Journal of Agriculture & Life Science, Год журнала: 2023, Номер 57(6), С. 25 - 38
Опубликована: Дек. 30, 2023
Язык: Английский
Agriculture, Год журнала: 2023, Номер 13(8), С. 1593 - 1593
Опубликована: Авг. 11, 2023
Precision agriculture employs cutting-edge technologies to increase agricultural productivity while reducing adverse impacts on the environment. is a farming approach that uses advanced technology and data analysis maximize crop yields, cut waste, productivity. It potential strategy for tackling some of major issues confronting contemporary agriculture, such as feeding growing world population environmental effects. This review article examines latest recent advances in precision including Internet Things (IoT) how make use big data. aims provide an overview innovations, challenges, future prospects smart farming. presents current state most innovations technology, drones, sensors, machine learning. The also discusses main challenges faced by management, adoption, cost-effectiveness.
Язык: Английский
Процитировано
285
Frontiers in Plant Science, Год журнала: 2024, Номер 14
Опубликована: Янв. 10, 2024
Hyperspectral imaging (HSI) and deep learning techniques have been widely applied to predict postharvest quality shelf life in multiple horticultural crops such as vegetables, mushrooms, fruits; however, few studies show the application of these evaluate issues cut flowers. Therefore, this study, we developed a non-contact rapid detection technique for emergence gray mold disease (GMD) potential longevity roses using based on HSI data.
Язык: Английский
Процитировано
9
Discover Agriculture, Год журнала: 2024, Номер 2(1)
Опубликована: Ноя. 7, 2024
Abstract Precision agriculture, a transformative farming approach, has gained prominence due to advancements in digital technologies. This paper explores the multifaceted landscape of precision focusing on its tangible benefits, challenges, and future directions. Purpose Amidst growing interest this aims provide comprehensive analysis various aspects. Specifically, it seeks elucidate benefits agriculture optimizing resource utilization, enhancing crop health, promoting sustainability. Moreover, examines challenges faced implementation proposes directions overcome these obstacles. Findings Through review existing literature case studies, presents nuanced understanding agriculture's impact farming, livestock production, economic outcomes, environmental It identifies key such as data security, costs, regulatory frameworks, while also highlighting innovative solutions promising field. Originality To best our knowledge, represents rigorous attempt comprehensively analyze with focus original contributions By synthesizing research offering insights into directions, adds emerging knowledge base surrounding potential revolutionize modern practices.
Язык: Английский
Процитировано
6
Scientific Reports, Год журнала: 2025, Номер 15(1)
Опубликована: Март 1, 2025
Abstract A simple Python algorithm was used to estimate the four major root traits: total length (TRL), surface area (SA), average diameter (AD), and volume (RV) of legumes (adzuki bean, mung cowpea, soybean) based on two-dimensional images. Four different thresholding methods; Otsu, Gaussian adaptive, mean adaptive triangle threshold were know effect in trait estimation optimize accuracy estimation. The results generated by applied 400 legume images compared with those two separate software (WinRHIZO RhizoVision), validated using ground truth data. Distance transform method for estimating SA, AD, RV ConnectedComponentsWithStat function TRL Among methods, Otsu worked well distance transform, while effective TRL. All traits showed a high correlation an R² ≥0.98 ( p < 0.001 ) square error (RMSE) bias (MBE) also minimal when comparing algorithm-derived values values, RMSE MBE both 10 TRL, 6 0.5 AD RV. This lower value metrics indicates smaller differences between software-derived values. Although observed software, closely aligned derived from WinRHIZO. We provided easy where can be analyzed without any incurring expenses, being open source; it modified expert their requirements.
Язык: Английский
Процитировано
0
Frontiers in Plant Science, Год журнала: 2025, Номер 16
Опубликована: Март 6, 2025
Vegetative indices (VIs) are widely used in high-throughput phenotyping (HTP) for the assessment of plant growth conditions; however, a range VIs among diverse soybeans is still an unexplored research area. For this reason, we investigated four major VIs: normalized difference vegetation index (NDVI), photochemical reflectance (PRI), anthocyanin (ARI), and change to carotenoid (CRI) soybean accessions. Furthermore, ensured correct positioning region interest (ROI) on leaf clarified effect choosing different ROI sizes. We also developed Python algorithm selection automatic calculation. According our results, each VI showed ranges (NDVI: 0.60-0.84, PRI: -0.03 0.05, ARI: -0.84 0.85, CRI: 2.78-9.78) two stages. The size pixels did not show any significant difference. In contrast, shaded part petiole had differences compared with non-shaded tip, side, center leaf, respectively. case algorithm, algorithm-derived high correlation ENVI software-derived value: NDVI -0.97, PRI -0.96, ARI -0.98, CRI -0.99. Moreover, average error was detected be less than 2.5% all these ENVI.
