CN108982883A - A kind of prediction Fresh-cut Lettuce shelf life model - Google Patents

A kind of prediction Fresh-cut Lettuce shelf life model Download PDF

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CN108982883A
CN108982883A CN201810778913.4A CN201810778913A CN108982883A CN 108982883 A CN108982883 A CN 108982883A CN 201810778913 A CN201810778913 A CN 201810778913A CN 108982883 A CN108982883 A CN 108982883A
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shelf life
fresh
vitamin
chlorophyll
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谢晶
郁杰
王金锋
杨冲
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Shanghai Maritime University
Shanghai Ocean University
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Abstract

The present invention provides a kind of prediction Fresh-cut Lettuce shelf life models to be utilized by studying the variation that the vitamin C of Fresh-cut Lettuce and chlorophyll content occur with the extension of storage time at different temperaturesArrheniusEquation respectively models vitamin C and chlorophyll, and obtaining shelf life forecasting model is chlorophyll content shelf life forecasting model: SLchlo=ln(C/C0)/(- 1.16 × 1014×e(- 83100/8.314T))；Vitamin C content shelf life forecasting model: SLVc=ln(V/V0)/(- 2.39 × 1015×e(- 90300/8.314T))；With the shelf life measured value at a temperature of 283K, separately verify the accuracy of the prediction model, by comparing the predicted value and relative error of two kinds of shelf life models, show that characterized by vitamin C, index models, can the shelf life preferably to Fresh-cut Lettuce in 0 ~ 20 DEG C of temperature range carry out real-time monitoring.

