油梨常溫后熟期的預(yù)測,研究結(jié)果可為油梨品質(zhì)控制提供指導和依據(jù)。
預(yù)測;模型;農(nóng)產(chǎn)品;油梨;常溫;后熟
果蔬品質(zhì)是指能滿足消費者要求和期望的綜合屬性,包括感官品質(zhì)、營養(yǎng)品質(zhì)等多個方面[1],果蔬采后隨儲藏時間的延長,其品質(zhì)會逐步變化、甚至老化、衰敗,最后失去商品性。感官品質(zhì)作為重要的品質(zhì)特性具有判斷直觀、快速的特點,同時其品質(zhì)變化與儲藏時間、儲藏溫度、處理條件等密切相關(guān),因此在果蔬的采后儲藏過程中,感官品質(zhì)變化成為研究重點。如采后獼猴桃硬度變化的研究[2-4],香蕉風味、硬度、表皮顏色變化的研究[5],芒果硬度、風味等的變化研究[6-8]。隨著傳感器技術(shù)、數(shù)學統(tǒng)計、化學分析、微生物分析及感官分析技術(shù)的發(fā)展,基于果蔬感官品質(zhì)特性[9]及其衰變理論[10]而建立的預(yù)測模型被廣泛應(yīng)用于果蔬采后儲藏管理,以預(yù)測、評估果蔬儲藏過程中的品質(zhì)變化。如利用芒果儲藏過程力學指標[11]、顏色值、硬度[12]等建立的儲藏期預(yù)測模型和品質(zhì)預(yù)測模型,基于質(zhì)量損失率國產(chǎn)獼猴桃儲藏期預(yù)測模型[13],利用近紅外光譜測定獼猴桃硬度的預(yù)測模型[14-15],基于番茄果實采后色澤、質(zhì)構(gòu)等建立的采后品質(zhì)及貨架期預(yù)測模型[16-18]等等。預(yù)測模型的建立能有效并全面的掌握果實的后熟進程,做到有效調(diào)控、監(jiān)管,從而為果蔬采后儲藏、流通、加工等提供依據(jù),具有重要的生產(chǎn)應(yīng)用價值[19]。
油梨又名鱷梨、酪梨、樟梨、牛油果,富含脂肪(脂肪含量可高達其干物質(zhì)量的70%),含2%的蛋白質(zhì)及多種糖類(葡萄糖,果糖、蔗糖、庚酮糖),纖維素、礦物質(zhì)、維生素、類胡蘿卜素、甾醇等多種生物活性成分,具有降低膽固醇含量,提升免疫功能,控制體質(zhì)量、降低冠心病風險等多項生理作用[20-21]。隨著國民生活水平及健康意識的提升,油梨已成為中國消費者熱捧的水果,中國油梨的進口量從2011年的31.8 t上升至2017年的3.21萬t。
油梨是一類呼吸躍變型的水果,具有呼吸變化明顯、成熟快、后熟時間短等特點。伴隨后熟過程一系列的生理生化反應(yīng),其果實的硬度、乙烯生成量、果皮色澤、PPO (polyphenol oxidase)活力、細胞壁降解酶活力、口感、風味等[22-28]均會隨果實成熟度變化,現(xiàn)有的研究發(fā)現(xiàn)油梨感官品質(zhì)是表征果實成熟情況的重要指標,也是油梨研究的重點。為加強油梨儲藏過程中的管理,國外已有通過色差Hue值預(yù)測模型[29]、近紅外無損檢測建立PLS回歸模型等[30]來預(yù)測管理油梨的品質(zhì)變化。但對于中國3.21萬t的油梨市場,如何科學有效的進行油梨的市場流通 (儲藏、運輸),成為中國油梨發(fā)展的產(chǎn)業(yè)問題。因此本試驗旨在探究常溫 (25 ℃) 儲藏條件下易于監(jiān)控、測定的品質(zhì)指標,通過其變化規(guī)律及動力學特性的分析而建立預(yù)測模型,揭示各品質(zhì)指標常溫 (25 ℃) 條件下內(nèi)在的變化規(guī)律性,從而實現(xiàn)通過簡單、快速的測定預(yù)測油梨的后熟進程,為油梨常溫 (25 ℃) 儲運、銷售、生產(chǎn)加工過程中品質(zhì)的計算機模擬與控制提供依據(jù)。
油梨:Hass品種,購買于廣州五山某水果超市。同一批次,整果無機械損傷,依據(jù)形狀、質(zhì)量、成熟度的均一性選擇樣品[24]。
試驗樣品選擇:果形、果皮色澤基本一致,整果呈綠色,單果質(zhì)量(195±2) g。
