Maturity determination at harvest and spatial assessment of moisture content in okra using Vis-NIR hyperspectral imaging

Xuan, Guantao; Gao, Chong; Shao, Yuanyuan; Wang, Xiaoyun; Wang, Yongxian; Wang, Kaili

doi:10.1016/j.postharvbio.2021.111597

Cited by 39 publications

(17 citation statements)

References 32 publications

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“…The moisture content in okra pods were also reported to vary greatly depending on variety, stages of maturity and geographical origin [ 34 , 72 ]. In the present study, okra pod was assumed to exhibit 80% moisture content [ 73 ]. Furthermore, the World Health Organization (WHO) recommends a daily intake of fruits and vegetables, roughly equal to 400–600 g, which may prevent diet-related non-communicable diseases [ 74 ].…”

Section: Methodsmentioning

confidence: 99%

Okra (Abelmoschus esculentus) in a refugee context in East Africa: Kitchen gardening helps with mineral provision

et al. 2021

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Kitchen gardening is considered a way to reconnect with agriculture and complement the cereal-based relief food offered to refugees in East Africa. This work aimed at profiling mineral content of okra in four refugee camps and settlements located in Ethiopia and Uganda and its contribution to adequate intake (AIs) or recommended dietary allowances (RDAs) for young children and pregnant and lactating women (PLW). The study also evaluated the applicability of portable X-ray fluorescence (PXRF) as compared with inductively coupled plasma mass spectrometry (ICP-MS) for mineral profiling of okra powder samples. The contents of minerals (mg kg−1) from the ICP-MS readings were in the following ranges: K (14,385–33,294), Ca (2610–14,090), P (3178–13,248), Mg (3896–7986), Cu (3.81–19.3), Fe (75.7–1243), Zn (33–141) and Mn (23.1–261). Regardless of geographic origin, at low-end consumption probability (17 g day−1 for young children and 68 g day−1 for PLW), okra could contribute ˂ 15% (2.7–12.9%) AI for macro-minerals (K and Ca). In addition, the contributions to RDA values for Fe and Zn, elements of known public health interest, ranged from 4.5 to 34.7% for young children. Interestingly, regression lines revealed strong agreement between ICP-MS and PXRF readings for Mn and Zn, with R2 values > 0.91. This information is useful in support of nutrition-sensitive kitchen gardening programs through scaling culturally important crops in refugee settings.

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Section: Methodsmentioning

confidence: 99%

Okra (Abelmoschus esculentus) in a refugee context in East Africa: Kitchen gardening helps with mineral provision

et al. 2021

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“…With the development of intelligent equipment and Internet of Things technology [12,13], machine vision and image-processing technologies have received extensive attention, especially for crop disease detection [14,15], spraying machines [16], and weed robots [17]. Advanced image-processing methods can greatly reduce costs and improve productivity [18]. From the perspective of agricultural product harvesting, the quantity and quality parameters can be considered as important indicators of agricultural products.…”

Section: Introductionmentioning

confidence: 99%

Uniformity Detection for Straws Based on Overlapping Region Analysis

Feng

Xie

et al. 2022

Agriculture

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Nowadays, the advanced comprehensive utilization and the complete prohibition of burning fully covered straws in croplands have become increasingly important in agriculture engineering. As a kind of direct straw-mulching method in China, conservation tillage with straw smashing is an effective method to reduce pollution and enhance fertility. In view of the high straw-returning yields, complicated manual operation, and the poor performance of straw detection with machine vision, this study introduces a novel form of uniformity detection for straws based on overlapping region analysis. An image-processing technology using a novel overlapping region analysis was proposed to overcome the inefficiency and low precision resulting from the manual identification of the straw uniformity. In this study, the debris in the gray map was removed according to region characteristics. Through using morphological theory with overlapping region analysis in low-density cases, straws of appropriate length can be identified and then uniformity detection can be accomplished. Compared with traditional threshold segmentation methods, the advantages of an accurate identification, fast operation, and high efficiency contribute to the better performance of the innovative overlapping region analysis. Finally, the proposed algorithm was verified through detecting the uniformity in low-density cases, with an average accuracy rate of 97.69%, providing a novel image recognition solution for automatic straw-mulching systems.

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“…Through the selection of characteristic wavelengths of hyperspectral images, simultaneous external and internal fruit quality testing can be realized; this is a major development trend in the field of fruit detection ( 10 ). Hyperspectral image technology can be used to detect meat quality ( 11 ), orange spores, cucumber frostbite ( 12 ), guava maturity ( 13 ), strawberry ripeness ( 14 ), Moisture of Okra ( 15 ), and many other food defects ( 16 – 18 ). However, hyperspectral images contain large amounts of wavelength information, thus requiring a long time to collect information; accordingly, its online detection applications are limited.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral dimension reduction and navel orange surface disease defect classification using independent component analysis-genetic algorithm

He²,

Liu³

et al. 2022

Front. Nutr.

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Canker is a common disease of navel oranges that is visible before harvest, and penicilliosis is a common disease occurring after harvest and storage. In this research, the typical fruit surface, canker spots, penicillium spore, and hypha of navel oranges were, respectively, identified by hyperspectral imaging. First, the light intensity on the edge of samples in hyperspectral images was improved by spherical correction. Then, independent component images and weight coefficients were obtained using independent component analysis. This approach, combined with use of a genetic algorithm, was used to select six characteristic wavelengths. The method achieved dimension reduction of hyperspectral data, and the testing time was reduced from 46.21 to 1.26 s for a self-developed online detection system. Finally, a deep learning neural network model was established, and the four kinds of surface pixels were identified accurately.

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Maturity determination at harvest and spatial assessment of moisture content in okra using Vis-NIR hyperspectral imaging

Cited by 39 publications

References 32 publications

Okra (Abelmoschus esculentus) in a refugee context in East Africa: Kitchen gardening helps with mineral provision

Okra (Abelmoschus esculentus) in a refugee context in East Africa: Kitchen gardening helps with mineral provision

Uniformity Detection for Straws Based on Overlapping Region Analysis

Hyperspectral dimension reduction and navel orange surface disease defect classification using independent component analysis-genetic algorithm

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