Язык: Английский
Процитировано
0
Plants, Год журнала: 2023, Номер 12(17), С. 3078 - 3078
Опубликована: Авг. 28, 2023
Soybean (Glycine max) is a crucial legume crop known for its nutritional value, as seeds provide large amounts of plant protein and oil. To ensure maximum productivity in soybean farming, it essential to carefully choose high-quality that possess desirable characteristics, such the appropriate size, shape, color, absence any damage. By studying relationship between seed shape other traits, we can effectively identify different genotypes improve breeding strategies develop high-yielding seeds. This study focused on analysis traits using Python algorithm. The length, width, projected area, aspect ratio were measured, total number was calculated. OpenCV library along with contour detection function used measure traits. obtained through algorithm compared values manually from two software applications (SmartGrain WinDIAS). algorithm-derived measurements area showed strong correlation various methods, R-square greater than 0.95 (p < 0.0001). Similarly, error metrics, including residual standard error, root mean square absolute all below 0.5% when comparing across measurement methods. For less 4% Furthermore, count present acquired images highly accurate, only few errors observed. preliminary investigated some morphological further research needed explore more attributes.
Язык: Английский
Процитировано
9
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
2
Sensors, Год журнала: 2024, Номер 24(14), С. 4635 - 4635
Опубликована: Июль 17, 2024
In the field of rice processing and cultivation, it is crucial to adopt efficient, rapid user-friendly techniques detect flavor values various varieties. The conventional methods for value assessment mainly rely on chemical analysis technical evaluation, which not only deplete resources but also incur significant time labor costs. this study, hyperspectral imaging technology was utilized in combination with an improved Particle Swarm Optimization Support Vector Machine (PSO-SVM) algorithm, i.e., Grid Iterative Search (GISPSO-SVM) introducing a new non-destructive technique determine rice. method captures feature data different varieties through image acquisition, preprocessing extraction, then uses these features train model using optimized machine learning algorithm. results show that introduction GIS algorithms PSO-optimized SVM very effective can improve parameter finding ability. terms prediction accuracy, Principal Component Analysis (PCA) combined GISPSO-SVM algorithm achieved 96% higher than 93% Competitive Adaptive Weighted Sampling (CARS) And selection accuracy degrees. This novel approach helps evaluate non-destructively provides perspective future detection methods.
Язык: Английский
Процитировано
1
Horticulturae, Год журнала: 2024, Номер 10(12), С. 1363 - 1363
Опубликована: Дек. 19, 2024
Phytopathogens pose a serious threat to agriculture, causing decrease in yield and product quality. This necessitates the development of methods for early detection phytopathogens, which will reduce losses improve quality by using lower quantities agrochemicals. In this study, efficiency spectral imaging differentiation diseases caused pathogens different types (Potato virus X (PVX) bacterium Pseudomonas syringae) was analyzed. An evaluation visual symptoms demonstrated presence pronounced case bacterial infection an almost complete absence viral infection. P. syringae severe inhibition photosynthetic activity infected leaf, while PVX did not have effect on activity. Reflectance spectra healthy plants were detected range from 400 1000 nm hyperspectral camera, dynamics infection-induced changes during disease progression strong increase reflectance blue red ranges, as well near-infrared range. PVX-induced spectrum had smaller amplitudes compared syringae, localized mainly edge (RE) The entire set normalized indices (NRI) analyzed calculated. most sensitive NRIs (NRI510/545, NRI510/850) (NRI600/850, NRI700/850) infections identified. use these makes it possible detect at stage. study identified possibility multispectral method pathogen detection, has high performance low cost analysis.
Язык: Английский
Процитировано
1
Plants, Год журнала: 2023, Номер 12(15), С. 2825 - 2825
Опубликована: Июль 31, 2023
The National Agrobiodiversity Center under the Rural Development Administration (RDA) in Jeonju, Republic of Korea stands as foremost national genebank country. Over years, has remained committed to enriching its collection with foreign genetic resources, elevating status a world-class plant resources (PGR)- holding genebank. Currently, several steps are being undertaken improve accessibility well international researchers, data available on and amend passport information for accessions. With implementation Nagoya Protocol, origin is highlighted an important input information. RDA-Genebank actively responds Protocol by supplementing lacking their origin. In addition, large number conserved continuously multiplied, agronomic traits investigated concurrently. traditional methods characterization germplasm requiring significant amount time effort, we have initiated high-throughput phenotyping using digital techniques our data. Primarily, started adding seed phenotype followed measuring root phenotypes which stored traits. This may be initial step toward largescale germplasm. this study, aim provide introduction RDA-Genebank, adopted standards, establishment improvement
Язык: Английский
Процитировано
3