物性測定儀(TA. XT. Plus),英國 Stable Micro System 公司;色差儀(CR-400),日本 Konica Minolta 公司;電子天平(PL203),梅特勒-托利多儀器上海有限公司。
將果形、色澤、大小一致的一批油梨放置在(25± 1) ℃、相對濕度75%條件下儲存,每間隔24 h測定其各品質(zhì)指標直至其果蒂處果肉呈白色結(jié)束試驗(本試驗儲藏第9天)。
1.3.1 呼吸速率的測定
25 ℃條件下,將試驗油梨放置在2 L磨口瓶內(nèi)2 h,用橡膠塞密封,事先用打孔器在橡膠塞上打2個孔,安裝玻璃管、乳膠管和止水夾為測氣裝置。用氣體測定儀測定放置前后瓶內(nèi)CO2的含量。利用密閉系統(tǒng)法方程計算呼吸速率,單位用mg/kg·h表示,每組試驗設(shè)3個重復[31]。
1.3.2 平均單果質(zhì)量的測定
隨機取樣3個果,采用電子天平(PL203)進行質(zhì)量測定,計算平均單果質(zhì)量、干基質(zhì)量損失率和每日質(zhì)量損失率[24, 32]。
油梨果肉干物質(zhì)質(zhì)量的測定:隨機取剛買到的3個油梨,每個油梨均分為4份,選取1/4果肉去核混勻制漿,稱取20 g樣品置于70 ℃烘箱中烘干至恒質(zhì)量,3組平行,計算油梨果肉干物質(zhì)質(zhì)量[33](dry weight,DW)。
式中0為初始平均單果質(zhì)量,g;W為第天平均單果質(zhì)量,g;DW為果肉干物質(zhì)質(zhì)量,g;W+1,第(+1)天平均單果質(zhì)量,g。
1.3.3 果皮色澤的測定
隨機取樣3個果,采用色差儀(CR-400)測定果實赤道處對角線4個點的色差值表示果皮色澤。色差測定結(jié)果用L、a、b表示,平行測定4次。其中L表示亮度,a表示紅綠度,b表示黃藍度[26-27]。每組試驗設(shè)3個重復。
1.3.4 硬度的測定
隨機取樣3個果,將油梨果實赤道處對角線上4點的外層果皮削去,采用TA. XT. Plus物性測定儀測定果肉硬度[21, 28, 34]。測定條件:采用P/2n針狀探頭,測前速率5 mm/s,貫入速度1 mm/s,測后速度5 mm/s,最小感知力5 g,穿刺深度8 mm。計算硬度變化率。
式中0為初始硬度值,N;H為第天的硬度值,N。
1.3.5 油梨風味及喜愛檢驗
取不同后熟期的油梨,選取果核區(qū)域果肉,切成大小一致的正方體(13 mm)果肉塊,采用任意組合的3位數(shù)編號,分裝于一次性紙碟中。挑選6位評價員對果肉進行評分,選取6種風味術(shù)語,分別是多汁感、脂肪感、平滑感、堅果味、黃油味、青草味[23]來進行評價,每種風味特性的強度總分定5分,得分越高表明此種風味強度越高。果肉喜愛檢驗評分采用0~9分,0分表示非常不喜歡,9分表示非常喜歡。各評價員獨立評定,每評定一個樣品,用清水漱口,間隔 6 min 后再品評下一個樣品,每個試樣重復 3 次,最后收集評定結(jié)果進行統(tǒng)計分析。
采用Excel 2010進行數(shù)據(jù)處理和圖形繪制,方差分析采用新復極差分析法Duncan,取95%的置信區(qū)間(0.05),結(jié)果采用“均值±標準差”的形式表示。
油梨平均單果質(zhì)量及呼吸作用的變化如圖1、圖2所示。如圖1可知隨儲藏時間的延長,平均單果質(zhì)量不斷減少,干基質(zhì)量損失率不斷增加[24, 35]。圖2反映了油梨常溫 (25 ℃)條件下呼吸產(chǎn)生的CO2量隨時間的變化情況,CO2生成速率隨時間先不斷增加,第3天達最大,此時呼吸速率最大,隨后CO2生成速率減少,呼吸速率下降。如圖可知呼吸產(chǎn)生的CO2量有明顯的峰值,油梨常溫 (25 ℃)儲藏過程有明顯的呼吸躍變點。此試驗的第3天為其呼吸躍變點。伴隨后熟過程的呼吸作用,油梨每日質(zhì)量損失率呈先增加后減少的趨勢,呼吸躍變點處每日質(zhì)量損失率最大,且圖中反映每日質(zhì)量損失率與呼吸速率呈正相關(guān)。
圖1 平均單果質(zhì)量、干基質(zhì)量損失率的變化情況
