Biology, classification, and entomopathogen-based management and their mode of action on Tuta absoluta (Meyrick) in Asia

Frontiers in Microbiology, Journal Year: 2024, Volume and Issue: 15

Published: Aug. 7, 2024

, known as the South American tomato leaf miner, significantly impacts plants (

Language: Английский

---

Transforming Agriculture: Harnessing Robotics and Drones for Sustainable Farming Solution

Journal of Experimental Agriculture International, Journal Year: 2024, Volume and Issue: 46(7), P. 219 - 231

Published: June 11, 2024

The agricultural sector is facing unprecedented challenges due to increasing food demand, environmental degradation, and labour shortages, exacerbated by a burgeoning global population. To address these issues sustainably, the concept of "smart farming" utilizing advanced robotics drones has emerged as transformative solution. This review paper delves into significant impact cutting-edge technologies on modern agriculture, focusing their applications, benefits, challenges, future prospects. Robotics in agriculture have considerably, playing crucial roles tasks such tillage, seeding, crop protection, harvesting, animal husbandry. latest robotic systems are equipped with artificial intelligence (AI) machine learning algorithms, enabling them perform complex high precision efficiency. These potential enhance productivity while minimizing impacts through farming techniques. Drones, similarly, revolutionized applications monitoring, spraying, mapping, surveillance. drone models multispectral sensors, GPS technology, AI-driven analytics, providing farmers real-time data actionable insights. helps optimizing resource use, improving health, yield reducing footprints. Despite advancements, several impede widespread adoption. High initial costs, technological curves, regulatory hurdles, security concerns remain barriers. Additionally, integration requires substantial infrastructure training, which can be daunting for small-scale farmers. emphasizes need strategic investments supportive policies overcome challenges. Collaborations between technology developers, experts, policymakers drive innovation facilitate adoption smart practices. hold immense revolutionize traditional By harnessing technologies, industry achieve sustainable solutions, enhancing ensuring future. provides comprehensive analysis current state directions farming, underscoring pivotal role transforming agriculture.

Language: Английский

---

Peningkatan Keberdayaan Ekonomi Melalui Pengelolaan Limbah Organik dan Pertanian Terpadu di Lahan Terbatas

Jurnal ABDINUS Jurnal Pengabdian Nusantara, Journal Year: 2025, Volume and Issue: 9(1), P. 46 - 57

Published: Jan. 1, 2025

Praktik pertanian di lahan terbatas dengan memanfaatkan limbah organik menjadi tantangan tersendiri, khususnya Desa Lempake, Samarinda Utara. Bank Ramli Bukit Benanga RT 037 Perumahan telah berhasil mengolah eco enzyme, kompos, dan maggot, meskipun produk tersebut belum dimanfaatkan dipasarkan secara optimal. Program Kemitraan Masyarakat ini bertujuan untuk memberdayakan masyarakat meningkatkan keterampilan dalam terpadu memfasilitasi pemasaran dari terbatas. Melalui pelatihan pendampingan teknik aerofarming, tabulampot, budikdamber, program maggot lebih efektif budidaya tanaman ikan. juga membekali mitra desain kemasan strategi online offline. Hasil antara lain peningkatan produksi pangan mandiri, pendapatan melalui organik, kualitas lingkungan sekitar Benanga. Selain itu, mendukung Tujuan Pembangunan Berkelanjutan (SDGs), penanggulangan kemiskinan, kesejahteraan, serta pola konsumsi yang berkelanjutan.

---

Geometric Alignment Improves Wheat NDVI Calculation from Ground-Based Multispectral Images

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 743 - 743

Published: Feb. 20, 2025

Multispectral sensors are integral to vegetation analysis, particularly in the calculation of various indices (VIs). The use integrated multispectral has become prevalent research, although their effectiveness is influenced by several factors. This highlights need for ongoing research into enhancement techniques improve accuracy and reliability status estimation. study investigated impact field view (FOV) variability on normalized differential index (NDVI) using a sensor. Data were collected from wheat at four growth stages (GS) (GS 1, GS 2, 3, 4, 10, 34, 70, 84 days after sowing (DAS), respectively) mounted around 100 cm above crop canopy. An active sensor was used provide reference data assessing measurement. A program developed Python (ver. 3.10) programming language process global navigation satellite system (GNSS) coordinates segment images align with FOV extracting reflectance NDVI calculation. results showed that proper alignment significantly improved regression metrics (R2 RMSE) all stages, R2 improvements ranging 3% 33%, RMSE reductions 0.03 0.06, respectively. high vegetative stage less affected due misalignment. These promising toward improving accuracy, especially during early mid-growth crop.

Language: Английский

---

Revolutionizing water quality management the impact of machine learning and artificial intelligence

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 27 - 42

Published: Jan. 1, 2025

Language: Английский

---

Seed multispectral imaging combined with machine learning algorithms for distinguishing different varieties of lettuce (Lactuca sativa L.)

