Effect of pruning intensity on soil moisture and water use efficiency in jujube(Ziziphus jujube Mill.) plantations in the hilly Loess Plateau Region, China

Jujube(Ziziphus jujube Mill.)is a traditional economic forest crop and is widely cultivated in hilly areas of the Loess Plateau,China.However,soil desiccation was discovered in jujube plantations.Pruning is recognized as a water-saving method that can reduces soil water consumption.In this study,we monitored the jujube plots with control(CK),light(C1),medium(C2)and high(C3)pruning intensities during the jujube growing period of 2012-2015 to explore the effect of pruning intensity on soil moisture and water use efficiency(WUE)of jujube plantations in the hilly Loess Plateau Region.The results showed that pruning is an effective method for soil water conservation in jujube plantations.Soil moisture increased with increasing pruning intensity during the jujube growing period of 2012-2015.C1,C2 and C3 pruning intensities increased soil water storage by 6.1-18.3,14.4-40.0 and 24.3-63.3 mm,respectively,compared to CK pruning intensity.Pruning promoted soil moisture infiltration to deeper soil layer.Soil moisture infiltrated to soil depths of 240,280 and>300 cm under C3 pruning intensity,220,260 and 260 cm under C2 pruning intensity,200,240 and 220 cm under C1 pruning intensity,and 180,200 and 160 cm under CK pruning intensity in 2013,2014 and 2015,respectively.Soil water deficit was alleviated by higher pruning intensity.In 2013-2015,soil water change was positive under C2(6.4 mm)and C3(26.8 mm)pruning intensities but negative under C1(-20.5 mm)and CK(-40.6 mm)pruning intensities.Moreover,pruning significantly improved fresh fruit yield and WUE of jujube plants.Fresh fruit yields were highest under C1 pruning intensity with the values of 6897.1-13,059.3 kg/hm^2,which were 2758.4-4712.8,385.7-1432.1 and 802.8-2331.5 kg/hm2 higher than those under CK,C2,and C3 pruning intensities during the jujube growing period of 2012-2015,respectively.However,C3 pruning intensity had the highest WUE values of 2.92-3.13 kg/m3,which were 1.6-2.0,1.1-1.2 and 1.0-1.1 times greater than those under CK,C1 and C2 pruning intensities,respectively.Therefore,C3 pruning intensity is recommended to jujube plantations for its economic and ecological benefits.These results provide an alternative strategy to mitigate soil desiccation in jujube plantations in the hilly Loess Plateau Region,which is critical for sustainable cultivation of economic forest trees in this region.

Interaction of Carbon Dioxide Enrichment and Soil Moisture on Photosynthesis, Transpiration, and Water Use Efficiency of Soybean

Soybean (Glycine max (L.) Merrill) is one of the most important oil and protein sources in the world. Interactive effect of elevated carbon dioxide (CO2) and soil water availability potentially impact future food security of the world under climate change. A rhizotron growth chamber experiment was conducted to study soil moisture interactions with elevated CO2 on gaseous exchange parameters of soybean under two CO2 concentrations (380 and 800 μmol·mol-1) with three soil moisture levels. Elevated CO2 decreased photosynthetic rate (11.1% and 10.8%), stomatal conductance (40.5% and 36.0%), intercellular CO2 concentration (16.68% and 12.28%), relative intercellular CO2 concentration (17.4% and 11.2%), and transpiration rate (43.6% and 39%) at 42 and 47 DAP. This down-regulation of photosynthesis was probably caused by low leaf nitrogen content and decrease in uptake of nutrients due to decrease in stomatal conductance and transpiration rate. Water use efficiency (WUE) increased under elevated CO2 because increase in total dry weight of plant was greater than that of water use under high CO2 conditions. Plants under normal and high soil moisture levels had significantly higher photosynthetic rate (7% to 16%) favored by optimum soil moisture content and high specific water content of soybean plants. Total dry matter production was significantly high when plants grown under elevated CO2 with normal (74.3% to 137.3%) soil moisture level. Photosynthetic rate was significantly and positively correlated with leaf conductance and intercellular CO2 concentration but WUE was significantly negatively correlated with leaf conductance, intercellular CO2 concentration and transpiration rate. However, the effect of high CO2 on plants depends on availability of nutrients and soil moisture for positive feedback from CO2 enrichment.