圖2 CO2生成速率和每日質(zhì)量損失率的變化情況
果皮色澤通常被作為判斷油梨成熟的一個重要指標[25]。果皮色差測定結(jié)果如圖3所示。隨儲藏時間的延長,色差*、*值不斷減少,*值不斷增大,色差曲線拐點出現(xiàn)在試驗的第3天,即油梨的呼吸躍變點,此時果皮色差*=26.18±1.25、*=3.54±0.81、*=4.80±1.32,其變化率分別為24.46%、133.11%、73.78%,果皮色差*值變化率最大。第4天開始,果皮色差*、*、*值基本保持不變。色澤變化與其果皮中所含色素有關(guān),研究發(fā)現(xiàn)油梨果皮色澤主要由其果皮中所含葉綠素決定[25],而葉綠素的降解主要發(fā)生在呼吸躍變點之前,因此本試驗條件下果皮色澤變化主要發(fā)生在第0~3天。
常溫(25 ℃)儲藏條件下色差*值與果皮外觀色澤變化情況如圖4所示。試驗發(fā)現(xiàn),色差*值伴隨果皮外觀色澤的變化其值從-10.69不斷上升至4.0,并維持這一值不變。如圖所示當果皮色澤呈綠色時,此時色差*值<0;伴隨果皮由綠色變化至紫色,*值不斷增加,第2天,果皮呈深紫色,此時果皮色差*=0;從試驗第3天開始,油梨的果皮呈黑色,此時色差*≥4.0。
注:L*、a*、b*為亮度、紅綠度、黃藍度,下同。
果肉硬度是反映油梨采后成熟行為的一個重要指標[35-36],圖5反映了不同儲藏時間硬度的變化情況,隨著儲藏時間的延長,油梨果肉硬度不斷下降,前3天硬度下降明顯,從最初的(144.20±2.23) N下降至第3天的(8.04±0.83) N,硬度下降94.4%。從后熟的第4天開始,油梨的硬度值達到Donetti等[21-24]定義的最佳可食硬度(4.4~6.7)N。硬度下降、果肉變軟源于儲藏過程中伴隨時間的延長細胞壁中各類酶對果膠和半纖維素的作用,原果膠不斷被降解成果膠酸、果膠[28],同時細胞薄層消失,原纖維細胞大量減少等[37]。
圖4 果皮色澤的變化情況
圖5 硬度變化情況
油梨常溫(25 ℃)條件下儲藏風味變化情況如圖6所示。如圖可知,果肉脂肪感、平滑感、堅果味、黃油味均隨常溫(25 ℃)儲藏時間的延長而增強,平滑感、堅果味、黃油味從第4天開始基本保持不變,脂肪感在第7天趨于平緩。青草味在儲藏開始階段感覺明顯,儲藏至第3天青草味基本消失。果肉多汁感隨儲藏時間呈先增強后減弱的趨勢,第4天多汁感最為明顯。油梨受喜愛程度隨油梨果肉脂肪感、平滑感、堅果味、黃油味的增強、果肉青草味的降低而增加,后熟至第3天果肉喜愛程度評分為6.5,被品評人員接受,隨后熟時間的延長,果肉喜愛度增強并趨于平緩[23]。
圖6 油梨感官品質(zhì)的變化
2.5.1 果肉各測定感官品質(zhì)指標與感官喜愛程度評分之間的相關(guān)性
常溫(25 ℃)儲藏條件下各測定指標與感官喜愛度評分之間的相關(guān)性如表1所示。由表可知:在所有相關(guān)檢測指標中,呼吸速率與感官喜愛度沒有顯著相關(guān),而干基質(zhì)量損失率、色差值、硬度值與感官評分在0.01水平下顯著相關(guān),其中干基質(zhì)量損失率、色差a值與感官喜愛程度呈正相關(guān),伴隨干基質(zhì)量損失率、色差a值的增加,感官喜愛程度評分增大。為實現(xiàn)無損、快捷、方便預(yù)測油梨后熟,本研究最終選取色差a值作為油梨常溫(25 ℃)儲藏過程品質(zhì)變化和儲藏時間動力學預(yù)測模型的關(guān)鍵因素。
表1 各品質(zhì)指標與感官喜愛度之間的皮爾遜相關(guān)系數(shù)表
注:**代表顯著性水平為0.01。
Note:**represents significant level at 0.01.
2.5.2 色差值Logistic方程的建立
通過對色差*值隨時間變化的觀察,以色差*值為因變量,使用Logistic方程對原始的*測定數(shù)據(jù)在Origin中進行擬合分析,結(jié)果如圖7所示,得到的Logistic方程為
=2(1-2)/(1+(/0)) (4)
