本文關(guān)鍵詞： 鮮食葡萄 物流質(zhì)量安全評(píng)估 微生物 定量二氧化硫 無損檢測　出處：《中國農(nóng)業(yè)大學(xué)》2016年博士論文　論文類型：學(xué)位論文

【摘要】：鮮食葡萄在我國居民水果消費(fèi)中占有重要地位,也是世界主要消費(fèi)水果之一,但鮮食葡萄屬于漿果類水果,不耐貯藏,其采收到最終消費(fèi)的過程中,通常要經(jīng)過多階段的物流過程,因此,研究鮮食葡萄物流質(zhì)量安全具有重要的現(xiàn)實(shí)意義。本文基于實(shí)地調(diào)研和相關(guān)文獻(xiàn)總結(jié),分析了鮮食葡萄物流過程特點(diǎn)和物流質(zhì)量安全形成機(jī)理,并針對(duì)其中關(guān)鍵要素展開了研究。基于品質(zhì)衰變量化分析,研究了鮮食葡萄物流質(zhì)量安全評(píng)估方法；研究了SO2濃度對(duì)鮮食葡萄品質(zhì)變化和物流質(zhì)量安全評(píng)估的影響；基于近紅外檢測和氣味識(shí)別,研究了基于無損檢測的鮮食葡萄物流質(zhì)量安全評(píng)估方法；在系統(tǒng)分析鮮食葡萄物流質(zhì)量安全信息化需求的基礎(chǔ)上設(shè)計(jì)了鮮食葡萄物流質(zhì)量安全管理平臺(tái)。主要研究結(jié)論如下：(1)本文研究中,表面霉菌生長是鮮食葡萄物流質(zhì)量安全關(guān)鍵限制性因素,構(gòu)建的霉菌生長動(dòng)力學(xué)模型決定系數(shù)達(dá)到0.9以上,模型可靠性評(píng)價(jià)中,準(zhǔn)確因子偏離值小于0.2,表明基于霉菌生長動(dòng)力學(xué)的方法對(duì)鮮食葡萄物流品質(zhì)變化預(yù)測與物流質(zhì)量安全評(píng)估具有適用性。研究還表明,鮮食葡萄物流品質(zhì)變化過程中的特定腐敗菌除灰霉菌外還可能為青霉菌,且其生長過程存在不穩(wěn)定性。(2)使用SO2控制表面霉菌生長條件下,質(zhì)構(gòu)變化和褐變成為鮮食葡萄物流質(zhì)量安全關(guān)鍵限制性因素,可分別基于一級(jí)反應(yīng)模型和零級(jí)反應(yīng)模型建模,模型決定系數(shù)均達(dá)到0.8以上,基于化學(xué)動(dòng)力學(xué)的方法適用于相應(yīng)條件下的物流質(zhì)量安全評(píng)估。研究還表明,冷鏈物流條件下,10ppm的穩(wěn)定SO2濃度可以有效控制鮮食葡萄表面微生物生長,而常溫條件下,需要維持20ppm的SO2濃度。(3)構(gòu)建的基于近紅外光譜的鮮食葡萄質(zhì)構(gòu)變化無損檢測模型決定系數(shù)達(dá)到0.93,交叉驗(yàn)證中,模型預(yù)測準(zhǔn)確度為0.81,表明近紅外檢測結(jié)合質(zhì)構(gòu)變化動(dòng)力學(xué)模型的方法可用于鮮食葡萄物流質(zhì)量安全評(píng)估。經(jīng)傳感器陣列優(yōu)化,基于4氣體傳感器陣列構(gòu)建的0℃條件下的鮮食葡萄品質(zhì)新鮮度貨架期當(dāng)量無損檢測模型,決定系數(shù)與驗(yàn)證準(zhǔn)確度均達(dá)到0.8以上,相應(yīng)方法可用于基于氣味識(shí)別的鮮食葡萄物流質(zhì)量安全評(píng)估,研究還表明,常溫條件下的建模需要考慮SO2濃度的影響。(4)基于鮮食葡萄物流安全信息化需求分析和相關(guān)技術(shù)應(yīng)用測試,互聯(lián)網(wǎng)技術(shù)、GPRS技術(shù)和SMS預(yù)警技術(shù)的集成可用于提高鮮食葡萄物流安全信息管理效率,保障鮮食葡萄物流質(zhì)量安全評(píng)估有效性。
[Abstract]:Fresh grape plays an important role in the consumption of fruit in our country and is also one of the main consumption fruits in the world. Usually, there are many stages of logistics process. Therefore, it is of great practical significance to study the quality and safety of fresh grape logistics. This paper is based on field research and related literature summary. The characteristics of fresh grape logistics process and the forming mechanism of logistics quality and safety were analyzed, and the key elements were studied. Based on the quantitative analysis of quality decay, the evaluation method of fresh grape logistics quality and safety was studied. The effect of SO2 concentration on quality change and logistics quality safety evaluation of fresh grape was studied. Based on near-infrared detection and odor recognition, the quality and safety evaluation method of fresh grape logistics based on non-destructive testing was studied. On the basis of systematic analysis of fresh grape logistics quality and safety information requirements, the quality and safety management platform of fresh grape logistics is designed. The main research conclusions are as follows: 1) in this paper. Surface mold growth is a key limiting factor for the quality safety of fresh grape logistics. The determinant coefficient of the established mold growth kinetic model is more than 0.9, and the reliability of the model is evaluated. The deviation value of the accurate factor is less than 0.2, which indicates that the method based on mold growth kinetics is applicable to the prediction of fresh grape logistics quality change and the evaluation of logistics quality safety. The specific spoilage bacteria in the process of changing the quality of fresh grape logistics may also be Penicillium, and its growth process is unstable. 2) SO2 is used to control the growth of surface fungi. The changes of texture and browning are the key limiting factors for the quality safety of fresh grape logistics, which can be modeled based on first-order reaction model and zero-order reaction model, respectively, and the determination coefficient of the model is more than 0.8. The method based on chemical kinetics is suitable for the evaluation of logistics quality and safety under the corresponding conditions. The study also shows that under the condition of cold chain logistics. Stable SO2 concentration of 10ppm can effectively control the growth of fresh grape surface microorganisms, but under normal temperature conditions. The determination coefficient of the nondestructive detection model for texture change of fresh grapevine based on near infrared spectroscopy was 0.93, which needed to be maintained at 20ppm SO2 concentration. The prediction accuracy of the model is 0.81. it shows that the method of near-infrared detection combined with the kinetic model of texture change can be used to evaluate the quality and safety of fresh grape logistics, which is optimized by sensor array. The non-destructive testing model of fresh grape quality shelf life equivalent at 0 鈩，

本文編號(hào)：1452567