Description

A kind of prediction Fresh-cut Lettuce shelf life model
Technical field
The present invention relates to a kind of prediction fresh cut vegetables shelf life model, especially a kind of mould for predicting Fresh-cut Lettuce shelf life Type.
Background technique
Romaine lettuce is also known as Leaf lettuce, is a kind of green vegetable full of nutrition, due to being rich in vitamin, carbon aquation in romaine lettuce The nutriments such as object and minerals are closed, it is edible frequently as green salad.However, the catagen speed of fresh cut product is than unprocessed original Material is faster, and the mainly damage due to caused by minimum process method (peeling, slice, stripping and slicing, chopping etc.) is such as organized soft Change, cutting surfaces brown stain, reduces nutritive value, there are peculiar smell and microbial spoilage, would generally shorten fresh-cut in storage The shelf life of fruits and vegetables.In recent years, the demand of fresh cut product increases rapidly, but the limitation of shelf life is still fresh-cut fruit and vegetable industry The biggest obstacle further developed.Therefore, herein by quality comparison in the circulation of shelf life model prediction fresh cut vegetables, to its goods The frame phase carries out real-time monitoring, has certain practical value.
Vitamin C and chlorophyll are very important two nutritive indexes of vegetables, with storage time in storage Extension, nutritional ingredient can change a lot, and can determine its shelf life according to the content of its index of quality.At present with temperature Prediction model based on degree is that Food Shelf-life predicts a kind of most common method, wherein common method isArrhenius Equation, the equation can reflect the relationship between rate constant and temperature, can be used to describe quality decay kinetics.It closes the country It is a lot of in the quality comparison research of Fresh-cut Lettuce at different conditions, but to Fresh-cut Lettuce in logistics progress with vitamin C and The report of shelf life forecasting model that chlorophyll etc. is characterized index and establishes is seldom, lacks and a kind of more accurately predicts shelf The method of phase.Herein by the research of vitamin C and the chlorophyll changing rule under different reserve temperatures to Fresh-cut Lettuce, benefit WithArrheniusEquation respectively models vitamin C and chlorophyll, by comparing the predicted value and opposite mistake of two models Difference, to obtain a kind of more accurate Fresh-cut Lettuce shelf life model.
Summary of the invention
The object of the present invention is to provide a kind of methods for predicting Fresh-cut Lettuce shelf life, and vitamin C and chlorophyll are vegetables Most important two nutritive indexes, present invention index characterized by vitamin C and chlorophyll pass throughArrheniusEstablishing equation Shelf life model, by comparing the predicted value and relative error of two models, so that it is pre- to find a kind of more accurate shelf life Model, preferably the quality comparison situation of detection Fresh-cut Lettuce in the circulation process are surveyed, is more effectively assessed in the process of circulation Nutrition change situation and shelf life terminal.
The present invention is realized by following technical step:
(1) select size is uniform, color is vivid, it is tender and crisp, without rot insect pest romaine lettuce, the romaine lettuce of select is disinfected in alcohol The segment that whole romaine lettuce is cut into 3 ~ 5cm is pulled out and is drained after impregnating 5 min in tap water by kitchen knife, is dried in ventilating and cooling place 1 h；
(2) Fresh-cut Lettuce is contained in plastic pallet and is wrapped up with preservative film, every 80 g of box or so, be respectively put into 273,278, 288, storage in 293 K insulating boxs, test initial stage is primary every 3 d, 3 d, 1.5 d, 1 d, 0.5 d test respectively, latter stage then according to Frequency is adjusted according to quality comparison situation.Each index carries out 2 ~ 3 parallel laboratory tests, can be used with ensuring that experimental data is stablized, most Average value and standard deviation are calculated afterwards.
(3) vitamin C and chlorophyll are established with the kinetic model of storage temperature fluctuation.Zero level and level-one are used respectively It learns reaction Kinetics Model and regression analysis is carried out to the vitamin C and chlorophyll of different reserve temperatures, determine first order kinetics more It is suitble to the changing rule of the reflection index of quality such as Fresh-cut Lettuce vitamin and chlorophyll, and the decision system of first _ order kinetics equation Number R2It is all larger than 0.95, fitting precision with higher.
(4) chlorophyll and vitamin according to Fresh-cut Lettuce at 273 K, 278 K, 288 K, 293 K in storage The changing rule of C, using 1/T as abscissa, with lnkFor ordinate, linear regression is carried out, due to chlorophyll and vitamin C level-one Kinetic model ratekIt is negative, therefore this test is with ln(-k) be fitted for ordinate, to acquire pre-exponential factor A0, activation energyaEqual shelf life forecasting models parameter.
(5) shelf life forecasting model of vitamin C and chlorophyll is thus obtained are as follows:
Vitamin C content shelf life forecasting model: SLchlo=ln(C/C0)/(- 1.16 × 1014×e(- 83100/8.314T))；
Chlorophyll content shelf life forecasting model:SL chlo= ln(V/V0)/(- 2.39 × 1015×e(- 90300/8.314T))；
In formulaSL chlo、SL vcChlorophyll and ascorbic shelf life respectively,C 0、V 0、C、VRespectively chlorophyll and ascorbic Measured value when initial content and storage t d.