得到的擬合結(jié)果中,1=-10.681,2=4.261,0=1.576,=5.053,得到的Logistic方程為
模型的檢驗選取同一批次中果皮呈綠色、紫色和黑色的油梨,測定果皮色差值,通過色差值的logistic方程對油梨儲藏時間進行預(yù)測,然后將果實放置在溫度為(25±1) ℃、相對濕度為75%的試驗條件下,每8 h觀察一次,當油梨果蒂處果肉呈白色時結(jié)束試驗,此時間段即為油梨的可放置時間(用1表示),油梨儲藏時間的測定值用表示,其中=9-1。預(yù)測值與測定值的線性關(guān)系如圖8所示,從圖中散點圖的分布情況可知,油梨儲藏時間在第0~4天時,預(yù)測值與測定值均勻分布在對角線兩側(cè),預(yù)測值和測定值有很好的線性相關(guān)性,此階段的決定系數(shù)為0.996,此時果皮色差<4。而在油梨儲藏的第5~9天,儲藏時間的測定值往往大于其預(yù)測值,預(yù)測準確性下降,此時果皮色差≥4。這與油梨果皮后熟過程中色澤的變化有關(guān),后熟過程中伴隨葉綠素的降解,果皮色澤從綠色逐漸變化成黑色,并隨儲藏時間的延長而維持不變,此時色差值不變,通過果皮色差值的logistic方程得到的預(yù)測值不變,因而所建立的模型無法應(yīng)用于色差≥4的情況。
圖7 色差a*值logistic曲線
圖8 模型檢驗組預(yù)測值與實測值的散點圖
對于油梨這類呼吸躍變型水果,為延長果實的儲藏期,通常會選取果實成熟度較低時進行采摘,以減少機械損傷和微生物侵擾,但此時的果實并不處于最佳的食用期,通常需要儲藏期間的后熟,保證果實的實用品質(zhì)。
本文充分研究了油梨常溫(25 ℃)儲藏條件下果實色澤、硬度、風味等的變化。試驗結(jié)果表明隨儲藏時間的延長,油梨感官品質(zhì)逐步完善,硬度下降至最佳可食硬度值(4.4~6.7)N、果皮顏色從綠色變化至黑色,果肉青草味消失,堅果味、黃油味凸顯,果肉受喜愛程度增加,后熟對于油梨果實品質(zhì)是一個必要的過程。
常溫(25 ℃)儲藏條件下,油梨有明顯的呼吸躍變點,且呼吸躍變點與色澤、硬度、感官品質(zhì)的變化密切相關(guān)。結(jié)合儲藏過程感官品質(zhì)與呼吸速率發(fā)現(xiàn),油梨常溫(25 ℃)儲藏條件下其感官品質(zhì)的變化主要發(fā)生在呼吸躍變點及之前的階段,此時硬度、色澤、風味等變化明顯。
油梨的感官品質(zhì)受成熟情況影響,通過儲藏過程色差、硬度、呼吸速率、質(zhì)量損失率與果肉受喜愛程度之間的皮爾遜相關(guān)系數(shù)的比較分析,確定色差*值為油梨儲藏預(yù)測模型關(guān)鍵指示因素,并建立色差*值logistic方程,方程的擬合效果2為0.993,在色差*<4時,模型預(yù)測值與實測值的決定系數(shù)為0.996,表明此模型在色差*<4時具有較高的擬合度,對實際應(yīng)用具有一定的參考價值。
[1] 汪琳,應(yīng)鐵進. 番茄果實采后貯藏過程中的顏色動力學模型及其應(yīng)用[J]. 農(nóng)業(yè)工程學報,2001,17(3):118-121. Wang Lin, Ying Tiejin. Kinetic model on surface color in tomato fruits during the post-harvest storage and its applic-ation[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2001, 17(3): 118-121. (in Chinese with English abstract)
[2] 羅靜,郭琳琳,黃玉南,等. 獼猴桃PG基因在果實貯藏過程中的表達及其與硬度的關(guān)系[J]. 園藝學報,2018,45(5):865-874. Luo Jing, Guo Linlin, Huang Yunan, et al. Relationship between PG gene expression and fruit firmness during kiwifruit storage[J]. Acta Horticulturae Sinica, 2018, 45(5): 865-874. (in Chinese with English abstract)
