Long-term reduced agricultural nonpoint source pollution driven by rural population aging DOI Creative Commons
Ming Gao, Fanlue Li, Meili Huan

и другие.

Humanities and Social Sciences Communications, Год журнала: 2025, Номер 12(1)

Опубликована: Апрель 18, 2025

Язык: Английский

Does regional economic development drive sustainable grain production growth in China? Evidence from spatiotemporal perspective on low-carbon total factor productivity DOI
Ruixue Wang, Xiangzheng Deng, Yunxiao Gao

и другие.

Socio-Economic Planning Sciences, Год журнала: 2024, Номер 98, С. 102129 - 102129

Опубликована: Дек. 3, 2024

Язык: Английский

Процитировано

7

Unleashing the power of innovation and sustainability: Transforming cereal production in the BRICS countries DOI Creative Commons
Cosimo Magazzino,

Tulia Gattone,

Muhammad Usman

и другие.

Ecological Indicators, Год журнала: 2024, Номер 167, С. 112618 - 112618

Опубликована: Сен. 16, 2024

Язык: Английский

Процитировано

6

Does climate change matter for bank profitability? Evidence from China DOI
Chien‐Chiang Lee, Xiaoli Zhang, Chi‐Chuan Lee

и другие.

The North American Journal of Economics and Finance, Год журнала: 2024, Номер 74, С. 102257 - 102257

Опубликована: Авг. 5, 2024

Язык: Английский

Процитировано

5

Rethinking energy poverty alleviation through financial inclusion: Do institutional quality and climate change risk matter? DOI
Isaiah Maket

Utilities Policy, Год журнала: 2024, Номер 91, С. 101820 - 101820

Опубликована: Сен. 12, 2024

Язык: Английский

Процитировано

5

Impact of agricultural credit on coffee productivity in Kenya DOI Creative Commons
Richard Wamalwa Wanzala, Nyankomo Marwa, Lwanga Elizabeth Nanziri

и другие.

World Development Sustainability, Год журнала: 2024, Номер 5, С. 100166 - 100166

Опубликована: Июнь 22, 2024

Historically, agricultural credit programs have been used as a policy instrument to improve productivity and livelihoods of smallholder farmers. The effectiveness such has widely deliberated with an opaque unanimity being reached since yield is stochastic. Therefore, this study examines the impact provided by Government Kenya intervention boost coffee productivity. Over years, there little – if any in-depth analysis that dedicated establishing on This surveyed 174 farmers (participants non-participants in program) Kiambu County between 2015 2019. paper espouses DEA Malmquist index estimate efficiency for participating non-participating program. empirical results disclose had highest geomean change (152%), (40.5%), technical (53.2%) scale (40.5%). Bayesian Modelling Average was assess determinants (BMA) findings from BMA indicated variety, education, extension visits crop system positive Gender age farmer negative Thus, these insights work would be instrumental providing directions terms lending crafting policies aimed at enhancing

Язык: Английский

Процитировано

4

Assessing energy efficiency, regional disparities in production technology, and factors influencing total factor energy productivity change in the agricultural sector of China DOI Creative Commons

Xiaomei Luan,

Rizwana Yasmeen, Wasi Ul Hassan Shah

и другие.

Heliyon, Год журнала: 2024, Номер 10(15), С. e35043 - e35043

Опубликована: Июль 24, 2024

Efficiently utilizing the energy resources in agriculture sector to produce more agricultural output with minimum environmental degradation is a shared global challenge. The Chinese government has introduced various policies aimed at enhancing efficiency (EE) and total factor productivity (TFEP) while addressing regional technological disparities sector. This study utilized DEA Super-SBM, Meta frontier Analysis, Malmquist-Luenberger index assess efficiency, changes productivity, technology gap ratio (TGR) across 30 provinces mainland China three distinct regions during period from 2000 2020. findings reveal that average EE China's 0.8492, indicating that, on average, there 15.08 % potential for improvement growth within Qinghai (1.5828), Shanghai (1.3716), Hainan (1.3582) are found be top 3 performers highest levels. Eastern region demonstrates high excellence EE, value of 1.0532. TGR Zhejiang indicates superior production utilize efficiently. Except Zhejiang, Liaoning, Jiangsu, Shanghai, Guangdong, Ningxia, above 0.96 near 1, China. Technology Gap Ratio eastern central western regions, consistently approaching 1. suggests possess advanced technologies, allowing them optimize resource utilization maximum output. (MLI) score 1.103 10.3 Further analysis reveals this primarily driven by change (TC), TC 1.080 surpassing (EC) 1.028. Among exhibits productivity. Specifically, (1.23), (1.197), Liaoning (1.184), Hebei (1.147) identified as Additionally, Kruskal-Wallis test confirmed statistically significant differences among regions.

