Combining slow-release fertilizer and plastic film mulching reduced the carbon footprint and enhanced maize yield on the Loess Plateau.

Agricultural practices significantly contribute to greenhouse gas (GHG) emissions, necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production. Plastic film mulching is commonly used in the Loess Plateau region. Incorporating slow-release fertilizers as a replacement for urea within this practice can reduce nitrogen losses and enhance crop productivity. Combining these techniques represents a novel agricultural approach in semi-arid areas. However, the impact of this integration on soil carbon storage (SOCS), carbon footprint (CF), and economic benefits has received limited research attention. Therefore, we conducted an eight-year study (2015-2022) in the semi-arid northwestern region to quantify the effects of four treatments [urea supplied without plastic film mulching (CK-U), slow-release fertilizer supplied without plastic film mulching (CK-S), urea supplied with plastic film mulching (PM-U), and slow-release fertilizer supplied with plastic film mulching (PM-S)] on soil fertility, economic and environmental benefits. The results revealed that nitrogen fertilizer was the primary contributor to total GHG emissions (≥71.97%). Compared to other treatments, PM-S increased average grain yield by 12.01%-37.89%, water use efficiency by 9.19%-23.33%, nitrogen accumulation by 27.07%-66.19%, and net return by 6.21%-29.57%. Furthermore, PM-S decreased CF by 12.87%-44.31% and CF per net return by 14.25%-41.16%. After eight years, PM-S increased SOCS (0-40 cm) by 2.46%, while PM-U decreased it by 7.09%. These findings highlight the positive effects of PM-S on surface soil fertility, economic gains, and environmental benefits in spring maize production on the Loess Plateau, underscoring its potential for widespread adoption and application.

Plant diversity decreases greenhouse gas emissions by increasing soil and plant carbon storage in terrestrial ecosystems.

The decline in global plant diversity has raised concerns about its implications for carbon fixation and global greenhouse gas emissions (GGE), including carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4). Therefore, we conducted a comprehensive meta-analysis of 2103 paired observations, examining GGE, soil organic carbon (SOC) and plant carbon in plant mixtures and monocultures. Our findings indicate that plant mixtures decrease soil N2O emissions by 21.4% compared to monocultures. No significant differences occurred between mixtures and monocultures for soil CO2 emissions, CH4 emissions or CH4 uptake. Plant mixtures exhibit higher SOC and plant carbon storage than monocultures. After 10 years of vegetation development, a 40% reduction in species richness decreases SOC content and plant carbon storage by 12.3% and 58.7% respectively. These findings offer insights into the intricate connections between plant diversity, soil and plant carbon storage and GGE-a critical but previously unexamined aspect of biodiversity-ecosystem functioning.

Straw returning and nitrogen reduction: Strategies for sustainable maize production in the dryland.

Implementing continue straw returning practices and optimizing nitrogen application can mitigate nitrogen losses and enhance nitrogen use efficiency (NUE) in dryland. 15N-labeled technique offers a robust approach for tracking fertilizer nitrogen fate and assessing nitrogen use efficiency. Based on the continue (>6 yr) experiment, we conducted a two-year experiment (2020 and 2021) to evaluate the effects of straw returning and nitrogen management under plastic film mulching on 15N recovery rates, N2O emissions and maize yield with three treatments: no straw returning with 225 kg N·ha-1 under plastic film mulching (RP-N225), straw returning with 225 kg N·ha-1 under plastic film mulching (RPS-N225), and straw returning with 20% nitrogen reduction (180 kg N·ha-1) under plastic film mulching (RPS-N180). After six years, both continue straw returning with plastic film mulching increased uptake of fertilizer nitrogen, had higher 15N recovery rates than RP-N225, leading to increased 15N accumulation in grain and aboveground biomass, ultimately enhancing yield. The RPS-N225 treatment exhibited the highest spring maize yield and nitrogen harvest index. The RPS-N180 treatment significantly increased maize yield more than RP-N225 and had the highest NUE, partial factor productivity of nitrogen fertilizer, and nitrogen uptake efficiency, with improvements ranging from 1.7 to 2.4%, 19.3-29.6%, and 17.3-27.5%, respectively, compared to the other treatments. Moreover, RPS-N225 resulted in significantly higher cumulative N2O emissions and yield-scaled N2O emissions than the other treatments, whereas the RPS-N180 treatment significantly decreased yield-scaled N2O emissions compared to RP-N225. Hence, combining continue straw returning with appropriate nitrogen reduction can effectively increase maize yield and yield-scaled N2O emissions. By offering insights into optimizing nitrogen fertilizer management after continue maize straw return, this study is contributed to widespread adoption of straw return practices and sustainable agricultural development in semi-arid areas.