[3] 俞靜芬,尚海濤,凌建剛,等. 1-MCP結(jié)合微孔保鮮膜對獼猴桃出庫貨架期品質(zhì)影響研究[J]. 農(nóng)產(chǎn)品加工,2018,2:4-5. Yu Jingfen, Shang Haitao, Ling Jiangang, et al. 1-MCP combined with microporous preservative film influence on kiwifruit storage shelf quality[J]. Farm Products Processing, 2018, 2: 4-5. (in Chinese with English abstract)
[4] 曹森,馬超,吉寧,等. 1-MCP對不同成熟度紅陽獼猴桃保鮮效果及后熟品質(zhì)的影響[J]. 食品科技,2018,43(11):29-37. Cao Sen, Ma Chao, Ji Ning, et al. Effects of 1-MCP on preservation and ripening quality of “hongyang” kiwifruit with different maturity[J]. Food Science and Technology, 2018, 43(11): 29-37. (in Chinese with English abstract)
[5] 淡明,黃梅華,梁曉君,等. 不同催熟條件對香蕉后熟均勻性的影響研究[J]. 熱帶作物學報,2018,39(6):1095-1101. Dan Ming, Huang Meihua, Liang Xiaojun, et al. The effect of ethylene ripening conditions on the ripening uniformity of different harvest maturity banana fruit[J]. Chinese Journal of Tropical Crops, 2018, 39(6): 1095-1101. (in Chinese with English abstract)
[6] 徐方旭,柳葉飛,劉詩揚,等. 1-MCP結(jié)合殼聚糖處理延緩芒果果實后熟與衰老的研究[J]. 食品工業(yè),2016,37(12):92-94. Xu Fangxu, Liu Yefei, Liu Shiyang, et al. Study on the delay of mango fruit ripening and senescence by using 1-MCP and chitosan coating treatment[J]. The Food Industry, 2016, 37(12): 92-94. (in Chinese with English abstract)
[7] 邵遠志,張哲,李庚虎,等. 采收成熟度與后熟處理對紅貴妃芒果貯藏品質(zhì)和生理的影響[J]. 保鮮與加工,2010,3(10):17-21. Shao Yuanzhi, Zhang Zhe, Li Genghu, et al. Effects of harvest maturity on storage quality anphysiology of mango fruit (cv. Hongguifei)[J]. Storage and Process, 2010, 3(10): 17-21. (in Chinese with English abstract)