(6) shelf life forecasting model of foundation is verified and is evaluated: choosing sample 10 DEG C (283 K) under the conditions of Shelf life measured value verifies the accuracy of the prediction model.State when using vitamin C and chlorophyll loss 20% is raw as fresh-cut Dish shelf life terminal verifies model SL by comparing measured value and predicted valuechloAnd SLvcAccuracy, as a result such as 3 institute of table Show.Shelf life model SL as shown in Table 3vcAnd SLchloRelative error be respectively 4.44% and 8.89%, can be within 10% Received.With shelf life forecasting model SLchloIt compares, shelf life model SLvcRelative error it is smaller, predicted value is more acurrate, says Shelf life model of the shelf life model of the bright Index Establishment characterized by vitamin C better than the Index Establishment characterized by chlorophyll.
The specific implementation steps of the present invention are as follows:
(1) uniform, bright in colour, tender and crisp, without insect pest of rotting the romaine lettuce of size is selected；
(2) Fresh-cut Lettuce after processing, is packaged to be placed in insulating box with preservative film and be stored immediately, irregularly to vitamin C and Chlorophyll
It is measured；
(3) vitamin C and chlorophyll are established with the kinetic model of storage temperature fluctuation；
(4) parameter of zero level and level-one Chemical Kinetics is established, selection is more suitable for showing each index quality comparison rule of romaine lettuce Rule；
(5) with 8.6 software of Origin carry out linear and nonlinear fitting, obtain the rate constants k of TBA value under different temperatures, Coefficient of determination R2With ∑ R2It is compared, finally finds out the rate constant A of TBA value0Activation energya；
(6) the Index Establishment shelf life forecasting model characterized by vitamin C and chlorophyll；
Chlorophyll content shelf life forecasting model: SLchlo=ln(C/C0)/(- 1.16 × 1014×e(- 83100/8.314T))；
Vitamin C content shelf life forecasting model: SLVc=ln(V/V0)/(- 2.39 × 1015×e(- 90300/8.314T))；
In formulaSL chlo、SL vcChlorophyll and ascorbic shelf life respectively,C 0、V 0、C、VRespectively chlorophyll and ascorbic Measured value when initial content and storage t d；
(7) shelf life model is predicted and verified to the vitamin C of Fresh-cut Lettuce and chlorophyll situation of change at a temperature of 283K Accuracy.
Shelf life model of the invention can more accurately the shelf life to Fresh-cut Lettuce in 0 ~ 20 DEG C of temperature range carry out Real-time monitoring.The preferably quality comparison situation of detection Fresh-cut Lettuce in the circulation process, is more effectively assessed in the process of circulation Nutrition change situation and shelf life terminal.
Specific embodiment
Select size is uniform, color is vivid, it is tender and crisp, without rot insect pest romaine lettuce, the romaine lettuce of select is disinfected in alcohol Kitchen knife the segment that whole romaine lettuce is cut into 3 ~ 5cm is pulled out and is drained after impregnating 5 min in tap water, dry in the air in ventilating and cooling place Shine 1 h.
Fresh-cut Lettuce is contained in plastic pallet and is wrapped up with preservative film, every 80 g of box or so, be respectively put into 273, 278, storage in 288,293 K insulating boxs, test initial stage is primary every 3 d, 3 d, 1.5 d, 1 d, 0.5 d test respectively, latter stage Then frequency is adjusted according to quality comparison situation.Each index carries out 2 ~ 3 parallel laboratory tests, to ensure that experimental data stabilization can With finally calculating average value and standard deviation.
Vitamin C and chlorophyll are established with the kinetic model of storage temperature fluctuation.Respectively with zero level and level-one chemistry Reaction Kinetics Model carries out regression analysis to the vitamin C and chlorophyll of different reserve temperatures, determines that first order kinetics are more suitable Close the changing rule of the reflection index of quality such as Fresh-cut Lettuce vitamin and chlorophyll, and the coefficient of determination of first _ order kinetics equation R2It is all larger than 0.95, fitting precision with higher.Relevant parameter is shown in Table 1.
1 zero level of table and first order kinetics reaction rate constantkAnd the coefficient of determinationR 2
(4) chlorophyll according to Fresh-cut Lettuce at 273 K, 278 K, 288 K, 293 K in storage and ascorbic Changing rule, using 1/T as abscissa, with lnkFor ordinate, linear regression is carried out, due to chlorophyll and vitamin C first order kinetics Learn model speedkIt is negative, therefore this test is with ln(-k) be fitted for ordinate, to acquire pre-exponential factor A0, it is living Changing can EaEqual shelf life forecasting models parameter, as shown in table 2.
2 index of quality shelf life forecasting model parameter of table
(5) shelf life forecasting model of vitamin C and chlorophyll is thus obtained are as follows:
Vitamin C content shelf life forecasting model:
SLVc=ln(V/V0)/(- 2.39 × 1015×e(- 90300/8.314T))；
Chlorophyll content shelf life forecasting model:
SLchlo=ln(C/C0)/(- 1.16 × 1014×e(- 83100/8.314T))；
In formulaSL chlo、SL vcChlorophyll and ascorbic shelf life respectively,C 0、V 0、C、VRespectively chlorophyll and ascorbic Measured value when initial content and storage t d.
(6) shelf life forecasting model of foundation is verified and is evaluated: choosing sample 10 DEG C (283 K) under the conditions of Shelf life measured value verifies the accuracy of the prediction model.State when using vitamin C and chlorophyll loss 20% is raw as fresh-cut Dish shelf life terminal verifies model SL by comparing measured value and predicted valuechloAnd SLvcAccuracy, as a result such as 3 institute of table Show.Shelf life model SL as shown in Table 3vcAnd SLchloRelative error be respectively 4.44% and 8.89%, can be within 10% Received.With shelf life forecasting model SLchloIt compares, shelf life model SLvcRelative error it is smaller, predicted value is more acurrate, says Shelf life model of the shelf life model of the bright Index Establishment characterized by vitamin C better than the Index Establishment characterized by chlorophyll.
The measured value and predicted value of Fresh-cut Lettuce under 3 283 K of table
Therefore the shelf life model that Index Establishment rises characterized by vitamin can be more accurately to fresh in 0 ~ 20 DEG C of temperature range The shelf life for cutting romaine lettuce carries out real-time monitoring.

