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Green Energy & Environment 2025年第1期10卷 161-172页

作者： Meng-Ying Liu Zhe-Hui Zhang Xue-Qi Wang Qian Sun Chen Zhang Yu Li Zhuohua Sun Katalin Barta Feng Peng Tong-Qi Yuan state key laboratory of efficient production of forest Resources Beijing Forestry UniversityBeijing100083China Beijing key laboratory of Lignocellulosic Chemistry Beijing Forestry UniversityBeijing100083China Department of Chemistry Organic and Bioorganic ChemistryUniversity of GrazHeinrichstrasse 28/II8010 GrazAustria

Developing a cost-effective and environmentally friendly process for the production of valuable chemicals from abundant herbal biomass receives great attentions in recent ***,taking advantage of the“lignin first”strategy,corn straw is converted to valuable chemicals including lignin monomers,furfural and 5-methoxymethylfurfural via a two steps *** key of this research lies in the development of a green and low-cost catalytic process utilizing magnetic Raney Ni catalyst and high boiling point ethylene *** utilization of neat ethylene glycol as the sole slovent under atmospheric conditions obviates the need for additional additives,thereby facilitating the entire process to be conducted in glass flasks and rendering it highly convenient for scaling *** the initial step,depolymerization of corn straw lignin resulted in a monomer yield of 18.1 wt%.Subsequently,in a dimethyl carbonate system,the carbohydrate component underwent complete conversion in a one-pot process,yielding furfural and 5-methoxymethylfurfural as the primary products with an impressive yield of 47.7%.

关键词： Atmospheric reductive catalytic fractionation Corn straw Ethylene glycol Raney Ni 5-Methoxymethylfurfural

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Beyond amplitude: Phase integration in bird vocalization recognition with MHAResNet

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Avian Research 2025年第01期 119-128页

作者： Jiangjian Xie Zhulin Hao Chunhe Hu Changchun Zhang Junguo Zhang School of Technology Beijing Forestry University state key laboratory of efficient production of forest Resources Beijing Forestry University key laboratory of National forestry and Grassland Administration on forestry Equipment and Automation Research Center for Biodiversity Intelligent Monitoring Beijing Forestry University

Bird vocalizations are pivotal for ecological monitoring, providing insights into biodiversity and ecosystem health. Traditional recognition methods often neglect phase information, resulting in incomplete feature representation. In this paper, we introduce a novel approach to bird vocalization recognition(BVR) that integrates both amplitude and phase information, leading to enhanced species identification. We propose MHARes Net, a deep learning(DL) model that employs residual blocks and a multi-head attention mechanism to capture salient features from logarithmic power(POW), Instantaneous Frequency(IF), and Group Delay(GD) extracted from bird vocalizations. Experiments on three bird vocalization datasets demonstrate our method's superior performance, achieving accuracy rates of 94%, 98.9%, and 87.1% respectively. These results indicate that our approach provides a more effective representation of bird vocalizations, outperforming existing methods. This integration of phase information in BVR is innovative and significantly advances the field of automatic bird monitoring technology, offering valuable tools for ecological research and conservation efforts.

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Hybrid ecophysiological growth model for deciduous Populus tomentosa plantation in northern China

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forest Ecosystems 2025年第1期12卷 112-120页

作者： Serajis Salekin Mark Bloomberg Benye Xi Jinqiang Liu Yang Liu Doudou Li Euan G.Mason Scion Research(New Zealand forest Research Institute Ltd.) Rotorua3046New Zealand New Zealand School of forestry University of CanterburyChristchurch8140New Zealand state key laboratory of efficient production of forest Resources Beijing Forestry UniversityBeijing100083China key laboratory for Silviculture and forest Ecosystem Research in Arid-and Semi-Arid Region of National forestry and Grassland Administration Beijing Forestry UniversityBeijing100083China key laboratory for Silviculture and Conservation of Ministry of Education Beijing Forestry UniversityBeijing100083China Institute of Medicinal Plant Development Chinese Academy of Medical SciencesPeking Union Medical CollegeBeijing100193China

