Remotely sensed real-time quantification of biophysical and biochemical traits of Citrus (Citrus sinensis L.) fruit orchards – A review

Ali, Anwar; Imran, Muhammad

doi:10.1016/j.scienta.2021.110024

Cited by 22 publications

(11 citation statements)

References 141 publications

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“…The application of hyperspectral reflectance in predicting the wheat grain yield was studied by Fei et al (2021) , who reported the effectiveness of red and NIR regions in predicting the grain yield in different irrigation regimes. The use of hyperspectral reflectance in predicting yield was not limited to agronomy crops and used for vegetables ( Awika et al, 2021 ), trees ( Ali and Imran, 2021 ), and industrial plants ( Holmes et al, 2020 ). Therefore, breeders can use spectral data to establish phenome-to-genome relationships by performing HypWAS and applying it via phenomics selection.…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

Yoosefzadeh-Najafabadi

Torabi

Tulpan

et al. 2021

Front. Plant Sci.

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In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.

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Section: Discussionmentioning

confidence: 99%

Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

Yoosefzadeh-Najafabadi

Torabi

Tulpan

et al. 2021

Front. Plant Sci.

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“…This has been possible due to their advantages as compared to terrestrial or other sensing platforms, such as their high flexibility to fly at low altitudes to collect detailed crop information, ease of operation, availability of highresolution images, acquisition of data on demand, and, foremost because their cost has been significantly reduced [194]. In this sense, the use of UAVs has rapidly expanded for the determination of multiple agronomic traits, such as LAI using RGB and multi-spectral imagery [195], physiological indicators based on hyperspectral images [196], and chlorophyll fluorescence [197], plant disease detection [198], 3D reconstructing for phenotyping purposes [199], and others. Additionally, in Latin America, a microgravity machine for space agriculture is under development with bioautomation fundamentals [200][201][202], and a bioreactor was built to establish conditions of carbon dioxide concentration levels, atmospheric pressure, temperature, Martian cycles of day and night, hyperaridity, and UV radiation (Figure 17b).…”

Section: -4-smart Agriculturementioning

confidence: 99%

Industrial, Collaborative and Mobile Robotics in Latin America: Review of Mechatronic Technologies for Advanced Automation

Cornejo,

Barrera,

Herrera Ruiz

et al. 2023

Emerg Sci J

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Mechatronics and Robotics (MaR) have recently gained importance in product development and manufacturing settings and applications. Therefore, the Center for Space Emerging Technologies (C-SET) has managed an international multi-disciplinary study to present, historically, the first Latin American general review of industrial, collaborative, and mobile robotics, with the support of North American and European researchers and institutions. The methodology is developed by considering literature extracted from Scopus, Web of Science, and Aerospace Research Central and adding reports written by companies and government organizations. This describes the state-of-the-art of MaR until the year 2023 in the 3 Sub-Regions: North America, Central America, and South America, having achieved important results related to the academy, industry, government, and entrepreneurship; thus, the statistics shown in this manuscript are unique. Also, this article explores the potential for further work and advantages described by robotic companies such as ABB, KUKA, and Mecademic and the use of the Robot Operating System (ROS) in order to promote research, development, and innovation. In addition, the integration with industry 4.0 and digital manufacturing, architecture and construction, aerospace, smart agriculture, artificial intelligence, and computational social science (human-robot interaction) is analyzed to show the promising features of these growing tech areas, considering the improvements to increase production, manufacturing, and education in the Region. Finally, regarding the information presented, Latin America is considered an important location for investments to increase production and product development, taking into account the further proposal for the creation of the LATAM Consortium for Advanced Robotics and Mechatronics, which could support and work on roboethics and education/R+D+I law and regulations in the Region. Doi: 10.28991/ESJ-2023-07-04-025 Full Text: PDF

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“…The traditional method of apple crop load assessment by manual counting with subsequent interpolation is laborious, imprecise, and hardly feasible in large orchards. Currently, new approaches are being developed and implemented in framework of precision agriculture [124,125]. Those include automated crop load assessment techniques based on computer vision and machine learning (see, e.g., Figure 4), which are becoming [126][127][128] widespread and commercially available to fruit growers.…”

Section: Approaches To Automated Precision Adjustment Of K Application Ratementioning

confidence: 99%

Essential Role of Potassium in Apple and Its Implications for Management of Orchard Fertilization

Кузин

Solovchenko

2021

Plants

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K (K) is of paramount importance for apple (Malus × domestica Borkh.), not only for tree growth and development but also for the size and quality of fruit yield. The apple plant’s demand for K varies, along with the progression of phenological phases, during the growing season. The K demand peaks during ripening of fruits featuring relatively high concentration of K comparable to that of the leaves. The mainstream method of apple tree K fertilization is through application of the fertilizer to the soils to improve K uptake by the roots. The bioavailability of K depends on assorted various factors, including pH, interaction with other nutrients in soil solution, temperature, and humidity. An important role in making the K from soil available for uptake by plants is played by plant growth-promoting microorganisms (PGPM), and the specific role of the PGPM is discussed. Advantages of fertigation (the combination of irrigation and fertilization) as an approach include allowing to balance application rate of K fertilizer against its variable demand by plants during the growing season. Excess K in the soil leads to competitive inhibition of calcium uptake by plants. The K-dependent deficiency of Ca leads to its predominant channeling to the leaves and hence to its decline in fruits. Consequently, the apple fruits affected by the K/Ca imbalance frequently develop physiological disorders in storage. This emphasizes the importance of the balanced K application, especially during the last months of the growing season, depending on the crop load and the actual K demand. The potential use of modern approaches to automated crop load estimation through machine vision for adjustment of K fertilization is underlined.

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Remotely sensed real-time quantification of biophysical and biochemical traits of Citrus (Citrus sinensis L.) fruit orchards – A review

Cited by 22 publications

References 141 publications

Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

Industrial, Collaborative and Mobile Robotics in Latin America: Review of Mechatronic Technologies for Advanced Automation

Essential Role of Potassium in Apple and Its Implications for Management of Orchard Fertilization

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