Agricultural Product Authenticity and Geographical Origin Traceability

Zhao, Tiejun; Nakano, Akimasa

doi:10.6090/jarq.52.115

Cited by 7 publications

(7 citation statements)

References 25 publications

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“…Previous studies have shown that the NIR plateau between 800 nm and 1300 nm, as well as water absorption bands above 1300 nm, are common characteristics of reflectance spectra of all healthy green plants. The high reflectivity in the NIR region of 800 nm to 1300 nm is due to the porous plant leaf structure (tissues and cells), whereas the low reflectivity above 1300 nm is caused by water absorption [3,39]. The 1300 nm wavelength is the dividing line of the histological structures and the specific components of plant leaves, both of which are the main factors affecting the reflectance spectral characteristics of the leaves.…”

Section: Characteristic Wavelength Bandsmentioning

confidence: 99%

“…In recent decades, with the advancements in spectroscopy and imaging technologies, hyperspectral imaging (HSI) technology has emerged as a highly efficient nondestructive measurement method. This technology was originally developed for remote sensing and is widely used in resource management, agriculture, mineral exploration, and environmental monitoring [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

“…The low reflectance above a wavelength of 1300 nm is due to the absorption of water. Furthermore, numerous studies have indicated that there are four water absorption bands for all angiosperm leaves, which occur at wavelengths of approximately 970, 1200, 1400, and 1920 nm [2,3,8,9]. These discoveries enable water status assessment using HSI.…”

Section: Introductionmentioning

confidence: 99%

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Application of Hyperspectral Imaging for Assessment of Tomato Leaf Water Status in Plant Factories

et al. 2020

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Irrigation management continues to be an important issue for tomato cultivation, especially in plant factories. Accurate and timely assessment of tomato leaf water status is a key factor in enabling appropriate irrigation, which can save nutrition solution and labor. In recent decades, hyperspectral imaging has been widely used as a nondestructive measurement method in agriculture to obtain plant biological information. The objective of this research was to establish an approach to obtain the tomato leaf water status—specifically, the relative water content (WC) and equivalent water thickness (MC)—for five different tomato cultivars in real time by using hyperspectral imaging. The normalized difference vegetation index (NDVI) and two-band vegetation index (TBI) analyses were performed on the tomato leaf raw relative reflection (RAW), the inversion-logarithm relative reflection (LOG), and the first derivative of relative reflection (DIFF) from wavelengths of 900 nm to 1700 nm. The best regression model for WC assessment was obtained by TBI regression using DIFF at wavelengths of 1410 nm and 1520 nm, and the best regression model for MC assessment was obtained by NDVI regression using RAW at wavelengths of 1300 nm and 1310 nm. Higher model performance was obtained with MC assessment than with WC assessment. The results will help improve our understanding of the relationship between hyperspectral reflectance and leaf water status.

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Section: Characteristic Wavelength Bandsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Hyperspectral Imaging for Assessment of Tomato Leaf Water Status in Plant Factories

et al. 2020

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“…A large number of studies have shown that the traceability system of agricultural products based on blockchain and IoT can improve the efficiency and reduce the logistics cost to a certain extent. "Blockchain + Internet of Things" realizes the risk-free, leverage-free and high-efficiency transfer of credit between things, and realizes the unification of capital flow, logistics and information flow on the chain [38]. The application of IoT ensures the trustworthiness of everything, realizes the mapping between the physical world and the digital world, and ensures the authenticity and integrity of the information on the chain, and further helps the traceability development of the smart supply chain.…”

Section: * Self-generated By the Authormentioning

confidence: 99%

Research Review of Agricultural Product Traceability System Based on Blockchain Technology

Zhou

2022

AJEBA

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With the frequent occurrence of domestic agricultural product safety accidents in China, consumers' trust in the quality and supply chain of agricultural products is gradually declining. Traceability, as a production control system that can connect all links of product circulation and manage undirected tracking of products, is of great significance to guarantee the quality and safety of products. In the traditional traceability system, there are problems of asymmetry, inaccuracy, non-transparency and insecurity of information. Blockchain can provide powerful technical support for the construction of agricultural products traceability system by virtue of decentralization, transparency and openness, non-tamperability and distributed storage. Applying blockchain technology to agricultural products traceability can effectively protect the rights and interests of all members of the agricultural products supply chain and the general consumers. Based on the analysis of the concept and main features of blockchain, this paper summarizes the research and application progress of blockchain-based traceability system at home and abroad in recent years by studying the traceability mechanism of agricultural products. The advantages and challenges of the implementation of blockchain-based agricultural products traceability system are elaborated. It is hoped that this paper can provide useful references for the research and establishment of blockchain agricultural products traceability system.

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“…All methods for food authenticity developed thus far have no more than one partial use for practical application as an analysis guideline. For both measuring the products and determining the production environment (e.g., soil conditions), a non-destructive system has been developed (Zhao & Nakano 2018). An environmental measurement node using open source hardware (UECS: Ubiquitous environmental control system) has also been developed (Yasuba et al 2013).…”

Section: Food Safety Combining Analytical Chemistry and Information Cmentioning

confidence: 99%

Authenticity of the Geographical Origin and Production Methods of Agricultural Products

Nakano

Zhao

2018

JARQ

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Multi-element analysis including stable isotopes can be used as a possible indicator for food safety and security. For the certification of geographical origin, the analytical methods can be performed in two ways: one where multivariate analysis is used to determine the concentrations of such omnipresent elements as Al, Ca, Cl, Mg, Mn, Fe and Zn, and one that focuses on such special elements as the stable isotope ratios of Sr, O, and H. For the certification of production methods, especially those regarding organic products, δ 15 N values could be a potential indicator, particularly in such protected cultivations as in a plant factory (advanced-type greenhouse horticulture). Because the accuracy of these values is affected by production conditions, the δ 15 N values of products can be predicted more accurately under controlled conditions, such as in a plant factory using δ 15 N-evaluated fertilizer, medium, and water. Non-destructive systems have been developed for measuring both the level of elements in a product and the production environment, such as soil conditions. In the near future, the results of chemically analyzed and those of non-destructively analyzed elemental composition will become interconnected to non-destructively certify the geographical origin and production method of agricultural products. All these destructive methods have been used to a limited extent for practical regulation as an analysis guideline; however, a combined system involving the use of the newly developed detector (nondestructive), data collection, and analysis using artificial intelligence could address the issue of falsely labeled products for practical application. Particularly in a plant factory, production is controlled and regulated, allowing the tracing of products from the farm to the table. In this context, the greenhouse production system would be an advanced example for the practical use of food safety combined with analytical chemistry and information communication technology.

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Agricultural Product Authenticity and Geographical Origin Traceability

Cited by 7 publications

References 25 publications

Application of Hyperspectral Imaging for Assessment of Tomato Leaf Water Status in Plant Factories

Application of Hyperspectral Imaging for Assessment of Tomato Leaf Water Status in Plant Factories

Research Review of Agricultural Product Traceability System Based on Blockchain Technology

Authenticity of the Geographical Origin and Production Methods of Agricultural Products

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