Short rotation plantation forestry(SRF)is being widely adopted to increase wood production,in order to meet global demand for wood ***,to ensure maximum gains from SRF,optimised management regimes need to be established by integrating robust predictions and an understanding of mechanisms underlying tree *** ecophysiological models,such as potentially useable light sum equation(PULSE)models,are useful tools requiring minimal input data that meet the requirements of *** models have been tested and calibrated for different evergreen conifers and broadleaves at both juvenile and mature stages of tree growth with coarse soil and climate ***,it is prudent to question:can adding detailed soil and climatic data reduce errors in this type of model?In addition,PULSE techniques have not been used to model deciduous species,which are a challenge for ecophysiological models due to their *** study developed a PULSE model for a clonal Populus tomentosa plantation in northern China using detailed edaphic and climatic *** results showed high precision and low bias in height(m)and basal area(m^(2)·ha^(-1))*** detailed edaphoclimatic data produce highly precise predictions and a good mechanistic understanding,the study suggested that local climatic data could also be *** study showed that PULSE modelling in combination with coarse level of edaphic and local climate data resulted in reasonably precise tree growth prediction and minimal bias.

关键词： Growth-yield model Populus species Hybrid ecophysiological modelling Deciduous trees Phenology

Responses of yield, root traits and their plasticity to the nitrogen environment in nitrogen-efficient cultivars of drip-irrigated rice

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Journal of Integrative Agriculture 2025年第2期24卷 480-496页

作者： Qingyun Tang Guodong Wang Lei Zhao Zhiwen Song Yuxiang Li key laboratory of Oasis Ecological Agriculture Shihezi University/Xinjiang Production and Construction Corps Northwest Oasis Water-saving Agriculture key laboratory Ministry of Agriculture and Rural Affairs/Key Laboratory of Efficient Utilization of Water and Fertilizer of Xinjiang Production and Construction Corps

The responses of drip-irrigated rice physiological traits to water and fertilizers have been widely ***,the responses of yield,root traits and their plasticity to the nitrogen environment in different nitrogen-efficient cultivars are not fully *** experiment was conducted from 2020–2022 with a high nitrogen use efficiency （high-NUE） cultivar （T-43） and a low-NUE cultivar （LX-3）,and four nitrogen levels (0,150,300,and 450 kg ha–1) under drip irrigation in large *** aim was to study the relationships between root morphology,conformation,biomass,and endogenous hormone contents,yield and *** results showed three main points:1) Under the same N application rate,compared with LX-3,the yield,N partial factor productivity （PFP）,fine root length density （FRLD）,shoot dry weight（SDW）,root indole-3-acetic acid （IAA）,and root zeatin and zeatin riboside （Z+ZR） of T-43 were significantly greater by11.4–18.9,11.3–13.5,11.6–15.7,9.9–31.1,6.1–48.1,and 22.8–73.6%,respectively,while the root–shoot ratio （RSR）and root abscisic acid （ABA） were significantly lower （P<0.05）;2) nitrogen treatment significantly increased the rice root morphological indexes and endogenous hormone contents （P<0.05）.Compared to N0,the yield,RLD,surface area density （SAD）,root volume density （RVD）,and root endogenous hormones （IAA,Z+ZR） were significantly increased in both cultivars under N2 by 61.6–71.6,64.2–74.0,69.9–105.6,6.67–9.91,54.0–67.8,and 51.4–58.9%,*** with N3,the PFP and N agronomic efficiency （NAE） of nitrogen fertilizer under N2 increased by 52.3–62.4 and39.2–63.0%,respectively;3) the responses of root trait plasticity to the N environment significantly differed between the cultivars （P<0.05）.Compared with LX-3,T-43 showed a longer root length and larger specific surface area,which is a strategy for adapting to changes in the nutrient *** the rice cultivar with high-NUE,the RSR was optimized by increasing the FRLD,root distribution in u

关键词： drip irrigation rice nitrogen environment root traits plasticity yield nitrogen use efficiency

PrDA1-1 and its interacting proteins PrTCP1/PrTCP9 in flare tree peony affect yield by regulating seed weight and number

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Journal of Integrative Agriculture 2025年第02期24卷 610-622页

作者： Chunyan He Fangyun Cheng state key laboratory of efficient production of forest Resources Beijing Forestry University National Engineering Research Center for Floriculture Beijing Forestry University Peony International Institute Beijing Forestry University School of Landscape Architecture Beijing Forestry University

