Organomineral fertilizer based on wood ash in bean cultivation in acidic tropical soil by Rackel Danielly de Souza Alves, Edna Maria Bonfim-Silva, Tonny José Araújo da Silva, Jakeline Rosa de Oliveira, Jholian Maicon Ribeiro-Santos, Luana Aparecida Menegaz Meneghetti

“…The organomineral fertilizer provided the highest shoot dry mass (23.0 g/pot) when no lime was applied, when compared to the other fertilizers. The highest grain yield of cowpea was observed in wood ash and organomineral, in the absence of liming. …”
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Comprehensive Structural, Chemical, and Optical Characterization of Cu₂ZnSnS₄ Films on Kapton Using the Automated Successive Ionic Layer Adsorption and Reacti... by Perla J. Vázquez-González, Martha L. Paniagua-Chávez, Lizette A. Zebadua-Chavarria, Rafael Mota-Grajales, C. A. Meza-Avendaño, Enrique Campos-González, A. Escobosa-Echavarría, Yaoqiao Hu, Aldo E. Pérez-Ramos, Manuel-Matuz, Carlos A. Hernández-Gutiérrez

“…Field emission scanning electron microscopy (FE-SEM) showed enhancements in surface morphology, with increased grain size and uniformity post-annealing. Chemical uniformity was confirmed through Secondary Ion Mass Spectrometry (SIMS), Energy-Dispersive Spectroscopy (EDS), and X-ray Photoelectron Spectroscopy (XPS). …”
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Assessing Four Decades of Land Use and Land Cover Change: Policy Impacts and Environmental Dynamics in the Min River Basin, Fujian, China by Weixuan Huang, Anil Shrestha, Yifan Xie, Jianwu Yan, Jingxin Wang, Futao Guo, Yuee Cao, Guangyu Wang

“…Second, by analyzing existing policies, we categorized four decades of LULCC trends from 1980 to 2020, delineating three distinct stages: (1) the Economic Restoration (ER) stage (1978–1989), when the ecological impacts of LULCC on forests, croplands, and water bodies received limited policy attention; (2) the Construction of Ecological Protection and Economic Development (EPED) stage (1989–2012), which saw a significant increase in forest coverage, primarily driven by various central and provincial environmental conservation policies, such as the Green for Grain and the “Three-Five-Seven Reforestation Project” in Fujian; and (3) the Ecological Civilization (EC) stage (2012–2020), in which policy focus shifted from expanding forest land areas to enhancing the quality of these areas. …”
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Preparation and Electrochemical Characterization of Y-Doped Li_1.3Al_0.3Ti_1.7(PO₄)₃ Solid Electrolytes for Lithium-Metal Batter... by Zhongran Yao, Fen Qi, Qiang Sun, Lin Ye, Xiaowei Yang, Guojie Chao, Pei Tang, Kongjun Zhu

“…However, their practical application is hindered by poor sintering characteristics and high grain boundary resistance. In this investigation, Li_1.3Al_0.3−xY_xTi_1.7(PO₄)₃ (LAYTP-<i>x</i>, <i>x</i> = 0.00, 0.01, 0.03, 0.05, and 0.07) were successfully synthesized via conventional solid-state reaction to explore the impact of Y³⁺ on both ionic conductivity and chemical stability. …”
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Lithological and geochemical characterization of ‘adinole’ artefacts from cave deposits in southwest Wales: A material of choice during the late Middle to Upper Palaeolithic by Richard Bevins, Elizabeth A. Walker, Nick Pearce, Duncan Pirrie, Rob Ixer, Ian Saunders, Matthew Power

“…Twenty-three artefacts previously identified as being manufactured from adinole, a fine-grained metasomatic rock, from late Middle to Upper Palaeolithic cave sites in southwest Wales have been re-examined in terms of their petrology and geochemistry. …”
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The size-fractionated composition of particulate biogenic silica and its ecological significance in the Changjiang Estuary area by Xizhen Liu, Xizhen Liu, Bin Wang, Bin Wang, Siyang Chen, Haiyan Jin, Haiyan Jin, Yanpei Zhuang, Zhibing Jiang, Hongliang Li, Hongliang Li, Jianfang Chen, Jianfang Chen

“…Temperature and nutrients were crucial factors controlling the grain size structure and distribution of PBSi. Further, we observed that the distinct zones of high PBSi values in the surface waters were affected by the Changjiang freshwater flushing, and those in the bottom waters were affected by the Yellow Sea Cold Water masses. …”
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Supportive functions of soil organic carbon for ecosystem services in karst desertification areas by Wang Xingfu, Liu Yi, Xiong Kangning, Huang Xianfei, Zhang Zhenming

“…The agroforestry models “forest-grain”, “forest-fruit”, “forest-vegetable” and “forest-medicine” can be used as extension models of the artificial ecosystem, which can promote ecosystem service synergy and the comprehensive control of rocky desertification in the South China Karst.…”
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MASFNet: Multi-level attention and spatial sampling fusion network for pine wilt disease trees detection by Dong Ren, Meng Li, Ziyu Hong, Li Liu, Jingfeng Huang, Hang Sun, Shun Ren, Pan Sao, Wenbin Wang, Jingcheng Zhang

“…Additionally, we propose a spatial sampling fusion (SSF) module that samples critical sub-regions of features across different layers, generating finer-grained features and thereby enhancing the discrimination between highly similar objects. …”
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Differences in soil Cd immobilization and blockage of rice Cd uptake by biochar derived from crop residue and bone − A 2-year field experiment by Zhongjun Xue, Fengfeng Sui, Yanjie Qi, Siyu Pan, Ning Wang, Rongjun Bian, Stephen Joseph, Xuhui Zhang, Lianqing Li, Genxing Pan