Dissecting PM sensor capabilities: A combined experimental and theoretical study on particle sizing and physicochemical properties.

Recent advancements in particulate matter (PM) optical measurement technology have enhanced the characterization of particle size distributions (PSDs) across various temporal and spatial scales, offering a more detailed analysis than traditional PM mass concentration monitoring. This study employs field experiments, laboratory tests, and model simulations to evaluate the influence of physicochemical characteristics of particulate matter (PM) on the performance of a compact, multi-channel PM sizing sensor. The sensor is integrated within a mini air station (MAS) designed to detect particles across 52 channels. The field experiments highlighted the sensor's ability to track hygroscopicity parameter κ-values across particle sizes, noting an increasing trend with particle size. The sensor's capability in identifying the size and mass concentration of different PM types, including ammonium nitrate, sodium chloride, smoke, incense, and silica dust particles, was assessed through laboratory tests. Laboratory comparisons with the Aerodynamic Particle Sizer (APS) showed high consistency (R2 > 0.96) for various PM sources, supported by Kolmogorov-Smirnov tests confirming the sensor's capability to match APSsize distributions. Model simulations further elucidated the influence of particle refractive index and size distributions on sensor performance, leading to optimized calibrant selection and application-specific recommendations. These comprehensive evaluations underscore the critical interplay between the chemical composition and physical properties of PM, significantly advancing the application and reliability of optical PM sensors in environmental monitoring.

Evaluating methods for marine fuel sulfur content using microsensor sniffing systems on ocean-going vessels.

Establishing emission control areas (ECAs) can effectively reduce air pollution from marine emissions, making efficient monitoring of the fuel sulfur content (FSC) of ocean-going vessels (OGVs) key to ECA policy enforcement. Various FSC detection approaches, including oil sample analysis, sniffing method, and optical remote sensing, have been proposed, each with its benefits and drawbacks. Among these, the sniffing method appears promising but requires further improvement in field operation protocol and data analysis processes. This study aims to develop a comprehensive methodology, including sensor calibration, field operations, and data analysis, to enhance the performance of an Unmanned Aerial Vehicle (UAV)-based Microsensor Sniffing System (MSS) for real-time FSC monitoring. Hong Kong has a cap of 0.5 % m/m FSC for OGVs, and hence Hong Kong waters served as the "real-world" monitoring location to evaluate the MSS system through land-based and sea-based measurements. Three different FSC calculation methods were employed and verified against bunker delivery note (BDN) data through blind testing. Results confirm that the MSS is effective in field settings, though it has an underestimation tendency, demonstrating an absolute error of 0.06 % m/m, 0.11 % m/m, and 0.10 % m/m for the Crest, Slope, and Area methods, respectively, compared to BDN data. However, high errors were possible with low CO2 and SO2 peak heights, and single-peak samples compared to multi-peak samples. Over 16 successful trips, the FSC of 125 valid OGVs (Mean FSC = 0.39 % m/m) exhibited a lognormal distribution pattern, with the distribution tail approaching the 0.5 % m/m regulatory cap. This investigation highlights the potential of a UAV-based MSS for monitoring and enforcing FSC regulations within ECAs, providing a systematic protocol to guide future research direction and enforcement practices.

Enhancing intercropping sustainability: Manipulating soybean rhizosphere microbiome through cropping patterns.