Tree peony is an emerging woody oilseed crop that has the potential to help meet the growing demand for edible oil and biofuel, and breeding high-yield varieties is the key to increasing production. The DA1 gene regulates seed weight and number and effectively improves crop yield, although its function in tree peonies has not yet been reported. In this study, three PrDA1 genes were first identified in the whole genome of ‘Jing Hong' flare tree peony(Paeonia rockii). PrDA1-1 is homologous to AtDA1 and contains three types of conserved structural domains: UIM(ubiquitin-interacting motif), LIM(Lin11, Isl-1, and Mec-3), and DA-like. PrDA1-1 was strongly expressed during both the early and late stages of seed development, and its constitutive expression in Arabidopsis reduced seed number but increased seed weight, which ultimately led to a reduction in yield. PrDA1-1 was found to interact with PrTCP1/PrTCP9 in yeast and plants, and the constitutive expression of PrTCP1/PrTCP9 in Arabidopsis increased seed weight and number, which resulted in higher yield. Since this study showed that PrDA1-1 and PrTCP1/PrTCP9 regulate seed weight and number to affect yield, these new genetic resources will help to improve the seed yield of tree peonies.

关键词： DA1 gene family PrTCP1/PrTCP9 Paeonia rockii seed traits

Selenate oxyanion-intercalated NiFeOOH for stable water oxidation via lattice oxygen oxidation mechanism

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Journal of Energy Chemistry 2025年第2期101卷 676-684页

作者： Yijie Zhang Weiyi Zhang Xiaowen Zhang Jinping Li Guang Liu Shanxi key laboratory of Gas Energy efficient and Clean Utilization College of Chemical Engineering and Technology Taiyuan University of Technology Shanxi Research Institute of Huai Rou laboratory

Transition metal-based compounds can serve as pre-catalysts to obtain genuine oxygen evolution reaction（OER） electrocatalysts in the form of oxyhydroxides through electrochemical ***,the role and existence form of leached oxygen anions are still ***,we selected iron selenite-wrapped hydrated nickel molybdate（denoted as NiMoO/FeSeO） as a pre-catalyst to study the oxyanion *** is surprising to find that SeO2-exists in the catalyst in the form of intercalation,which is different from previous studies that suggest that anions are doped with residual elements after electrochemical activation,or adsorbed on the catalyst *** experiment and theoretical calculations show that the existence of SeO42-intercalation effectively adjusts the electronic structure of NiFeOOH,promotes intramolecular electron transfer and O-O release,and thus lowers the reaction energy *** expected,the synthesized NiFeOOH-SeO only needs 202 and 285 mV to attain 100 and 1000 mA cm-2in 1 M ***,the anion exchange membrane water electrolyzer（AEMWE） consisting of NiFeOOHSeO anode and Pt/C cathode can reach 1 A cm-2at 1.70 V and no significant attenuation within 300 *** findings provide insights into the mechanism,by which the intercalated oxyanions enhance the OER performance of NiFeOOH,thereby facilitating large-scale hydrogen production through AEMWE.

关键词： Anion exchange membrane electrolyzer Industrial current densities Lattice oxygen oxidation Oxyanion intercalation Water splitting

Compiling molecular evidence from a tetraploid rose genome into a near-saturated map for the identification of pigment-related genes

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Horticultural Plant Journal 2025年第1期11卷 351-366页

作者： Bixuan Cheng Yanlin Sun Huihua Wan Kai Zhao Lidan Sun Le Luo Huitang Pan Qixiang Zhang Chao Yu state key laboratory of efficient production of forest Resources Beijing Key Laboratory of Ornamental Plants Germplasm Innovation and Molecular BreedingNational Engineering Research Center for FloricultureBeijing Laboratory of Urban and Rural Ecological Environment and School of Landscape ArchitectureBeijing Forestry UniversityBeijing 100083China key laboratoryof Beijing for Identification and Safety Evaluation of Chinese Medicine Instituteof Chinese Materia MedicaChina Academy of Chinese Medical SciencesBeijing 100700China College of Life Sciences Fujian Normal UniversityFuzhouFujian 350117China