“…The results indicated that biochar significantly decreased grain Cd concentrations by on average of 60.1 % and 22.9 % in 2021 and 2022, respectively. …”
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Dietary intakes, food behaviours, and health indicators among Métis youth in Manitoba, Canada by Chantal Perchotte, Olena Kloss, Joyce Slater, Alan Katz, Bhanu Pilli, Aynslie Hinds, Marcelo L Urquia, Julianne Sanguins, Chris Green, Jaime Cidro, Dan Chateau, Nathan Nickel, Thomas Falkenberg

“…Percent energy intake of saturated fat was also significantly higher in Métis (12.4%) than non-Métis (11.6%) participants. Median intakes of Grain Products and Meat and Alternatives servings were significantly lower among Métis than non-Métis (6.0 vs. 7.0 and 1.8 vs. 2.0, respectively) participants. …”
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Dynamics of ecosystem service values in the Tarim River Basin by Mengxin Sun, Mengxin Sun, Xin Shen, Xin Shen, Hailiang Xu, Hailiang Xu, Ai Shajiang·Aili, Ai Shajiang·Aili

“…Farmland expanded by over 10% from 2000 to 2015, but its growth slowed between 2015 and 2020 due to the “Grain for Green” policy. Built-up areas grew significantly between 2005 and 2010 but declined afterward due to stricter urban planning. …”
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Tracing Aquatic Macrophyte Development in Nansi Lake, Northern China's Largest Freshwater Lake: Plant Macrofossils From 1855 to Present by Qinghui Zhang, Yufei Wu, Liwei Yang, Zekun Li, Zonglei Li, Yuying Yang, Shiyue Chen, Enfeng Liu

“…Multiple factor analysis was employed to investigate the correlation between these shifts and changes in paleolimnological indicators (invertebrates, geochemistry, and grain size), as well as documented records related to hydrology, climate changes, and human activities. …”
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Molecular cytogenetic characteristics of new spring bread wheat introgressive lines resistant to stem rust by O. A. Baranova, I. G. Adonina, S. N. Sibikeev

“…Recently, the harmfulness of a dangerous wheat disease, stem rust, caused by Puccinia graminis f. sp. tritici, was increased in the main grain-producing regions of the Russian Federation. …”
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An empowerment programme to improve diet quality during pregnancy – the Power 4 a Healthy Pregnancy cluster randomised controlled trial by Renske M. van Lonkhuijzen, Jeanne H. M. de Vries, Elske Brouwer-Brolsma, Susanne Cremers, Janine P. M. Faessen, Edith J. M. Feskens, Annemarie Wagemakers

“…Although other components, including fruit, whole-grain foods, nuts, dairy foods, iodine, and fish showed greater average increases in diet quality scores within the intervention group, these differences were not significant. …”
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Superplastic Forming/Diffusion Bonding of TA15 Titanium Alloy for Manufacturing Integrated Solid/Hollow Four-Layer Grid Lightweight Structure Components by Zheng Han, Yuhan Xing, Taiying Liu, Ning Zhang, Shaosong Jiang, Zhen Lu

“…When the temperature is too high, the grain size increases remarkably, and the elongation decreases. …”
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Mobilization of plant genetic resources from the territory of India by N. P. Loskutova, T. M. Ozerskaya

“…The greatest number of accessions received by the Institute represented groat crops (over 3500), followed by wheat (1250), and industrial crops and grain legumes (nearly 1000 each). In total, during the whole period of its existence, the Institute has mobilized 24605 accessions.…”
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Resistance of spring bread wheat cultivars and lines to Septoria leaf blotch, tan spot, and spot blotch pathogens by Yu. V. Zeleneva, V. P. Sudnikovа, N. M. Kovalenkо, I. V. Gusev

“…Leaf and stem diseases of cereal crops are among the most harmful in the agrocenoses of Tambov Province, significantly reducing grain yield and rapidly progressing in many regions of Russia. …”
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Closed-loop systems for plants expressing animal proteins: a modernized framework to safeguard the future of agricultural innovation by Kristin A. Bresnahan, Justin M. Ferber, J. Thomas Carrato, Thomas J. Stoddard, Patrick V. Palad, Magi Richani

“…PMF products, particularly those that express an animal protein in seed and grain crops, have the potential to substantially benefit U.S. and global agriculture, food systems, economies, and the environment. …”
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Sole and Combined Application of Biodigestate, N, P, and K Fertilizers: Impacts on Soil Chemical Properties and Maize Performance by Aruna Olasekan Adekiya, Olufunmilayo Titilayo Ande, Samuel Olatunde Dahunsi, Joshua Ogunwole

“…Overall, the treatment of DN1P1K1 demonstrated the highest grain yield, likely due to optimal nutrient supply from N, P, and K fertilizers, along with an improved soil environment facilitated by the biodigestate. …”
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Construction and Optimization of Integrated Yield Prediction Model Based on Phenotypic Characteristics of Rice Grown in Small–Scale Plantations by Jihong Sun, Peng Tian, Zhaowen Li, Xinrui Wang, Haokai Zhang, Jiangquan Chen, Ye Qian

“…This study employs four rice phenotypic traits, namely, panicle angle, panicle length, total branch length, and grain number, along with seven machine learning methods—multiple linear regression, support vector machine, MLP, random forest, GBR, XGBoost, and LightGBM—to construct a yield prediction model group. …”
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