[8] 劉英. 熱浸處理對芒果漿加工原料質(zhì)量的影響[D]. 南寧:廣西大學,2011. Liu Ying. The Effect of Hot Water Immersion Treatment on Quality of Raw Materials of Mango Pulp[D]. Nanning: Guangxi University, 2011. (in Chinese with English abstract)
[9] Pathare P B,Opara U L,AlSaid F A J. Colour measurement and analysis in fresh and processed foods: A review[J]. Food & Bioprocess Technology, 2013, 6(1): 36-60.
[10] 史波林,趙鐳,支瑞聰. 基于品質(zhì)衰變理論的食品貨架期預(yù)測模型及其應(yīng)用研究進展[J]. 食品科學,2012,33(21):345-350. Shi Bolin, Zhao Lei, Zhi Ruicong. Advances in predictive shelf life models based on food quality deterioration theory and their applications[J]. Food Science, 2012, 33(21): 345-350. (in Chinese with English abstract)
[11] 沈力,胥義,鈕怡清. 小臺農(nóng)芒果力學特性及其貯藏期預(yù)測模型的研究[J]. 食品與發(fā)酵工業(yè),2015,41(4):212-218. Shen Li, Xu Yi, Niu Yiqing. Research on mechanical properties and storage life prediction model of mango under storage temperatures[J]. Food and Fermentation Industries, 2015, 41(4): 212-218. (in Chinese with English abstract)
[12] 李敏,高兆銀,蘇增建,等. 基于芒果果肉顏色的品質(zhì)檢測技術(shù)[J]. 熱帶作物學報,2017,38(1):166-170. Li Min, Gao Zhaoyin, Su Zengjian, et al. Quality evaluation of mango by fresh colorimetric measurements[J]. Chinese Journal of Tropical Crops, 2017, 38(1): 166-170. (in Chinese with English abstract)
[13] 顧海寧,李強,陳晨,等. 獼猴桃儲藏期品質(zhì)變化研究及預(yù)測模型建立[J]. 食品工業(yè),2014,35(6):7-10.Gu Haining, Li Qiang, Chen Chen, et al. Quality change and storage period forecast mode of domestic kiwi[J]. The Food Industry, 2014, 35(6): 7-10. (in Chinese with English abstract)
[14] 呂強,湯明杰,趙杰文,等. 近紅外光譜預(yù)測獼猴桃硬度模型的簡化研究[J]. 光譜學與光譜分析,2009,29(7):1768-1771.
[15] Arpaia M L, Collin S, Sievert J, et al. Influence of cold storage prior to and after ripening on quality factors and sensory attributes of ’Hass’ avocados[J]. Postharvest Biology & Technology, 2015, 110: 149-157.