Язык: Английский

Процитировано

4

Assessing technology's influence on cropland green production efficiency in the Yellow River basin, China DOI

Chaoqing Chai,

Ruiting Wen, Huadong Zhu

и другие.

Environmental Impact Assessment Review, Год журнала: 2025, Номер 112, С. 107838 - 107838

Опубликована: Фев. 3, 2025

Язык: Английский

Процитировано

0

Assessment of the resilience factors associated with European green efficiency DOI Creative Commons

C. Calafat-Marzal,

Virginia L. Vega,

V. Sanz-Torro

и другие.

The Science of The Total Environment, Год журнала: 2025, Номер 966, С. 178643 - 178643

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Climate Change and Agricultural Productivity in Nigeria (2000 – 2023) DOI Creative Commons

Obianamma C. Mbonu

African Journal of Economics and Sustainable Development, Год журнала: 2025, Номер 8(1), С. 80 - 94

Опубликована: Фев. 12, 2025

This study investigated the effects of climate change on agricultural productivity in Nigeria from 2000 to 2023. Data were sourced Central Bank (CBN) Statistical Bulletin and World Climate Change Database. The employed an ex-post facto research design, data analyzed using linear regression with Error Correction Model (ECM). findings revealed that had a negative impact output during examined period. Based these results, concludes detrimental Nigeria’s sector highlight need for immediate adaptive strategies. Key measures such as adoption climate-resilient crop varieties, enhanced irrigation systems, sustainable farming practices are essential building resilience ensuring food security amid current environmental challenges. recommends prioritizing research, development, dissemination varieties engineered drought heat resistance. Additionally, farmers should be supported adopt techniques capable withstanding high humidity associated diseases, including use humidity-tolerant varieties.

Язык: Английский

Процитировано

0

Optimal Drought Index Selection for Soil Moisture Monitoring at Multiple Depths in China’s Agricultural Regions DOI Creative Commons
Peiwen Yao, Hong Fan, Qilong Wu

и другие.

Agriculture, Год журнала: 2025, Номер 15(4), С. 423 - 423

Опубликована: Фев. 17, 2025

Droughts are a major driver of global environmental degradation, threatening lives and causing significant economic losses, with approximately 80% these losses linked to agricultural drought, characterized by soil moisture deficits. Remote sensing technology offers high spatiotemporal resolution data for continuous monitoring drought severity. However, the effectiveness remote indices across different depths remains unclear. This study assessed performance eight widely used indices—Perpendicular Drought Index (PDI), Modified Perpendicular (MPDI), Temperature Condition (TCI), Vegetation (VCI), Health (VHI), Normalized Supply Water (NVSWI), Temperature–Vegetation Dryness (TVDI), Standardized Precipitation–Evapotranspiration (SPEI) at multiple timescales—in five (0–50 cm, 10 cm intervals) nine regions China from 2001 2020. Results reveal that varies significantly depths, general decline in as depth increases. For between 10–40 VCI NVSWI exhibited highest accuracy, while PDI, MPDI, VHI performed optimally Northeast Plain. At 50 depth, however, optical struggled accurately capture conditions. Additionally, TCI TVDI showed notable lag effects, 4-month 5-month delays, respectively, SPEI cumulative effects over 3–6 months. These findings provide critical insights guide selection appropriate monitoring, aiding management decision-making.

Язык: Английский

Процитировано

0