Understanding the responses of soybean rhizosphere and functional microbiomes in intercropping scenarios holds promise for optimizing nitrogen utilization in legume-based intercropping systems. This study investigated three cropping layouts under film mulching: sole soybean (S), soybean-maize intercropping in one row (IS), and soybean-maize intercropping in two rows (IIS), each subjected to two nitrogen levels: 110 kg N ha-1 (N110) and 180 kg N ha-1 (N180). Our findings reveal that cropping patterns alter bacterial and nifh communities, with approximately 5 % of soybean rhizosphere bacterial amplicon sequence variants (ASVs) and 42 % of rhizosphere nifh ASVs exhibiting altered abundances (termed sensitive ASVs). Root traits and soil properties shape these communities, with root traits exerting greater influence. Sensitive ASVs drive microbial co-occurrence networks and deterministic processes, predicting 85 % of yield variance and 78 % of partial factor productivity of nitrogen, respectively. These alterations impact bacterial and nifh diversity, complexity, stability, and deterministic processes in legume-based intercropping systems, enhancing performance in terms of yield, nitrogen utilization efficiency, land equivalent ratio, root nodule count, and nodule dry weight under IIS patterns with N110 compared to other treatments. Our findings underscore the importance of field management practices in shaping rhizosphere-sensitive ASVs, thereby altering microbial functions and ultimately impacting the productivity of legume-based intercropping systems. This mechanistic understanding of soybean rhizosphere microbial responses to intercropping patterns offers insights for sustainable intercropping enhancements through microbial manipulation.

How Does the Environment Affect Wheat Yield and Protein Content Response to Drought? A Meta-Analysis.

Wheat (Triticum aestivum L.) is one of the most significant cereal crops grown in the semi-arid and temperate regions of the world, but few studies comprehensively explore how the environment affects wheat yield and protein content response to drought by means of meta-analysis. Therefore, we collected data about grain yield (GY), grain protein yield (GPY), grain protein content (GPC), and grain nitrogen content (GNC), and conducted a meta-analysis on 48 previously published data sets that originate from 15 countries. Our results showed that drought significantly decreased GY and GPY by 57.32 and 46.04%, but significantly increased GPC and GNC by 9.38 and 9.27%, respectively. The responses of wheat GY and GNC to drought were mainly related to the drought type, while the GPY was mainly related to the precipitation. The yield reduction due to continuous drought stress (CD, 83.60%) was significantly greater than that of terminal drought stress (TD, 26.43%). The relationship between the precipitation and GPY increased in accordance with linear functions, and this negative drought effect was completely eliminated when the precipitation was more than 513 mm. Sandy soils and high nitrogen application level significantly mitigated the negative effects of drought, but was not the main factor affecting the drought response of wheat. Compared with spring wheat, the drought resistance effect of winter wheat was more obvious. Evaluation of these models can improve our quantitative understanding of drought on wheat yield and food security, minimizing the negative impact of drought on crop production.

Decreased carbon footprint and increased grain yield under ridge-furrow plastic film mulch with ditch-buried straw returning: A sustainable option for spring maize production in China.

Ditch-buried straw returning with ridge-furrow plastic film mulch (RP+S) is a novel tillage measure in semiarid regions, but it is unclear whether RP+S can increase maize yield while reducing the carbon footprint (CF). Therefore, a six-year continuous experiment was conducted from 2016 to 2021 to quantify the effect of four straw returning and film mulching measures [conventional flat cultivation (CK), conventional flat cultivation with ditch-buried straw returning (CK+S), ridge-furrow plastic film mulch (RP), and RP+S] on soil organic carbon sequestration (SOCS), greenhouse gas (GHG) emissions, CF, and economic benefits. Straw returning and film mulching measures significantly increased total GHG emissions across the six seasons. For all treatments, nitrogen fertilizer was the most important source of GHG emissions (≥73%), followed by diesel (8-11%) and plastic film (8%, RP and RP+S only). RP+S significantly increased yield and partial factor productivity of nitrogen fertilizer by 8.7-59.1%, and net economic benefit by 7.37-57.76%, but decreased CF by 34-61% and CF per net return by 33-61% relative to the other treatments. RP+S had the highest GHG emissions, increasing by 6.11-16.47% relative to the other treatments. However, compared with the initial 0-40 cm SOCS in 2016, RP+S had the highest carbon sequestration rate (678.17 kg·ha-1·yr-1), increasing by 2.29% after six years, followed by CK+S (1.78%), CK (0.89%), and RP (-0.49%). Thus, RP+S had the lowest CF and CF per net return in four treatments. This comprehensive analysis of agronomic and environmental benefits revealed that RP+S is a high-yielding, economically and environmentally friendly measure in semiarid areas.

The evaluation and optimization of calibration methods for low-cost particulate matter sensors: Inter-comparison between fixed and mobile methods.