With their high economic value and cultural significance,modern roses are one of the most important ornamental *** of their complicated genetic background and tetraploid nature,the creation of high-density genetic maps of roses has been a challenge that has slowed the pace of molecular breeding for modern *** current construction of tetraploid genetic maps based on existing diploid rose genomes could lead to inaccurate marker information and genotyping ***,we generated the first high-quality tetraploid genome of Rosa chinensis‘Yunzheng Xiawei.'Utilizing Illumina,PacBio,and Hi-C sequencing technologies,we assembled a genome of 858.59 Mb with *** of inheritance analysis using PolyOrigin indicated that modern roses show both quadrivalent and bivalent *** on this reference genome,high-density genetic maps were constructed using MSTmap with nearly saturated *** trait locus(QTL)analysis was conducted using WinQTLCart and R/qtl for flavonoids and carotenoids,and 11 QTL clusters were *** combining the genome annotation,phylogenetic analyses,and gene expression analyses,we were able to identify several key genes related to flavonoid and carotenoid *** study provides the basis for further genetic analyses of highly heterozygous tetraploid roses and could facilitate the progress of marker-assisted selection in modern roses.

关键词： Rosa Tetraploid genome Tetrasomic inheritance Genetic linkage map Flower color

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Beyond amplitude:Phase integration in bird vocalization recognition with MHAResNet

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Avian Research 2025年第1期16卷 119-128页

作者： Jiangjian Xie Zhulin Hao Chunhe Hu Changchun Zhang Junguo Zhang School of Technology Beijing Forestry UniversityBeijing100083China state key laboratory of efficient production of forest Resources Beijing Forestry UniversityBeijing100083China key laboratory of National forestry and Grassland Administration on forestry Equipment and Automation Beijing100083China Research Center for Biodiversity Intelligent Monitoring Beijing Forestry UniversityBeijing100083China

Bird vocalizations are pivotal for ecological monitoring,providing insights into biodiversity and ecosystem *** recognition methods often neglect phase information,resulting in incomplete feature *** this paper,we introduce a novel approach to bird vocalization recognition(BVR)that integrates both amplitude and phase information,leading to enhanced species *** propose MHARes Net,a deep learning(DL)model that employs residual blocks and a multi-head attention mechanism to capture salient features from logarithmic power(POW),Instantaneous Frequency(IF),and Group Delay(GD)extracted from bird *** on three bird vocalization datasets demonstrate our method's superior performance,achieving accuracy rates of 94%,98.9%,and 87.1%*** results indicate that our approach provides a more effective representation of bird vocalizations,outperforming existing *** integration of phase information in BVR is innovative and significantly advances the field of automatic bird monitoring technology,offering valuable tools for ecological research and conservation efforts.

关键词： Bird vocalization recognition Feature fusion Phase information Residual network

Advances in regional-scale crop growth and associated process modeling

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Science China Earth Sciences 2025年第3期68卷 653-668页

作者： Wenfeng LIU Yawei BAI Taisheng DU Mengxue LI Hong YANG Shichao CHEN Chuanbin LIANG Shaozhong KANG state key laboratory of efficient Utilization of Agricultural Water Resources China Agricultural University National Field Scientific Observation and Research Station on efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province Center for Agricultural Water Research in China China Agricultural University 2w2e Environmental Consulting GmbH

In the context of global change, ensuring national food security and achieving sustainable development of agricultural production systems have become major challenges worldwide. To address these issues, regional-scale crop growth and associated process(CROP-AP) models, with their robust simulation and predictive capabilities, have emerged as important tools for studying a wide range of issues relating to agricultural production at river basin, national, and even global scales. Here, we provide a systematic review of the advances of regional-scale CROP-AP models. First, regional-scale CROP-AP models are categorized based on model characteristics: statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The origin, development, principle, structure, and application of each model type are introduced. Then, the main functions of regional-scale CROP-AP models are critically reviewed from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and ***, the future development trends and research priorities of regional-scale CROP-AP models are explored from six key perspectives: model validation and calibration, the ability to simulate the coupling of crop physiology and human activities,enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence. This review aims to provide comprehensive references and insights for the further development and application of large-scale, high-precision CROP-AP models.

关键词： Regional scale Crop model Biophysical processes Model functions Global change

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Genomic selection for meat quality traits based on VIS/NIR spectral information

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Journal of Integrative Agriculture 2025年第1期24卷 235-245页

作者： Xi Tang Lei Xie Min Yan Longyun Li Tianxiong Yao Siyi Liu Wenwu Xu Shijun Xiao Nengshui Ding Zhiyan Zhang Lusheng Huang state key laboratory for Pig Genetic Improvement and production Technology Jiangxi Agricultural UniversityNanchang 330045China

The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target *** 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lo

关键词： VIS/NIR genomic selection GEBV machine learning pig meat quality

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