Multivariate analysis between meteorological factor and fruit quality of Fuji apple at different locations in China

Zhang, Qiang; Zhou, Botao; Li, Minji; Wei, Qinping; Han, Zhenhai

doi:10.1016/s2095-3119(17)61826-4

Cited by 54 publications

(35 citation statements)

References 15 publications

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“…The higher levels of Pb and Ni in NE samples might be related to the relatively higher industrial pollution in this region . The BHB samples were detected with relatively lower levels of B, Zn, and K. The BHB region is the main apple‐cultivating region, and produces about half of the total yield . We suggest that the relative lower level of minerals might be related to continuous planting and increased planting density in this region .…”

Section: Discussionmentioning

confidence: 80%

“…Due to differences in regional climates and agricultural practices, Chinese apples from various regions have different qualities, possess different internal characteristics, appeal to different customers, and command different commercial prices. For example, apples from Akesu in Xinjiang province, Jingning in Gansu province, and Luochuan in Shaanxi province have a sweeter taste and are more fragrant, because of the relatively longer duration of sunshine in these regions . Apples from Zhaotong in Yunnan province and Yanyuan in Sichuan province have a deeper red color fruit peel and a good taste, as the higher altitude results in more intense ultraviolet B (UV‐B) exposure .…”

Section: Introductionmentioning

confidence: 99%

“…For example, apples from Akesu in Xinjiang province, Jingning in Gansu province, and Luochuan in Shaanxi province have a sweeter taste and are more fragrant, because of the relatively longer duration of sunshine in these regions . Apples from Zhaotong in Yunnan province and Yanyuan in Sichuan province have a deeper red color fruit peel and a good taste, as the higher altitude results in more intense ultraviolet B (UV‐B) exposure . Yantai from Shandong province is the largest production region in China, and Yantai Fuji apples have a good reputation …”

Section: Introductionmentioning

confidence: 99%

“…2 Apples from Zhaotong in Yunnan province and Yanyuan in Sichuan province have a deeper red color fruit peel and a good taste, as the higher altitude results in more intense ultraviolet B (UV-B) exposure. 2,3 Yantai from Shandong province is the largest production region in China, and Yantai Fuji apples have a good reputation. 4 Apples from various regions often differ in fruit safety because of different government policies and farming practices.…”

Section: Introductionmentioning

confidence: 99%

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Geographical origin of Chinese apples based on multiple element analysis

et al. 2019

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BACKGROUND Apples from different regions of China show different qualities and internal characteristics, and appeal to different customers. However, these aspects have not been studied in depth. We characterized the profiles of 14 elements in 317 apple samples collected from five regions of China. Principal component analysis (PCA), linear discriminant analysis (LDA), and back‐propagation artificial neural networks analysis (BP‐ANN) were used to build models for apple authentication. RESULTS Fourteen elements were successfully identified in apple samples by performing graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma atomic emission spectroscopy (ICP‐AES) analyses. Comparative analysis showed significantly different element profiles in samples from different regions. The first five principal components obtained by PCA accounted for 71.8% of the total variance. The LDA obtained 70.0% classification rates. The BP‐ANN obtained 82.7% classification rates. CONCLUSION This study indicated the possibility that apples could be authenticated based on differences in their element profiles, and provided a basis for further geographical origin studies. © 2019 Society of Chemical Industry

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Section: Discussionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Geographical origin of Chinese apples based on multiple element analysis

et al. 2019

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“…Apples are popular among consumers due to their high nutritional value and their ability to improve and beautify skin. China has the largest area of apple orchards and the highest total apple yield in the world, with the "Fuji" apple being the major Chinese cultivar, accounting for more than 70% of the apple acreage in China (Qiang, Bei-Bei, Min-Ji, Qin-Ping, & Zhen-Hai, 2018). The "Qinguan" apple is another important cultivar in China's apple industry, with its large size, red color, superior storability, and unique flavor making it popular with consumers.…”

Section: Introductionmentioning

confidence: 99%

Nondestructive detection of apple crispness via optical fiber spectroscopy based on effective wavelengths

Zhu

2019

Food Science & Nutrition

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Crispness is regarded as a significant quality index for apples. Currently, destructive sensory evaluation is the accepted method used to detect apple crispness, making it essential to develop a method that can detect apple crispness in a nondestructive manner. In this study, spectroscopy was proposed as the nondestructive technique for detecting apples' crispness, ultimately obtaining a spectral reflectance curve between 450 nm and 1,000 nm. In order to simplify and improve modeling efficiency, successive projections algorithm (SPA) and x‐loading weights (x‐LW) methods were used to select the most effective wavelengths. Partial least squares (PLS) algorithm, radial basis neural networks (RBNN), and multilayer perceptron neural networks (MLPNN) methods were used to establish the models and to predict the crispness of “Fuji” and “Qinguan” apple varieties. Based on the full wavelength (FW), the prediction accuracy of the PLS model for “Fuji” and “Qinguan” apple varieties was 92.05% and 95.87%, respectively. The effective wavelengths selected via SPA for the “Fuji” apple variety were 450.41 nm, 476.80 nm, 677.75 nm, and 750.72 nm, and the effective wavelengths selected via x‐LW for the “Qinguan” apple variety were 542.51 nm, 544.79 nm, 676.96 nm, and 718.29 nm. The prediction accuracy of the PLS model based on effective wavelengths for “Fuji” and “Qinguan” apple varieties reached 91.31% and 96.41%, respectively. Compared with the RBNN model, the MLPNN model achieved better prediction results for both “Fuji” and “Qinguan” apples, with the prediction accuracy reaching 97.8% and 99.9%, respectively. Based on the above findings, effective wavelength selection and MLPNN modeling were able to detect apple crispness with the highest accuracy. Overall, it can be concluded that the less effective wavelengths are conducive to developing an instrument for crispness detection.

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Determination of geographical origin of concentrated apple juice through analysis of stable isotopic and mineral elemental fingerprints: preliminary results

Liu

Zhao

Mu³

et al. 2021

J Sci Food Agric

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BACKGROUND With increasing attention being paid to food authenticity, the geographic origin of food has become a topic of interest for both consumers and producers. As far as we know, there are relatively few studies on the origin traceability of concentrated apple juice. The most commonly used methods of origin tracing research is by using stable isotopes and mineral elements technology, because these indicators are directly related to local geographical environment. RESULTS In this study, a discriminant model was established by determining the content of the stable isotopes (δ13C, δ18O) and 13 mineral elements (B, Mn, Co, Ni, Cu, Sr, V, Ba, Fe, Mg, Na, Ca and Cr) in concentrated apple juice. Linear discriminant analysis (LDA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS‐DA) were employed for regional classification of samples. After data conversion and correlation analysis, spatial and quantitative prediction models were established using multiple linear regressions. Finally, the experimental results showed that the eight key variables(δ 13 C, δ 18 O, B, Ca, Mg, Cu, Sr and Na) selected by the analysis can be used to further characterize the production area. CONCLUSION The results showed that the carbon and oxygen isotopes combined with certain mineral elements can be used to indicate the origin of concentrated apple juice. © 2020 Society of Chemical Industry

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Multivariate analysis between meteorological factor and fruit quality of Fuji apple at different locations in China

Cited by 54 publications

References 15 publications

Geographical origin of Chinese apples based on multiple element analysis

Geographical origin of Chinese apples based on multiple element analysis

Nondestructive detection of apple crispness via optical fiber spectroscopy based on effective wavelengths

Determination of geographical origin of concentrated apple juice through analysis of stable isotopic and mineral elemental fingerprints: preliminary results

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