Food Chemistry X, Journal Year: 2025, Volume and Issue: unknown, P. 102399 - 102399

Published: March 1, 2025

Accurate identification of high-quality seeds is crucial for maintaining superior crop traits. Lettuce widely consumed vegetable with diverse varieties, however, the traditionally methods are both time-consuming and labor-intensive. This study explores feasibility rapid, non-destructive different lettuce varieties using multispectral imaging combined machine learning. We firstly collected seed morphological spectral data from 15 imaging. Then we applied Support Vector Machine (SVM), Random Forest (RF), Back-Propagation Neural Network (BP), Linear Discriminant Analysis (LDA) variety identification. The results demonstrated that learning models, effectively distinguished varieties. LDA model based on fusion feature performed best, average classification accuracy was 92.7 %. In batch validation, achieved an 93.2 %.This method reduces cost improves efficiency, showing great potential in other crops.

Language: Английский

---

Bridging agro-science and human nutrition: zinc nanoparticles and biochar as catalysts for enhanced crop productivity and biofortification

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: Aug. 16, 2024

The integration of zinc nanoparticles (Zn NPs) with biochar offers a transformative approach to sustainable agriculture by enhancing plant productivity and human nutrition. This combination improves soil health, optimizes nutrient uptake, increases resilience environmental stressors, leading superior crop performance. Our literature review shows that combining Zn NPs significantly boosts the composition, including proteins, vitamins, sugars, secondary metabolites. enhancement tolerance challenges, quality, shelf life. technique addresses global issue deficiency biofortifying food crops increased levels, such as mung beans, lettuce, tomatoes, wheat, maize, rice, citrus, apples, microgreens. Additionally, improve properties water retention, cation exchange capacity (CEC), microbial activity, making soils more fertile productive. porous structure facilitates slow sustained release Zn, ensuring its bioavailability over extended periods reducing need for frequent fertilizer applications. synergy promotes agricultural practices reduces footprint traditional farming methods. However, potential ecological risks biomagnification, nanoparticle accumulation, toxicity require careful consideration. Comprehensive risk assessments management strategies are essential ensure benefits do not compromise or health. Future research should focus on deploying in agriculture, balancing security integrity positioning this viable solution nutrient-efficient agriculture.

Language: Английский

---

Innovations in Date palm(Phoenix dactylifera L.) micropropagation: detailed review of in vitro culture methods and plant growth regulator applications

Plant Cell Tissue and Organ Culture (PCTOC), Journal Year: 2024, Volume and Issue: 159(1)

Published: Sept. 25, 2024

Language: Английский

---

Optimizing Edge AI for Tomato Leaf Disease Identification

Engineering Technology & Applied Science Research, Journal Year: 2024, Volume and Issue: 14(4), P. 16061 - 16068

Published: Aug. 2, 2024

This study addresses the critical challenge of real-time identification tomato leaf diseases using edge computing. Traditional plant disease detection methods rely on centralized cloud-based solutions that suffer from latency issues and require substantial bandwidth, making them less viable for applications in remote or bandwidth-constrained environments. In response to these limitations, this proposes an on-the-edge processing framework employing Convolutional Neural Networks (CNNs) identify diseases. approach brings computation closer data source, reducing conserving bandwidth. evaluates various pre-trained models, including MobileNetV2, InceptionV3, ResNet50, VGG19 against a custom CNN, training validating comprehensive dataset images. MobileNetV2 demonstrated exceptional performance, achieving accuracy 98.99%. The results highlight potential AI revolutionize agricultural settings, offering scalable, efficient, responsive solution can be integrated into broader smart farming systems. not only improves but also provide actionable insights timely alerts farmers, ultimately contributing increased crop yields food security.

Language: Английский

---

An overview of symbiotic and pathogenic interactions at the fungi-plant interface under environmental constraints

Frontiers in Fungal Biology, Journal Year: 2024, Volume and Issue: 5

Published: Oct. 25, 2024

The complex and dynamic interactions between fungi plants constitute a critical arena in ecological science. In this comprehensive review paper, we explore the multifaceted relationships at fungi-plant interface, encompassing both mutualistic antagonistic interactions, environmental factors influencing these associations. Mutualistic associations, notably mycorrhizal relationships, play pivotal role enhancing plant health balance. On contrary, fungal diseases pose significant threat to health, agriculture, natural ecosystems, such as rusts, smuts, powdery mildews, downy wilts, which can cause extensive damage lead substantial economic losses. Environmental constraints abiotic biotic are elucidated understand their shaping interface. Temperature, moisture, soil conditions, along with presence of other microbes, herbivores, competing plants, significantly influence outcome interactions. interplay mutualism antagonism is emphasised key determinant ecosystem stability. implications extend overall productivity, conservation efforts. potential applications knowledge bioremediation, biotechnology, biocontrol strategies emphasise importance adapting climate change. However, challenges future directions field include impacts change, emerging pathogens, genomic insights, interface restoration ecology. Hence, paper provides overview influences, conservation, restoration.

Language: Английский

---