Applied Energy, Год журнала: 2024, Номер 379, С. 124946 - 124946
Опубликована: Ноя. 22, 2024
Язык: Английский
Journal of Advances in Biology & Biotechnology, Год журнала: 2024, Номер 27(4), С. 59 - 72
Опубликована: Март 16, 2024
This extensive analysis reveals the significant influence of artificial light, especially light-emitting diodes (LEDs), on enhancing plant growth for sustainable agriculture and horticulture optimization. The production seedlings is an essential component contemporary agriculture. While study conducted complex relationships between plants light sources. Controlled conditions in chambers vertical farming systems are excellent solutions that enable year-round space-efficient seedling production. It possible to draw conclusion using can result increased biomass, faster rates, better crop quality. review highlights effects various spectra, intensities, durations critical physiological processes involved seed germination, vegetative growth, overall development during propagation. Apart from that, new looks into complexity photosynthesis, photomorphogenesis, photoperiodic reactions, providing useful insights customising different crops developmental stages.
Язык: Английский
Процитировано
2
Ecological Engineering & Environmental Technology, Год журнала: 2024, Номер 25(6), С. 234 - 254
Опубликована: Апрель 26, 2024
Ensuring food security is a top goal for all nations, yet infected plants can negatively impact agricultural production and the country's economic resources.In past, farmers have depended on conventional techniques to enhance crop yield.In recent times, there has been significant decline in due pest infestations Chilli crops.The progress of deep learning facilitates categorization diverse sorts images practical applications.Especially, detecting multi-class pests with good accuracy using algorithms consistently challenge.The proposed study concentrated identifying leaves methods such as YOLOv5 YOLOv7.To improve classification accuracy, new unique dataset called standard balanced custom 'Chilli dataset' created 13,414 images.This includes three specific classes: Black Thrips, Redmites, White Fly.We analysed YOLOv7 evaluate their effectiveness crops obtained novel detection performance metrics.The resultant parameters mean Average Precision (mAP) classes 98.6% 86.1% YOLOv7.The YOLOv5s detector demonstrates superior compared classification, 12.5% improvement.The algorithm achieves its best (86.1%) at lower epoch (110), while highest (98.6%) higher (350).Nevertheless, despite this distinction, recommended accurately well-balanced type datasets, comparison YOLOv7, VGG-16 (~92.7%), VGG-19 (~84.24%)deep architectures.
Язык: Английский
Процитировано
2
Cogent Engineering, Год журнала: 2024, Номер 11(1)
Опубликована: Июль 5, 2024
Hand-pushed cone penetrometer has been utilized to assess soil compaction based on penetration resistance (SPR). However, the manual operation of these devices can be quite challenging and erroneous. The accuracy data gathered using such hindered by operator's limitation in maintaining a constant-rate into soil, thus preventing attainment steady, predefined rate. To address this issue, constant-rate, IoT-enabled is designed constructed. developed measures SPR across profile with lead screw arrangement that ensures penetration. device comprises mechanical system an electronic control unit utilizes IoT framework. includes primary frame, standard probe. SPR, depth along coordinates location are measured stored web server. A user-friendly customizable interface mobile application enable real-time access. up 2000 kPa 400 mm depth. Comparative analysis shows (CRP) provides more reliable less variable measurements compared hand-pushed (HPP), significant differences observed at multiple depths. This maintains penetration, ensuring adherence standards for accurate measurements.
Язык: Английский
Процитировано
2
International Journal of Innovative Science and Research Technology (IJISRT), Год журнала: 2024, Номер unknown, С. 3036 - 3042
Опубликована: Июль 24, 2024
The integration of internet things in agriculture has paved way for smart farming solutions thereby enhancing productivity and efficiency. This paper aimed at developing a system consisting two (2) modules namely: Agro-AI module, Chabot that allows the farmers to inquire, Get–Started which is registration portal training farmers. In addition, inclusion soil detector can assess PH, moisture fertility, all play significant role giving real-time information about conditions boost farmers’ productivity. was built using following techniques: Javascript, HTML, PHP, CSS front end MySQL back end. implementation Sf- IoT will help improve farmers' assist making decisions regarding management leading improved crop quality, yield, harvest.
Язык: Английский
Процитировано
2
Applied Energy, Год журнала: 2024, Номер 379, С. 124946 - 124946
Опубликована: Ноя. 22, 2024
Язык: Английский
Процитировано
2