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

Time-lagged Effects of the Spring Atmospheric Heat Source over the Tibetan Plateau on Summer Precipitation in Northeast China during 1961–2020:Role of Soil Moisture

The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in Northeast China(NEC)remains unknown.The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study.Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation,and higher soil moisture in the Yellow River Valley-North China region(YRVNC)acts as a bridge.During spring,the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC.Thus,soil moisture increases,which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat.Owing to the memory of soil moisture,the lower spring sensible heat over the YRVNC can last until mid-summer,decrease the land–sea thermal contrast,and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific.This modulates the East Asia–Pacific teleconnection pattern,which leads to a cyclonic anomaly and excessive summer precipitation over NEC.

Understanding Bridging Sites and Accelerating Quantum Efficiency for Photocatalytic CO_(2) Reduction

We report a novel double-shelled nanoboxes photocatalyst architecture with tailored interfaces that accelerate quantum efficiency for photocatalytic CO_(2) reduction reaction(CO_(2)RR)via Mo–S bridging bonds sites in S_(v)–In_(2)S_(3)@2H–MoTe_(2).The X-ray absorption near-edge structure shows that the formation of S_(v)–In_(2)S_(3)@2H–MoTe_(2) adjusts the coordination environment via interface engineering and forms Mo–S polarized sites at the interface.The interfacial dynamics and catalytic behavior are clearly revealed by ultrafast femtosecond transient absorption,time-resolved,and in situ diffuse reflectance–Infrared Fourier transform spectroscopy.A tunable electronic structure through steric interaction of Mo–S bridging bonds induces a 1.7-fold enhancement in S_(v)–In_(2)S_(3)@2H–MoTe_(2)(5)photogenerated carrier concentration relative to pristine S_(v)–In_(2)S_(3).Benefiting from lower carrier transport activation energy,an internal quantum efficiency of 94.01%at 380 nm was used for photocatalytic CO_(2)RR.This study proposes a new strategy to design photocatalyst through bridging sites to adjust the selectivity of photocatalytic CO_(2)RR.

Enhancing I^(0)/I^(-)Conversion Efficiency by Starch Confinement in Zinc-lodine Battery

The redox couple of I^(0)/I^(-)in aqueous rechargeable iodine–zinc(I^(2)-Zn)batteries is a promising energy storage resource since it is safe and cost-effective,and provides steady output voltage.However,the cycle life and efficiency of these batteries remain unsatisfactory due to the uncontrolled shuttling of polyiodide(I_(3)^(-)and I_(5)^(-))and side reactions on the Zn anode.Starch is a very low-cost and widely sourced food used daily around the world.“Starch turns blue when it encounters iodine”is a classic chemical reaction,which results from the unique structure of the helix starch molecule–iodine complex.Inspired by this,we employ starch to confine the shuttling of polyiodide,and thus,the I^(0)/I^(-)conversion efficiency of an I^(2)-Zn battery is clearly enhanced.According to the detailed characterizations and theoretical DFT calculation results,the enhancement of I^(0)/I^(-)conversion efficiency is mainly originated from the strong bonding between the charged products of I_(3)^(-)and I_(5)^(-)and the rich hydroxyl groups in starch.This work provides inspiration for the rational design of high-performance and low-cost I^(2)-Zn in AZIBs.