With the development of the air pollution control, the low-cost sensors are widely used in air quality monitoring, while the data quality of these sensors is always the most concern for users. In this study, data from nine air monitoring stations with standard PM instruments were used as reference and compared with the data of mobile and fixed PM sensors in Jinan, the capital city of Shandong Province, China. Data quality of PM sensors was checked by the cross-comparison among standard method, fixed and mobile sensors. And the impacts of relative humidity and size distribution (PM2.5/PM10) on the performance of PM sensors were evaluated as well. To optimize the calibration method for both fixed and mobile PM sensors, a two-step model was designed, in which the RH and PM2.5/PM10 ratio were both used as input parameters. We firstly calibrated the sensors with five independent models, and then all the calibrated data were linearly fitted by the LR-final model. In comparison with standard instruments, the LR-final model increased the R2 values of the PM2.5 and PM10 measured by fixed sensors from 0.89 and 0.79 to 0.98 and 0.97, respectively. The R2 values of PM2.5 and PM10 measured by the mobile sensors both increased to 0.99 from 0.79 and 0.62. Overall, the two-step calibration model appeared to be a promising approach to solve the poor performance of low-cost sensors.

The Effect of Grain Position on Genetic Improvement of Grain Number and Thousand Grain Weight in Winter Wheat in North China.

Genetic improvements have significantly contributed to wheat production. Five wheat cultivars-widely grown in north China in the 1950s, 1990s, or 2010s-were grown in field experiments conducted in the 2014-2015 and 2015-2016 growing seasons. This study evaluated the genetic progress in wheat grain yield and its related traits in north China and explored how breeding and selection have influenced grain numbers and weights within spikelets in the past 60 years. The results showed that the significant increases in grain yield in the past 60 years were mainly due to increases in grain number per spike and grain weight, while spike number per m2 has not changed significantly. Improvements in thousand grain weight (TGW) from the 1950s to 2010s have occurred at four grain positions (G1 to G4). The relative contribution of G4 to TGW increased over time, but was much less than the contributions of G1, G2, and G3. Indeed, the average grain weight at G4 was much less than that of 1000 grains. The increase in grain number per spike since the 1950s was mainly due to an increase in grain number at G1, G2 and G3, with the relative contribution of grain position to grain number being G1 > G2 > G3 > G4. Dwarfing genes increased grain number per spike and grain number at G3 and G4, but not TGW. In future, yields could be boosted by enhancing grain weight at G4 and grain number at G3 and G4, while maintaining those at G1 and G2.

Human eye-inspired soft optoelectronic device using high-density MoS2-graphene curved image sensor array.

Soft bioelectronic devices provide new opportunities for next-generation implantable devices owing to their soft mechanical nature that leads to minimal tissue damages and immune responses. However, a soft form of the implantable optoelectronic device for optical sensing and retinal stimulation has not been developed yet because of the bulkiness and rigidity of conventional imaging modules and their composing materials. Here, we describe a high-density and hemispherically curved image sensor array that leverages the atomically thin MoS2-graphene heterostructure and strain-releasing device designs. The hemispherically curved image sensor array exhibits infrared blindness and successfully acquires pixelated optical signals. We corroborate the validity of the proposed soft materials and ultrathin device designs through theoretical modeling and finite element analysis. Then, we propose the ultrathin hemispherically curved image sensor array as a promising imaging element in the soft retinal implant. The CurvIS array is applied as a human eye-inspired soft implantable optoelectronic device that can detect optical signals and apply programmed electrical stimulation to optic nerves with minimum mechanical side effects to the retina.

Changes in Rice Grain Quality of Indica and Japonica Type Varieties Released in China from 2000 to 2014.

