Research on Crop Water Status Monitoring and Diagnosis by Terahertz Imaging

Li, Bin; Wang, Rong; Ma, Jianjun; Xu, Weihao

doi:10.3389/fphy.2020.571628

Cited by 9 publications

(4 citation statements)

References 36 publications

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“…For example, Yu et al (2022) employed electron microscopy CT for non-destructive observation of coconut variations, aiming to explore growth and development. Li et al (2020) conducted terahertz imaging to observe changes in leaf water content in their research on crop water status monitoring and diagnosis. These studies demonstrate the feasibility of obtaining images of target objects through non-destructive means.…”

Section: Related Workmentioning

confidence: 99%

An improved Deeplab V3+ network based coconut CT image segmentation method

Liu,

Zhang,

Chen

et al. 2023

Front. Plant Sci.

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Due to the unique structure of coconuts, their cultivation heavily relies on manual experience, making it difficult to accurately and timely observe their internal characteristics. This limitation severely hinders the optimization of coconut breeding. To address this issue, we propose a new model based on the improved architecture of Deeplab V3+. We replace the original ASPP(Atrous Spatial Pyramid Pooling) structure with a dense atrous spatial pyramid pooling module and introduce CBAM(Convolutional Block Attention Module). This approach resolves the issue of information loss due to sparse sampling and effectively captures global features. Additionally, we embed a RRM(residual refinement module) after the output level of the decoder to optimize boundary information between organs. Multiple model comparisons and ablation experiments are conducted, demonstrating that the improved segmentation algorithm achieves higher accuracy when dealing with diverse coconut organ CT(Computed Tomography) images. Our work provides a new solution for accurately segmenting internal coconut organs, which facilitates scientific decision-making for coconut researchers at different stages of growth.

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Section: Related Workmentioning

confidence: 99%

An improved Deeplab V3+ network based coconut CT image segmentation method

Liu,

Zhang,

Chen

et al. 2023

Front. Plant Sci.

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“…Otherwise, parsley has a greater transmission due to a smaller amount of water contained in the leaf and, therefore, produces less absorption. Finally, in another paper, Zahid et al measured refractive index n for baby-leaf, basil, pea-shoot and spinach [27] . The results show how the real part of the refractive index decreases over the time.…”

Section: Monitoring Leaves Water Content: Case Studies Of Thz Technol...mentioning

confidence: 99%

Studies of leaf water content in smart agriculture using THz technologies: a review

Greco¹,

Leccese²,

Doria³

et al. 2022

J Smart Environ Green Comput

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In recent years, the concept of smart agriculture has entered our collective daily routine by radically modifying the methods by which crop monitoring was previously carried out. More precisely, the term smart farming focuses its attention on the use technologies already present on the market like, sensors (multispectral, hyperspectral, thermal and terahertz sensors), WNS (wireless sensor network) and drones capable to reduce the human work in the fields, optimizing at the same time the quantity and quality of the products limiting the use of resources, as water, fertilizers, pesticides and herbicides. Recently, one of the most important problem in the field of precision farming is the availability of water; unfortunately, this factor becomes more critical from year to year. To resolve this problem, the first step is to reduce consumption and rationalize the use of water by adjusting the water supply to the needs of the systems in order to increase its yield while saving money. In this respect, the development of non-destructive techniques operating in the THz spectral region has allowed to monitor in real time the water content present in leaves and plants. In fact, due to the strong water absorption and reflection in this spectral region, this feature can be exploited to detect the water content of leaves and plants helping us to intervene promptly in cases where the plant needs water, avoiding so does water stress, but above all trying to use our primary resource adequately by reducing waste. About this, Imaging and Time-Domain Spectroscopy (THz-TDS) techniques have been applied to monitor soil conditions, drought stress and presence of pathogens on the plants. In this review, we focus our attention on the latest research carried out on monitoring the water content present in leaves through THz technologies. Moreover, we pose particular attention in the description of our system set composed by a 97 GHz transmitter-receiver able to analyze the spatial distribution of the water inside a leaf.

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“…Recently, the terahertz (THz) spectrum has also been used in geological investigations [24,25]. THz radiation can penetrate nonpolar materials and exhibits strong absorption when it encounters proteins, polar organics, and others [26][27][28][29][30]. The deposition of organic matter is an important index used to investigate geological evolution.…”

Section: Introductionmentioning

confidence: 99%

Terahertz Dating of Sedimentary Rocks

et al. 2022

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The depositional products of sedimentary rocks provide vital references for investigating the paleoenvironment, paleogeography, and tectonic evolution history. However, the detection methods of geological evolution are still relatively complicated, and how to combine geological age and geological evolution is confusing. Based on the sensitivity of terahertz waves to organic matter, a THz dating method was introduced for characterizing the geological age of sedimentary rocks. In this study, the geological evolution of Liujiang Basin was analyzed by using terahertz time domain spectroscopy (THz-TDS). According to the close relation between organic matter content and sedimentary environment, it can be inferred that the geological deposition in this area is affected by Marine cover. In addition, the refractive index of Ordovician sedimentary rocks is significantly higher than that of other sedimentary rocks. Based on these results, it is inferred that the sedimentary environment of the Liujiang Basin gradually changed from continental deposition to deep-water marine deposition from the Neoproterozoic to the Ordovician, and the sea water gradually retreated due to the crustal movement, resulting in a transition from deep-water deposition to continental inshore ocean facies deposition. These findings are highly consistent with the geological history of the study area. Combined with principal component analysis (PCA) technology, the relative geological age of sedimentary rocks can be divided. Our study con-firmed the reliability of this THz dating technique, which provides an effective way to study the geological evolution history of sedimentary rocks.

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Research on Crop Water Status Monitoring and Diagnosis by Terahertz Imaging

Cited by 9 publications

References 36 publications

An improved Deeplab V3+ network based coconut CT image segmentation method

An improved Deeplab V3+ network based coconut CT image segmentation method

Studies of leaf water content in smart agriculture using THz technologies: a review

Terahertz Dating of Sedimentary Rocks

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