Microscopic characteristics of tight sandstone reservoirs and their effects on the imbibition efficiency of fracturing fluids:A case study of the Linxing area,Ordos Basin

The Linxing area within the Ordos Basin exhibits pronounced reservoir heterogeneity and intricate micro-pore structures,rendering it susceptible to water-blocking damage during imbibition extraction.This study delved into the traits of tight sandstone reservoirs in the 8th member of the Shihezi Formation(also referred to as the He 8 Member)in the study area,as well as their effects on fracturing fluid imbibition.Utilizing experimental techniques such as nuclear magnetic resonance(NMR),high-pressure mercury intrusion(HPMI),and gas adsorption,this study elucidated the reservoir characteristics and examined the factors affecting the imbibition through imbibition experiments.The findings reveal that:①The reservoir,with average porosity of 8.40%and average permeability of 0.642×10^(-3)μm^(2),consists principally of quartz,feldspar,and lithic fragments,with feldspathic litharenite serving as the primary rock type and illite as the chief clay mineral;②Nano-scale micro-pores and throats dominate the reservoir,with dissolution pores and intercrystalline pores serving as predominant pore types,exhibiting relatively high pore connectivity;③Imbibition efficiency is influenced by petrophysical properties,clay mineral content,and microscopic pore structure.Due to the heterogeneity of the tight sandstone reservoir,microscopic factors have a more significant impact on the imbibition efficiency of fracturing fluids;④A comparative analysis shows that average pore size correlates most strongly with imbibition efficiency,followed by petrophysical properties and clay mineral content.In contrast,the pore type has minimal impact.Micropores are vital in the imbibition process,while meso-pores and macro-pores offer primary spaces for imbibition.This study offers theoretical insights and guidance for enhancing the post-fracturing production of tight sandstone reservoirs by examining the effects of these factors on the imbibition efficiency of fracturing fluids in tight sandstones.

EFFICIENCY AND COMFORT THROUGH DEEP ENERGY RETROFITS: BALANCING ENERGY AND MOISTURE MANAGEMENT

Homes that survived to be called“historic”did so because they worked;that is,they delivered a level of performance that met the owner’s expectations and tolerance level without catastrophic damage to the home,pocketbook,or surrounding environment.Home performance expectations have changed and now include a desire to use less energy while at the same time realizing a level of comfort that includes air conditioning and constant temperatures in all rooms.In order to meet these performance expectations,old homes often require some“re-engineering.”Increasing insulation will advance energy efficiency goals,reduce costs,and make a home more sustainable but by itself is insufficient,and,often,it can also upset the moisture balance resulting in unexpected mold and sick building syndrome.Improvement in moisture management design is a critically important consideration whenever energy efficiency is increased;however,many projects fail to address moisture adequately.This article will walk through the process of insulating and air sealing a house(two very different activities,sometimes combined,sometimes not),and shed particular light on how different approaches encourage or discourage moisture problems.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Erratum to:Unraveling engineering disturbance effects on deformation in red-bed mudstone railway cuttings:incorporating crack-facilitated moisture diffusion

Erratum to:J.Mt.Sci.(2024)21(5):1663-1682 https://doi.org/10.1007/s11629-023-8561-0 During the production process,the first author’s name was wrongly written as“Rang Huang”in the metadata.The correct name for the first author is“Kang Huang”.The first author’s name in the fulltext pdf is correct.

Magneto-Photo-Thermoelastic Excitation Rotating Semiconductor Medium Based on Moisture Diffusivity

In this research,we focus on the free-surface deformation of a one-dimensional elastic semiconductor medium as a function of magnetic field and moisture diffusivity.The problem aims to analyze the interconnection between plasma and moisture diffusivity processes,as well as thermo-elastic waves.The study examines the photothermoelasticity transport process while considering the impact of moisture diffusivity.By employing Laplace’s transformation technique,we derive the governing equations of the photo-thermo-elastic medium.These equations include the equations for carrier density,elastic waves,moisture transport,heat conduction,and constitutive relationships.Mechanical stresses,thermal conditions,and plasma boundary conditions are used to calculate the fundamental physical parameters in the Laplace domain.By employing numerical techniques,the Laplace transform is inverted to get complete time-domain solutions for the primary physical domains under study.Referencemoisture,thermoelastic,and thermoelectric characteristics are employed in conjunction with a graphical analysis that takes into consideration the effects of applied forces on displacement,moisture concentration,carrier density,stress due to forces,and temperature distribution.

