Abstract
In order to explore and establish an non-destructive method for the detection of mouldy core in apples,the changes of seven impedance parameters with frequency and three physiochemical quality properties were measured on normal fruits and mouldy-core fruits of Fuji apple using LCR instrument under 100 Hz to 3.98 MHz,1.0 voltage and constant temperature of(20 ± 1) ℃.The results showed that with increasing frequency,complex impedance(Z) and parallel resistance(R p) of apples revealed a decrease whereas susceptance(B) and conductance(G) exhibited an increase.Significant linear relationship between lgf and lgZ or lgB was observed,respectively(R2 0.99);phase angle(θ),logarithm of parallel capacitance(lgC p) and logarithm of loss coefficient(lgD) revealed a fluctuating trend,with 1,2 and 3 turning points,respectively.Mouldy-core incidence did not change the trend of each impedance parameter-frequency curve in fruits,but the values of some parameters were altered,for example,Z decrease,B and C p increased.Totally 27 specific impedance parameters with non-zero loading coefficient for the construction of 14 effective principal components were screened through sparse principal component analysis(SPCA).When recognizing mouldy-core fruits using classifiers of support vector machine(SVM) and artificial neural network(ANN),SVM provided higher accuracy.In addition,in 10 crossvalidation classification tests,mouldy core fruits could be discriminated with an accuracy of 94%,confirming the validity of impedance parameters screened and the feasibility of SPCA-SVM analysis software for discriminating mouldy-core from normal fruits.Moreover,the incidence of mouldy-core fruits presented a decrease in density and soluble solid contents in comparison to normal fruits,which provided a physiochemical basis for changes in bio-impedance properties.
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Claims 11
Claim · model-written summary
Apple complex impedance and parallel resistance decreased with frequency.
- Taxon
- Apple
Malus domesticat0 - Outcome
- complex impedance(Z) and parallel resistance(R p)e0
- Direction
- decreasee0
- Qualifier
- increasing frequencye0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“with increasing frequency,complex impedance(Z) and parallel resistance(R p) of apples revealed a decrease whereas susceptance(B) and conductance(G) exhibited an increase.”
Claim · model-written summary
Apple susceptance and conductance increased with frequency.
- Taxon
- AppleMalus domesticat0
- Outcome
- susceptance(B) and conductance(G)e0
- Direction
- increasee0
- Qualifier
- increasing frequencye0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“with increasing frequency,complex impedance(Z) and parallel resistance(R p) of apples revealed a decrease whereas susceptance(B) and conductance(G) exhibited an increase.”
Claim · model-written summary
Log frequency had strong linear relationships with log impedance and log susceptance.
- Taxon
- AppleMalus domesticat0
- Outcome
- linear relationship between lgf and lgZ or lgBe0
- Value
- R2 0.99e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“Significant linear relationship between lgf and lgZ or lgB was observed,respectively(R2 0.99)”
Claim · model-written summary
Phase angle, log parallel capacitance and log loss coefficient fluctuated with one, two and three turning points, respectively.
- Taxon
- AppleMalus domesticat0
- Outcome
- phase angle(θ),logarithm of parallel capacitance(lgC p) and logarithm of loss coefficient(lgD)e0
- Direction
- fluctuating trende0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“phase angle(θ),logarithm of parallel capacitance(lgC p) and logarithm of loss coefficient(lgD) revealed a fluctuating trend,with 1,2 and 3 turning points,respectively.”
Claim · model-written summary
Mouldy core did not change impedance parameter frequency curve trends.
- Taxon
- AppleMalus domesticat0
- Outcome
- trend of each impedance parameter-frequency curvee0
- Direction
- did not changee0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“Mouldy-core incidence did not change the trend of each impedance parameter-frequency curve in fruits”
Claim · model-written summary
Mouldy core decreased fruit impedance.
- Taxon
- AppleMalus domesticat0
- Outcome
- Ze0
- Direction
- decreasee0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“Z decrease,B and C p increased”
Claim · model-written summary
Mouldy core increased susceptance and parallel capacitance.
- Taxon
- AppleMalus domesticat0
- Outcome
- B and C pe0
- Direction
- increasede0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“Z decrease,B and C p increased”
Claim · model-written summary
Sparse principal component analysis selected 27 impedance parameters for 14 effective components.
- Taxon
- AppleMalus domesticat0
- Outcome
- specific impedance parameterse0
- Value
- 27e0
- Qualifier
- 14 effective principal componentse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“Totally 27 specific impedance parameters with non-zero loading coefficient for the construction of 14 effective principal components were screened through sparse principal component analysis(SPCA).”
Claim · model-written summary
SVM classified mouldy core fruit more accurately than ANN.
- Taxon
- AppleMalus domesticat0
- Outcome
- accuracye0
- Direction
- highere0
- Comparator
- artificial neural network(ANN)e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“When recognizing mouldy-core fruits using classifiers of support vector machine(SVM) and artificial neural network(ANN),SVM provided higher accuracy.”
Claim · model-written summary
The impedance based SPCA-SVM classifier discriminated mouldy core fruit with 94% accuracy across ten tests.
- Taxon
- AppleMalus domesticat0
- Outcome
- accuracye0
- Value
- 94%e0
- Qualifier
- 10 crossvalidation classification testse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“in 10 crossvalidation classification tests,mouldy core fruits could be discriminated with an accuracy of 94%”
Claim · model-written summary
Mouldy core fruit had lower density and soluble solids than normal fruit.
- Taxon
- AppleMalus domesticat0
- Outcome
- density and soluble solid contentse0
- Direction
- decreasee0
- Comparator
- normal fruitse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Nondestructive Detection of Apple Mouldy Core Based on Bioimpedance Properties”
e0“the incidence of mouldy-core fruits presented a decrease in density and soluble solid contents in comparison to normal fruits”