Regulatory mechanisms in agroecosystems: A retrospective and forecast of spatial and temporal dynamics of precipitation as a factor of crop yield DOI Creative Commons
Y. Nykytiuk, O. Kravchenko

Regulatory Mechanisms in Biosystems, Год журнала: 2024, Номер 15(4), С. 688 - 695

Опубликована: Окт. 12, 2024

The research tested the hypothesis that climate of studied area has property spatial and temporal regularity, this regularity is hierarchically organized, which makes it possible to predict state in coming decades. practical aspect information obtained assessment prospects for changes yields most common crops region. variability precipitation between years 1960 2023, soil properties landscape cover structure were investigated within 10 administrative regions northern northwestern Ukraine. This region covers Polissia Forest-Steppe geographical zones. MEM variables able explain 95.1% precipitation. ANOVA revealed 8 canonical axes statistically significant. contribution explanation different, allows us identify hierarchical main patterns RDA1 RDA2 represent large-scale component variability. indicates differentiation meridional direction with allocation eastern western sectors denoting correlated land types. did not correlate properties, but had a positive correlation proportion broadleaf forests mosaic herbaceous shrubs cover. axis negative agricultural land. was positively organic matter sand content, negatively clay silt content. increased an increase broadleaf, coniferous or mixed vegetation structure. decreased sparse RDA3 independent content area, shrubs, forests. RDA4 increasing proportions rainfed cover, RDA5 crops, RDA6 RDA7 RDA8 soil. modelling dynamics over more than 60 can be carried out using eight AEM predictors, different frequencies variable amplitudes time. If we assume established oscillatory will continue decades, then these predictors extended time interest regression model used obtain forecast near future. downward trend precipitation, mainly areas developed agriculture.

Язык: Английский

Centralized and Decentralized Approach to Monsoon Precipitation Forecasting in Pakistan DOI Open Access

MaryamKhan,

Qudsia Zafar,

Sumayyea Salahuddin

и другие.

VFAST Transactions on Software Engineering, Год журнала: 2025, Номер 13(1), С. 72 - 87

Опубликована: Март 4, 2025

Rainfall, is one of the most important meteorological factors that affects many parts our everyday lives including crop productivity, water quality, livestock availability, hydroelectric power generation to name a few. Rainfall prediction can significantly contribute boosting economy by enabling better planning, risk management, and resource allocation in various industrial sectors. In this study, forty years monsoon precipitation data gathered for 39 stations across five zones Pakistan. We propose multi-step Long Short-Term Memory (LSTM)-based model capable forecasting Monsoon yearly data. Three LSTM models stack, bidirectional convolutional are applied on dataset performance these analysed using centralized decentralized approach. It observed RMSE score strategy was found than approach, whereby 100% had lower as compared one. Moreover, approach 78.7% different exhibited R2 > 0.9 values indicating general fit model.

Язык: Английский

Процитировано

0
Integrated water management and agroforestry planning in the Kulsi river basin: a data-driven decision-making approach DOI
Ananya Kalita, Ankur Pan Saikia, Pranveer Singh

и другие.

Agroforestry Systems, Год журнала: 2025, Номер 99(5)

Опубликована: Апрель 28, 2025

Язык: Английский

Процитировано

0
Blockchain Technology Adoption for Agriculture, Manufacturing, Services, Knowledge, Culture, and Research: A Systematic Literature Review DOI Open Access
Vasiliki Basdekidou, Harry Papapanagos

WSEAS TRANSACTIONS ON SYSTEMS, Год журнала: 2025, Номер 24, С. 229 - 278

Опубликована: Май 6, 2025

Since FinTech had the most potential in business, economics, and knowledge disciplines, study's major goal was to address contributions of Blockchain technology adoption (BCT/BCA) six knowledge, culture, research areas. To ensure that on subject accessed pertinent publications were found, vetted, examined, PRISMA technique -a model for systematic literature reviews (SLRs)- employed this investigation. The results show BCA improves organizational procedures, performance, fidelity, integrity, trust businesses, cultures, projects with a disrupting financial (FinTech) mindset. It also enhances corporate transaction transparency scalability, big data, same-data, information sharing, prevents fraud fraudulence suspension cyber-hacking protection. Additionally, implementation smart contracts offers ESG sustainability benefits. This hybrid methodology, blending together qualitative analysis SLR. All 789 chosen initial step underwent quantitative analysis, eight cited papers passed screening process examination. study sequence is composed three layers: (i) factors function as functionality, (ii) possibilities problems related variables, (iii) contributions, consequences, outlook issues- defined paper projected Furthermore, significant contribution thought be managers' ability consult suggested insightful information, economic difficulties, estimation. Scholars, researchers, managers, practitioners will all benefit from study.

Язык: Английский

Процитировано

0
Trend Analysis of Rainfall for Multi-Purpose Water Resources Projects Using Machine Learning Predictive Model-ARIMA DOI
Rahul Grover,

Siddhartha Sharma,

Priya Jindal

и другие.

SN Computer Science, Год журнала: 2024, Номер 5(8)

Опубликована: Ноя. 29, 2024

Язык: Английский

Процитировано

2
AI-Based Short-Term Precipitation Prediction in Precision Agriculture DOI

Mehmet Selahaddin Şentop,

Meriç Yücel, Burak Berk Üstündağ

и другие.

Опубликована: Июль 15, 2024

Язык: Английский

Процитировано

0
Regulatory mechanisms in agroecosystems: A retrospective and forecast of spatial and temporal dynamics of precipitation as a factor of crop yield DOI Creative Commons
Y. Nykytiuk, O. Kravchenko

Regulatory Mechanisms in Biosystems, Год журнала: 2024, Номер 15(4), С. 688 - 695

Опубликована: Окт. 12, 2024

The research tested the hypothesis that climate of studied area has property spatial and temporal regularity, this regularity is hierarchically organized, which makes it possible to predict state in coming decades. practical aspect information obtained assessment prospects for changes yields most common crops region. variability precipitation between years 1960 2023, soil properties landscape cover structure were investigated within 10 administrative regions northern northwestern Ukraine. This region covers Polissia Forest-Steppe geographical zones. MEM variables able explain 95.1% precipitation. ANOVA revealed 8 canonical axes statistically significant. contribution explanation different, allows us identify hierarchical main patterns RDA1 RDA2 represent large-scale component variability. indicates differentiation meridional direction with allocation eastern western sectors denoting correlated land types. did not correlate properties, but had a positive correlation proportion broadleaf forests mosaic herbaceous shrubs cover. axis negative agricultural land. was positively organic matter sand content, negatively clay silt content. increased an increase broadleaf, coniferous or mixed vegetation structure. decreased sparse RDA3 independent content area, shrubs, forests. RDA4 increasing proportions rainfed cover, RDA5 crops, RDA6 RDA7 RDA8 soil. modelling dynamics over more than 60 can be carried out using eight AEM predictors, different frequencies variable amplitudes time. If we assume established oscillatory will continue decades, then these predictors extended time interest regression model used obtain forecast near future. downward trend precipitation, mainly areas developed agriculture.

Язык: Английский

Процитировано

0