Physical and mechanical properties of spinach for whole-surface online imaging inspection

Tang, Xiuying; Mo, Chang Yeun; Chan, Diane E.; Peng, Yankun; Qin, J.; Yang, Chun‐Chieh; Kim, Moon S.; Chao, Kuanglin

doi:10.1117/12.884892

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…Twelve spinaches were taken randomly per day for nondestructive detection using machine vision and E‐nose and then used for artificial sensory evaluation. Prior to each experiment, the spinach plants were taken out of the refrigerator and allowed to rest at room temperature for 10 min (Tang, Mo, Chan, Peng, & Chao, ).…”

Section: Methodsmentioning

confidence: 99%

Rapid and nondestructive detection of freshness quality of postharvest spinaches based on machine vision and electronic nose

Huang

et al. 2019

Journal of Food Safety

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Artificial sensory evaluation and physicochemical analysis tend to be tedious and time consuming. Therefore, this study employs machine vision, electronic nose (E‐nose), and multisensory data fusion to rapidly and nondestructively detect spinach freshness during storage. Spinach freshness during refrigeration was classified into four grades by 10 trained panelists. Machine vision and E‐nose were then used to obtain the image and odor information of the samples, respectively. K‐nearest neighbor (KNN), support vector machine (SVM), and back‐propagation artificial neural network (BPNN) were applied to predict spinach freshness. Result from the BPNN model based on machine vision achieved the same result as the KNN model with a classification accuracy of 85.42%. The BPNN model based on E‐nose achieved a better result than the SVM model with classification accuracies of 81.25% and 75.00%, respectively. Furthermore, the BPNN model based on multisensory data fusion greatly improved the detection accuracy of spinach freshness with a classification accuracy of 93.75%. Multisensory data fusion approaches based on machine vision and E‐nose are capable of intelligently detecting the freshness of postharvest spinach during storage. The main advantage is to allow a rapid and nondestructive detection of spinach freshness without using any chemical pretreatments. Practical Applications Fresh spinach is an important source of minerals, vitamins, carotenes, and other nutrients. Timely and accurately knowing the grade of spinach freshness before decay is of great interest in ensuring edible quality and reducing economic losses. Traditional analytical methods of spinach freshness tend to be tedious and time consuming. Novel analytical techniques such as machine vision and electronic nose (E‐nose) showed good feasibility in detecting spinach freshness during refrigerated storage. The detection accuracy could be highly improved based on the multisensory data fusion of machine vision and E‐nose. The results of this study confirmed that machine vision and E‐nose could constitute a rapid and nondestructive method to detect spinach freshness during storage instead of tedious and time‐consuming methods. The method of combining machine vision and E‐nose could be applied in the fruit and vegetable industry in the future.

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Section: Methodsmentioning

confidence: 99%

Rapid and nondestructive detection of freshness quality of postharvest spinaches based on machine vision and electronic nose

Huang

et al. 2019

Journal of Food Safety

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“…in packaging bags). Most mechanical properties reported in the literatures were investigated based on individual sample by performing mechanical tests such as tensile test, compression test, penetration test, cutting, tearing, puncturing and shearing (Ávila et al, 2007;Desmet et al, 2004a;2004b;Golmohammadi, 2013;More et al, 2014;Nabil et al, 2012;Tang et al, 2011;Wang et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Effect of Compression on Mechanical Properties of Ready-to-Eat (Rte) Spinach Varieties

Ariffin

Gkatzionis

Bakalis

2020

MABJ

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Compression-induced injury is frequently encountered during handling, packaging, transporting, and storage. In this study, compression test was performed using a mechanical tester, Universal Testing Machine Z030 (Zwick/Roell, Germany). Spinach varieties (Teen, Organic, Salad, and Baby) were used to study the response of spinach varieties towards stress. For single loading/unloading compression, maximum work (MaxW) and area under the curve (AUC) required to compress Organic spinach were found to be the highest followed by Teen and Salad spinach. The MaxW and AUC were found to be decreasing after storage which showed that the total work generated to compress the leaves was reduced due to texture degradation of the product after storage. For multiple loading/unloading compression, as the number of compressions increased, the MaxW decreased. Similar trend was observed at day 6. Apart from that, the MaxW for all the three spinach types were found to be similar at the 5th compression. This shows that regardless of the spinach types, they reached maximum resistance towards stress after the 5th consecutive compression. Under 200 N compression, leaves with stem required higher energy to compress compared to leaves without stem. However, for leaves compressed under 50 N and 100 N, the difference was only noticed on the 1st compression. The MaxW was found to be similar for leaves with stem and without stem starting from the 2nd compression till the 5th compression. The irregular and larger cell size of Organic spinach as compared to round-shaped and smaller cell size of Teen and Salad spinach may contribute to the ability of the Organic spinach tissue to have higher resistance towards mechanical stress during compression.

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“…Single-axis tensile strength tests have been conducted to determine various strength parameters of e.g. cabbage leaves (Kohyama et al 2008), lettuce (Newman et al 2005), spinach (Watanabe et al 2017, Tang et al 2011, chives (Pinzón et al 2013), as well as rosemary stems (Arevalo et al 2013) and many other thin-layered plant materials (Gładyszewska 2007).…”

Section: Introductionmentioning

confidence: 99%

Impact of seed light stimulation on the mechanical strength and photosynthetic pigments content in the scorzonera leaves

Ciupak¹,

Dziwulska‐Hunek²,

Krawiec³

et al. 2019

Acta Agroph.

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The leaves of scorzonera are vulnerable to mechanical damage due to heavy rainfall or wind. The aim of the study was to determine the impact of pre-sowing exposure of scorzonera seeds to laser light on the mechanical strength of the leaves and the content of photosynthetic pigments. The research material consisted of scorzonera leaves obtained from seeds treated with He-Ne laser light at the wavelength of 632.8 nm, surface power density of 5 mW cm-2 , and exposure time of 1, 5, 10, and 30 minutes. Young's modulus measurements showed that the leaves of the plants grown from seeds subjected to laser light stimulation were characterized by better mechanical strength compared to the leaves of the control. The highest values of the Young's modulus were recorded for scorzonera plants grown from seeds subjected to laser light exposure for 10 minutes. Exposure to light for a period of 1, 5 and 30 minutes significantly affected the content of chlorophylls and carotenoids in the leaves relative to the control. The largest increase in the content of photosynthetic pigments was recorded for 1 minute. The improvement in the mechanical strength of scorzonera leaves may reduce their vulnerability to mechanical damage during vegetation.

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Physical and mechanical properties of spinach for whole-surface online imaging inspection

Cited by 6 publications

References 6 publications

Rapid and nondestructive detection of freshness quality of postharvest spinaches based on machine vision and electronic nose

Rapid and nondestructive detection of freshness quality of postharvest spinaches based on machine vision and electronic nose

Effect of Compression on Mechanical Properties of Ready-to-Eat (Rte) Spinach Varieties

Impact of seed light stimulation on the mechanical strength and photosynthetic pigments content in the scorzonera leaves

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