Claims (5)

1. a kind of prediction Fresh-cut Lettuce shelf life model, it is characterised in that: store Fresh-cut Lettuce respectively at different temperatures, survey Vitamin C and chlorophyll have been determined with the changing rule of storage time, establish shelf life forecasting model；Specific step is as follows:
(1) uniform, bright in colour, tender and crisp, without insect pest of rotting the romaine lettuce of size is selected；
(2) Fresh-cut Lettuce after processing, is packaged to be placed in insulating box with preservative film and be stored immediately, irregularly to vitamin C and Chlorophyll
It is measured；
(3) vitamin C and chlorophyll are established with the kinetic model of storage temperature fluctuation；
(4) parameter of zero level and level-one Chemical Kinetics is established, selection is more suitable for showing each index quality comparison rule of romaine lettuce Rule；
(5) with 8.6 software of Origin carry out linear and nonlinear fitting, obtain the rate constants k of TBA value under different temperatures, Coefficient of determination R2With ∑ R2It is compared, finally finds out the rate constant A of TBA value0Activation energya；
(6) the Index Establishment shelf life forecasting model characterized by vitamin C and chlorophyll；
Chlorophyll content shelf life forecasting model:
SLchlo=ln(C/C0)/(- 1.16 × 1014×e(- 83100/8.314T))；
Vitamin C content shelf life forecasting model:
SLVc=ln(V/V0)/(- 2.39 × 1015×e(- 90300/8.314T))；
In formulaSL chlo、SL vcChlorophyll and ascorbic shelf life respectively,C 0、V 0、C、VRespectively chlorophyll and ascorbic Measured value when initial content and storage t d；
(7) shelf life model is predicted and verified to the vitamin C of Fresh-cut Lettuce and chlorophyll situation of change at a temperature of 283K Accuracy.
2. a kind of prediction Fresh-cut Lettuce shelf life model as described in claim 1, it is characterised in that: romaine lettuce is impregnated through tap water It is dried into 1 h in ventilating and cooling place after processing, avoid its because temperature is excessively high, caused by overlong time Fresh-cut Lettuce lose it is original Nutritive value.
3. a kind of prediction Fresh-cut Lettuce shelf life model as described in claim 1, it is characterised in that: Fresh-cut Lettuce in 273, 278,283,285K, the interior storage of 293 K insulating boxs, test initial stage is primary every 3 d, 3 d, 1.5 d, 1 d, 0.5 d test respectively, Latter stage then adjusts frequency according to quality comparison situation；Each index carries out 2 ~ 3 parallel laboratory tests, to ensure that experimental data is stablized It can use, finally calculate average value and standard deviation.
4. a kind of prediction Fresh-cut Lettuce shelf life model as described in claim 1, it is characterised in that: pass through corresponding quality energy Grade Functional Analysis determines that first order kinetics are more suitable for reflecting the changing rule of Fresh-cut Lettuce vitamin C and chlorophyll, and level-one is dynamic The coefficient of determination R2 of mechanical equation is all larger than 0.95.
5. the shelf life forecasting model of Fresh-cut Lettuce as described in claim 1, it is characterised in that: with chlorophyll and vitamin C State when losing 20% is Fresh-cut Lettuce shelf life terminal, by shelf life model at a temperature of 283KSL chloWithSL vcPredicted value It is compared with relative error, obtaining one kind, more accurately prediction Fresh-cut Lettuce shelf life model is Vitamin C content shelf life Prediction model:
SLVc=ln(V/V0)/(- 2.39 × 1015×e(- 90300/8.314T)),
In formulaSL vcAscorbic shelf life respectively,V 0、VMeasurement when respectively ascorbic initial content and storage t d Value.
CN201810778913.4A 2018-07-16 2018-07-16 A kind of prediction Fresh-cut Lettuce shelf life model Pending CN108982883A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110796316A (en) * 2019-11-08 2020-02-14 中国科学院华南植物园 Method for predicting shelf life and quality of fruits and vegetables
CN113204898A (en) * 2021-06-07 2021-08-03 四川省农业科学院农产品加工研究所 Method for predicting shelf life of fresh-cut potatoes based on shelf life model

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110796316A (en) * 2019-11-08 2020-02-14 中国科学院华南植物园 Method for predicting shelf life and quality of fruits and vegetables
CN113204898A (en) * 2021-06-07 2021-08-03 四川省农业科学院农产品加工研究所 Method for predicting shelf life of fresh-cut potatoes based on shelf life model

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