Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 27 - 37
Published: Nov. 22, 2024
Language: Английский
Frontiers in Sustainable Food Systems, Journal Year: 2025, Volume and Issue: 9
Published: Feb. 26, 2025
The agriculture sector is currently facing several challenges, including the growing global human population, depletion of natural resources, reduction arable land, rapidly changing climate, and frequent occurrence diseases such as Ebola, Lassa, Zika, Nipah, most recently, COVID-19 pandemic. These challenges pose a threat to food nutritional security place pressure on scientific community achieve Sustainable Development Goal 2 (SDG2), which aims eradicate hunger malnutrition. Technological advancement plays significant role in enhancing our understanding agricultural system its interactions from cellular level green field for benefit humanity. use remote sensing (RS), artificial intelligence (AI), machine learning (ML) approaches highly advantageous producing precise accurate datasets develop management tools models. technologies are beneficial soil types, efficiently managing water, optimizing nutrient application, designing forecasting early warning models, protecting crops plant insect pests, detecting threats locusts. application RS, AI, ML algorithms promising transformative approach improve resilience against biotic abiotic stresses sustainability meet needs ever-growing population. In this article covered leveraging AI RS data, how these enable real time monitoring, detection, pest outbreaks. Furthermore, discussed allows more precise, targeted control interventions, reducing reliance broad spectrum pesticides minimizing environmental impact. Despite data quality technology accessibility, integration holds potential revolutionizing management.
Language: Английский
Citations
0
Applied Energy, Journal Year: 2025, Volume and Issue: 389, P. 125743 - 125743
Published: March 26, 2025
Language: Английский
Citations
0
Agricultural Water Management, Journal Year: 2025, Volume and Issue: 312, P. 109448 - 109448
Published: March 29, 2025
Language: Английский
Citations
0
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: May 7, 2025
Accurately predicting global soil moisture (SM) is crucial for sustainable agriculture and water resource management. Recognizing the challenges posed by heterogeneity of SM's spatiotemporal variability, this study proposes a novel approach that leverages Fourier analysis to decompose periodic fluctuations in SM, revealing underlying trends cycles. This integrated with Long Short Term Memory (LSTM) networks enhance accuracy SM prediction. transforms time series data into frequencies amplitudes, capturing its intrinsic characteristics. transformation reveals both variable invariant features representing changes within between periods. By integrating these sequence leveraging memory learning capabilities LSTM neural networks, reliability prediction can be enhanced. Our experiments on LandBench1.0 dataset demonstrate proposed model reduces root mean square error [Formula: see text] compared state-of-the-art methods. underscores adapt inherent complex spatial-temporal patterns dynamics, especially scenarios characterized rapid environmental subtle temporal dynamics.
Language: Английский
Citations
0
Smart Agricultural Technology, Journal Year: 2025, Volume and Issue: unknown, P. 101008 - 101008
Published: May 1, 2025
Language: Английский
Citations
0
Agronomy, Journal Year: 2023, Volume and Issue: 13(11), P. 2811 - 2811
Published: Nov. 13, 2023
Drought stress poses a considerable challenge to agriculture sustainability in arid regions. Water scarcity severely affects date palm growth and productivity these However, as water resources become increasingly scarce regions, understanding the drought tolerance of cultivars becomes imperative for developing drought-resistant optimizing irrigation usage sustainable agriculture. This research examines impact different levels based on evapotranspiration (ETc), i.e., 40%, 60%, 80%, 100% ETc, time intervals (0, 6, 12, 18, 24 months) leaf growth, net photosynthesis, chlorophyll b content, relative content (LRWC) four prominent cultivars, Khalas, Barhee, Hilali, Ashrasee. In addition, study also effects dry weight, potassium calcium leaf, stem, root, proline fresh leaves cultivars. A solar-powered drip system with automated time-based scheduling was used accurately control amount. To real-time estimate ETc area, meteorological data were collected using cloud-based IoT system. The findings this revealed that severe conditions (40 60 % ETc) significantly reduced plant biomass, physiological biochemical attributes; however, can be grown under moderate (80% minimal effect phenotypic, physiological, traits conserve water. drought-related characteristics decreased gradually an increase over months. Comparing Khalas Barhee are more drought-tolerant, followed by while Ashrasee is susceptible. elucidated conservation strategy employed response drought-induced morphological parameters It provides valuable insights into practices future studies focused other nondestructive innovative techniques such pulse-amplitude-modulation (PAM) fluorimetry, infrared radiation (IR), video imaging (VIS) methods identify palms.
Language: Английский
Citations
9
IntechOpen eBooks, Journal Year: 2023, Volume and Issue: unknown
Published: Oct. 11, 2023
Date palm cultivation is an essential part of Saudi Arabia’s economy. However, it faces several challenges: water scarcity, improper farm management, pests and diseases, inadequate farming practices, processing marketing, labor shortages. Artificial intelligence (AI) the Internet Things (IoT) can help enrich crop enable predictive analytics, increase efficiency, promote sustainability in date cultivation. Recently, interest this sector has begun by applying latest precision engineering technologies integrated with AI IoT techniques to address these challenges. This chapter aims provide overview applications IoT-based technologies, such as sensors, ML algorithms, data their potential benefits challenges supporting Arabia. Specifically, smart irrigation, systems, cold storage pest infestation prediction, fruit quality optimization. In addition, economic environmental using Arabia that need be addressed realize fully. The provides insight into developments future directions for cultivation, providing valuable information researchers policymakers.
Language: Английский
Citations
8
Foods, Journal Year: 2023, Volume and Issue: 12(20), P. 3811 - 3811
Published: Oct. 17, 2023
Dates are highly perishable fruits, and maintaining their quality during storage is crucial. The current study aims to investigate the impact of conditions on dates (Khalas Sukary cultivars) at Tamer stage predict attributes using artificial neural networks (ANN). studied were modified atmosphere packing (MAP) gases (CO2, O2, N), packaging materials, temperature, time, evaluated moisture content, firmness, color parameters (L*, a*, b*, ∆E), pH, water activity, total soluble solids, microbial contamination. findings demonstrated that significantly impacted (p < 0.05) two stored date cultivars. use MAP with 20% CO2 + 80% N had a high potential decrease rate transformation growth 4 °C for both developed ANN models efficiently predicted changes closely aligned observed values under different conditions, as evidenced by low Root Mean Square Error (RMSE) Absolute Percentage (MAPE) values. In addition, reliability was further affirmed linear regression between measured values, which follow 1:1 line, R2 ranging from 0.766 0.980, demonstrate accurate estimating fruit attributes. study’s contribute food supply chain management through identification optimal predicting thereby minimizing waste enhancing safety.
Language: Английский
Citations
7
Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 5984 - 5984
Published: Nov. 28, 2024
This paper discusses how integrating renewable energy, AI, and IoT becomes important in promoting climate-smart agriculture. Due to the changing climate, rise energy costs, ensuring food security, agriculture faces unprecedented challenges; therefore, development toward innovative technologies is emerging for its sustainability efficiency. review synthesizes existing literature systematically identify AI could optimize resource management, increase productivity, reduce greenhouse gas emissions within an agricultural context. Key findings pointed importance of managing resources sustainably, scalability technologies, and, finally, policy interventions ensure technology adoption. The further outlines trends global adoption smart solutions, indicating areas commonality difference emphasizing need focused policies capacity-building initiatives that will help, particularly developing world, benefits such innovations. Eventually, this research covers some gaps understanding IoT, jointly contribute driving towards a greener more resilient sector.
Language: Английский
Citations
2
Remote Sensing in Earth Systems Sciences, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 28, 2024
Language: Английский
Citations
2