[16] Obenlanda D, Sievert J, Negm F, et al. Influence of maturity and ripening on aroma volatiles and flavor in ’Hass’ avocado[J]. Postharvest Biology & Technology, 2012, 71: 41-50.
[17] ElAguirre-Joya J A, Ventura-Sobrevilla J, Martínez- Vazquez G, et al. Effects of a natural bioactive coating on the quality and shelf life prolongation at different storage conditions of avocado (Mill.) cv. Hass[J]. 2017, 14: 102-107.
[18] Cox K A, McGhie T K, White A, et al. Skin colour and pigment changes during ripening of ’Hass’ avocado fruit[J]. Postharvest Biology and Technology, 2004, 31(3): 287-294.
[19] Ge Yu, Si Xiongyuan, Cao Jianqiu, et al. Morphological characteristics, nutritional quality, and bioactive constituents in fruits of two avocado () varieties from Hainan Province, China[J]. Journal of Agricultural Science 2017, 9(2): 8-17.
[20] Vargas-Ortiz M, Rodríguez-Jimenes G, Salgado-Cervantes M, et al. Minimally processed avocado through flash vacuum- expansion: Its effect in major physicochemical aspects of the puree and stability on storage[J]. Journal of Food Processing and Preservation, 2017, 41(3): 1-10.
[21] Maftoonazad N, Ramaswamy H S. Effect of pectin-based coating on the kinetics of quality change associated with stored avocados[J]. Journal of Food Processing & Preservation, 2008, 32(4): 621-643.
[22] Hertog M L A T. The impact of biological variation on postharvest population dynamics[J]. Postharvest Biology & Technology, 2002, 26(3): 253-263.
[23] Olarewaju O O, Bertling I, Magwaza L S. Non-destructive evaluation of avocado fruit maturity using near infrared spectroscopy and PLS regression models[J]. Scientia Horticulturae, 2016, 199: 229-236.
[24] Villa-Rodríguez J A., Molina-Corral F J, Ayala-Zavala J F, et al. Effect of maturity stage on the content of fatty acids and antioxidant activity of ‘Hass’ avocado[J]. Food Research International, 2011, 44(5): 1231-1237.
[25] 高佳,王寶剛,馮曉元,等. 甜櫻桃和酸櫻桃品種果實性狀的綜合評價[J]. 北方園藝,2011,1(7):17-21. Gao Jia, Wang Baogang, Feng Xiaoyuan, et al. Composite appreciation of fruit charaters in sweet cherry and sour cherry cultivars[J]. Northern Horticulture, 2011, 1(7): 17-21. (in Chinese with English abstract)
[26] Ozdemir F, Topuz A. Changes in dry matter, oil content and fatty acids composition of avocado during harvesting time and post-harvesting ripening period[J]. Food Chemistry, 2004, 86(1): 79-83.
[27] 馬慶華,王貴禧,梁麗松. 質(zhì)構(gòu)儀穿刺試驗檢測冬棗質(zhì)地品質(zhì)方法的建立[J]. 中國農(nóng)業(yè)科學,2011,44(6):1210-1217. Ma Qinghua, Wang Guixi, Liang Lisong. Establishment of the detecting method on the fruit texture of dongzao by puncture test[J]. Scientia Agricultura Sinica, 2011, 44(6): 1210-1217. (in Chinese with English abstract)
[28] Arzate-Vázquez I, Chanona-Pérez J J, Perea-Flores M De J, et al. Image processing applied to classification of avocado variety hass (Mill.) during the ripening process[J]. Food and Bioprocess Technology, 2011, 4(7): 1307-1313.
[29] Magwaza L S, Tesfay S Z. A Review of destructive and non-destructive methods for determining avocado fruit maturity[J]. Food and Bioprocess Technology, 2015, 8(10): 1995-2011.
[30] Goulao L, Oliveira C. Cell wall modifications during fruit ripening: When a fruit is not the fruit[J]. Trends in Food Science & Technology, 2008, 19(1): 4-25.