Unraveling engineering disturbance effects on deformation in red-bed mudstone railway cuttings:incorporating crack-facilitated moisture diffusion

Red-bed mudstone, prevalent in southwest China, poses a formidable challenge due to its hydrophilic clay minerals, resulting in expansion, deformation, and cracking upon exposure to moisture. This study addresses uplift deformation disasters in high-speed railways by employing a moisture diffusion-deformation-fracture coupling model based on the finite-discrete element method(FDEM). The model integrates the influence of cracks on moisture diffusion. The investigation into various excavation depths reveals a direct correlation between depth and the formation of tensile cracks at the bottom of the railway cutting. These cracks expedite moisture migration, significantly impacting the temporal and spatial evolution of the moisture field. Additionally, crack expansion dominates hygroscopic deformation, with the lateral coordinate of the crack zone determining peak vertical displacement. Furthermore, key factors influencing deformation in railway cuttings, including the swelling factor and initial moisture content at the bottom of the cutting, are explored. The number of tensile and shear cracks increases with greater excavation depth, particularly concerning shear cracks. Higher swelling factors and initial moisture contents result in an increased total number of cracks, predominantly shear cracks. Numerical calculations provide valuable insights, offering a scientific foundation and directional guidance for the precise prevention, control, prediction, and comprehensive treatment of mudstone-related issues in high-speed railways.

Synergistic Impacts of Indian Ocean SST and Indo-China Peninsula Soil Moisture on the 2020 Record-breaking Mei-yu

The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.

Antecedent Precipitation Index to Estimate Soil Moisture and Correlate as a Triggering Process in the Occurrence of Landslides

Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.

Comparison of isotope-based linear and Bayesian mixing models in determining moisture recycling ratio

Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation,i.e.,the moisture recycling ratio,but various isotope-based models usually lead to different results,which affects the accuracy of local moisture recycling.In this study,a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio.Among the three vapor sources including advection,transpiration,and surface evaporation,the advection vapor usually played a dominant role,and the contribution of surface evaporation was less than that of transpiration.When the abnormal values were ignored,the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9%for transpiration,0.2%for surface evaporation,and–1.1%for advection,respectively,and the medians were 0.5%,0.2%,and–0.8%,respectively.The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied,and the contribution of advection was relatively larger.The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios.Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input,and it was important to accurately estimate the isotopes in precipitation vapor.Generally,the Bayesian mixing model should be recommended instead of a linear model.The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.

Differences in Precipitation and Related Wind Dynamics and Moisture and Heat Features in Separate Areas of the South China Sea before and after Summer Monsoon Onset

Using surface and balloon-sounding measurements, satellite retrievals, and ERA5 reanalysis during 2011–20, this study compares the precipitation and related wind dynamics, moisture and heat features in different areas of the South China Sea(SCS) before and after SCS summer monsoon onset(SCSSMO). The rainy sea around Dongsha(hereafter simply referred to as Dongsha) near the north coast, and the rainless sea around Xisha(hereafter simply referred to as Xisha) in the western SCS, are selected as two typical research subregions. It is found that Dongsha, rather than Xisha, has an earlier and greater increase in precipitation after SCSSMO under the combined effect of strong low-level southwesterly winds, coastal terrain blocking and lifting, and northern cold air. When the 950-h Pa southwesterly winds enhance and advance northward, accompanied by strengthened moisture flux, there is a strong convergence of wind and moisture in Dongsha due to a sudden deceleration and rear-end collision of wind by coastal terrain blocking. Moist and warm advection over Dongsha enhances early and deepens up to 200 h Pa in association with the strengthened upward motion after SCSSMO, thereby providing ample moisture and heat to form strong precipitation. However, when the 950-h Pa southwesterly winds weaken and retreat southward, Xisha is located in a wind-break area where strong convergence and upward motion centers move in. The vertical moistening and heating by advection in Xisha enhance later and appear far weaker compared to that in Dongsha, consistent with later and weaker precipitation.

Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent integration.The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and processing.However,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion terminals.Simultaneously,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart grid.In response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these issues.The scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT terminals.It then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy states.This comprehensive approach reduces the impact of subjective factors on trust measurements.Additionally,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious terminals.This,in turn,enhances the security and reliability of the smart grid environment.The effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation experiments.Notably,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

Effect of building energy efficiency standards on carbon emission efficiency in commercial buildings

The building sector plays a crucial role in the worldwide shift toward achieving net-zero emissions.Building energy efficiency standards(BEESs)are highly effective policies for reducing carbon emissions.Therefore,exploring the provincial variations in carbon emission efficiency(CEE)in the building sector and identifying the effect of BEESs on CEE is crucial.This study focuses on commercial buildings in China and applies a difference in differences model to evaluate the impact of BEESs on the CEE of commercial buildings.The slacks-based measure–data envelopment analysis model is employed to assess the CEE of commercial buildings in 30 Chinese provinces from 2000 to 2019.Furthermore,heterogeneous tests are used to explore how climate characteristics and economic conditions affect the efficiency of BEESs.The results indicate that BEESs positively influence the CEE of commercial buildings.Specifically,a 1%increase in the intensity of BEESs causes a 0.1484%increase in the CEE of commercial buildings.Moreover,the impact of BEESs is particularly pronounced in the southern and western provinces.This study provides valuable scientific evidence for governments to enhance BEESs implementation.

Assessing the yield difference of double-cropping rice in South China driven by radiation use efficiency

Double-cropping rice in South China continues to break the total yield record,but the yield potential of singlecropping rice is not being realized.Radiation use efficiency(RUE)has been singled out as an important determinant of grain yield in many cereal species.However,there is no information on whether the yield gaps in doublecropping rice involve differences in RUE.Field experiments were performed over two years to evaluate the effects of intercepted radiation(IP)and RUE on the above-ground biomass production,crop growth rate(CGR),and harvest index(HI),in four representative rice varieties,i.e.,Xiangyaxiangzhan(XYXZ),Meixiangzhan 2(MXZ2),Nanjingxiangzhan(NJXZ),and Ruanhuayoujinsi(RHYJS),during the early and late seasons of rice cultivation in South China.The results revealed that grain yield in the early season was 8.2%higher than in the late season.The yield advantage in the early season was primarily due to higher spikelets per panicle and above-ground biomass resulting from a higher RUE.The spikelets per panicle in the early season were 6.5,8.3,6.9,and 8.5%higher in XYXZ,MXZ2,NJXZ,and RHYJS,respectively,than in the late season.The higher early season grain yield was more closely related to RUE in the middle tillering stage(R^(2)=0.34),panicle initiation(R^(2)=0.16),and maturation stage(R^(2)=0.28),and the intercepted photosynthetically active radiation(IPAR)in the maturation stage(R^(2)=0.28),while the late season grain yield was more dependent on IPAR in the middle tillering stage(R^(2)=0.31)and IPAR at panicle initiation(R^(2)=0.23).The results of this study conclusively show that higher RUE contributes to the yield progress of early season rice,while the yield improvement of late season rice is attributed to higher radiation during the early reproductive stage.Rationally allocating the RUE of double-cropping rice with high RUE varieties or adjustments of the sowing period merits further study.

Effect of antioxidants on the efficiency of jet milling and the powder characteristics of Sm2Co17 permanent magnets

This study investigated the effect of antioxidants on the grinding efficiency,magnetic powder characteristics,microstructure,and magnetic properties of 2:17 type SmCo permanent magnet materials.The results show that adding antioxidants helps improve the dispersion among magnetic powders,leading to a 33.3%decrease in jet milling time and a 15.8%increase in magnet powder production yield.Additionally,adding antioxidants enhances the oxidation resistance of the magnetic powders.After being stored in a constant temperature air environment at 25C for 48 h,the O content in the powder decreased by 33%compared to samples without antioxidants.While in the magnet body,the O content decreased from 0.21 wt.%to 0.14 wt.%,which helps increase the effective Sm content and domain wall pinning uniformity in the magnet.Excellent magnetic properties were obtained in the magnet with added antioxidants:B_(r)=11.6 kGs,SF=79.6%,H_(cj)=16.8 kOe,and(BH)_(max)=32.5 MGOe.