Prediction model of avocado ripening process based on sensory quality at room temperature
Li Biansheng, Peng Hongmei, Zhang Derun, Ruan Zheng※
(510640,)
‘Hass’ avocado is enjoyed by consumers worldwide due to its rich flavor, high overall quality and health related attributes. The nutritional and dense phytochemical composition of avocado is attracting more consumers. Avocados do not ripen on the tree and must be ripened after harvest, which means that most or all of the ripening process needs to be carefully controlled in the commercial postharvest environment. In view of the problems that the storage time and quality changes of avocado during the storage and transportation in the Chinese avocado market are difficult to be controlled, as well as that avocado is easy to be damaged, the color of the avocado peel, the hardness of the avocado pulp, and the sensory quality indicators at room temperature (25±1 ℃, 75% RH) were measured to monitor their intrinsic variation during ripening in this study. The Pearson correlation analysis between the affection degree of avocado flesh and the color difference, hardness, respiration rate, weight loss rate, respectively, was also performed. At last, the prediction model for the ripening of avocado was developed based on first-order functional equation, logistic equation of dry weight loss rate-and the color differencevalue-storage time. The results showed that the weight of avocado fruit decreased from 195.2±0.9 to 181.2±0.8 with the prolongation of storage time (0-9 d), and the daily weight loss rate and respiration rate increased first at the storage time of 0~3 d and then decreased sharply. Conversely, the peel color, characterized by(34.66±1.27),a(-10.69±1.29) andbvalues (18.31±1.56), changed significantly when the storage time was less than 3 d, and then tended to constant (~25.63, ~4.19, and~3.45, respectively). However, the avocado flesh hardness decreased from 144.2N to 8.04N during storing for 3 d and reached equilibrium when the storage time exceeded 3 h. Additionally, apart from the respiratory rate (=-0.221), the dry weight loss rate, peel color (L,aandbvalues), and avocado flesh hardness during storing at room temperature were significantly correlated with sensory preference scores (<0.01), in which the dry weight loss rate (=0.840)andavalue (=0.915) were positively related to sensory preference scores, and flesh hardness (=-0.954),L(=-0.947), andbvalues (=-0.952) were negatively related to sensory preference scores. Based on determination of the color of avocado peel were nondestructive, fast, convenient, hereinvalue was selected as key indicators to establish the prediction model of avocado quality change during storing. At the storage time of 0-9 d, thevalue was fitted well based on logistic equation.2values was 0.993. In the validation experiments,whenvalue less than 4, thepredicted and the measured values have a good linear correlation,the decision coefficient is 0.996, indicating that the developed model can be used to predict the ripening period of avocado at room temperature whenvalue less than 4. The research results in this work can provide favorable guidance and basis for quality control of avocado.
prediction; models; agricultural products; avocado; room temperature; ripening
10.11975/j.issn.1002-6819.2019.13.034
TS255.3
A
1002-6819(2019)-13-0285-07
2018-11-10
2019-05-10
國家重點研發(fā)計劃項目:食品高效冷凍解凍關(guān)鍵技術(shù)及裝備開發(fā)(2017YFD0400404)
李汴生,教授,博士,主要從事食品加工和保藏研究。Email:febshli@scut.edu.cn
阮 征,副教授,博士,主要從事食品加工和保藏研究。Email:zhruan@scut.edu.cn
李汴生,彭紅梅,張德潤,阮征.基于感官品質(zhì)的油梨常溫后熟進程預(yù)測模型[J]. 農(nóng)業(yè)工程學報,2019,35(13):285-290. doi:10.11975/j.issn.1002-6819.2019.13.034 http://www.tcsae.org
Li Biansheng, Peng Hongmei, Zhang Derun, Ruan Zheng. Prediction model of avocado ripening process based on sensory quality at room temperature [J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(13): 285-290. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2019.13.034 http://www.tcsae.org