China is the first country to use heterosis successfully for commercial rice production. This study compared the main quality characteristics (head rice rate, chalky rice rate, chalkiness degree, gel consistency, amylose content, and length-to-width ratio) of 635 rice varieties (not including upland and glutinous rice) released from 2000 to 2014 to establish the quality status and offer suggestions for future rice breeding for grain quality in China. In the past 15 years, grain quality in japonica rice and indica hybrid rice has improved. In japonica rice, inbred varieties have increased head rice rates and decreased chalkiness degree over time, while hybrid rice varieties have decreased chalky rice rates and chalkiness degree. In indica hybrid rice, the chalkiness degree and amylose contents have decreased and gel consistency has increased. Improvements in grain quality in indica inbred rice have been limited, with some increases in head rice rate and decreases in chalky rice rate and amylose content. From 2010 to 2014, the percentage of indica varieties meeting the Grade III national standard of rice quality for different quality traits was low, especially for chalky rice rate and chalkiness degree. Japonica varieties have more superior grain quality than indica rice in terms of higher head rice rates and gel consistency, lower chalky rice rates and chalkiness degree, and lower amylose contents, which may explain why the Chinese prefer japonica rice. The japonica rice varieties, both hybrid and inbred, had similar grain qualities, but this varied in indica rice with the hybrid varieties having higher grain quality than inbred varieties due to significantly better head rice rates and lower chalkiness degree. For better quality rice in future, the chalky rice rate and chalkiness degree should be improved in japonica rice along with most of the quality traits in indica rice.

Evolutionary agroecology: individual fitness and population yield in wheat (Triticum aestivum).

Although the importance of group selection in nature is highly controversial, several researchers have argued that plant breeding for agriculture should be based on group selection, because the goal in agriculture is to optimize population production, not individual fitness. A core hypothesis behind this claim is that crop genotypes with the highest individual fitness in a mixture of genotypes will not produce the highest population yield, because fitness is often increased by "selfish" behaviors, which reduce population performance. We tested this hypothesis by growing 35 cultivars of spring wheat (Triticum aestivum L.) in mixtures and monocultures, and analyzing the relationship between population yield in monoculture and individual yield in mixture. The relationship was unimodal, as predicted. The highest-yielding populations were from cultivars that had intermediate fitness, and these produced, on average, 35% higher yields than cultivars with the highest fitness. It is unlikely that plant breeding or genetic engineering can improve traits that natural selection has been optimizing for millions of years, but there is unutilized potential in traits that increase crop yield by decreasing individual fitness.

Effect of post-silking drought on nitrogen partitioning and gene expression patterns of glutamine synthetase and asparagine synthetase in two maize (Zea mays L.) varieties.

Glutamine synthetase (GS) and asparagine synthetase (AS) are proposed to have important function in plant nitrogen (N) remobilization, but their roles under drought stress are not well defined. In this study, the expression dynamics of GS and AS genes were analyzed in two maize varieties (ZD958 and NH101) in relation to post-silking drought stress induced nitrogen partitioning. ZD958 was a 'stay-green' variety with 5% nitrogen harvest index (NHI) lower than NH101. From silking to maturity, the amount of nitrogen remobilized from ear-leaves in ZD958 was evidently lower than NH101, and post-silking drought stress increased the nitrogen remobilization for both varieties. In ear-leaves, the expression of ZmGln1-3 was enhanced under drought stress. Three AS genes (ZmAS1, ZmAS2 and ZmAS3) were differentially regulated by post-silking drought treatment, of which the expression of ZmAS3 was stimulated at late stage of leaf senescence. In NH101, the expression level of ZmAS3 was markedly higher than that in ZD958. In developing grains, there were no significant differences in expression patterns of GS and AS genes between well water and drought treated plants. Drought stress altered maize N partitioning at the whole-plant level, and the up-regulation of GS and AS genes may contribute to the higher leaf nitrogen remobilization when exposed to drought treatments.

Specimen-specific vertebral fracture modeling: a feasibility study using the extended finite element method.

Osteoporotic vertebral body fractures are an increasing clinical problem among the aging population. Specimen-specific finite element models, derived from quantitative computed tomography (QCT), have the potential to more accurately predict failure loads in the vertebra. Additionally, the use of extended finite element modeling (X-FEM) allows for a detailed analysis of crack initiation and propagation in various materials. Our aim was to study the feasibility of QCT/X-FEM analysis to predict fracture properties of vertebral bodies. Three cadaveric specimens were obtained, and the L3 vertebrae were excised. The vertebrae were CT scanned to develop computational models and mechanically tested in compression to measure failure load, stiffness and to observe crack location. One vertebra was used for calibration of the material properties from experimental results and CT gray-scale values. The two additional specimens were used to assess the model prediction. The resulting QCT/X-FEM model of the specimen used for calibration had 2 and 4% errors in stiffness and failure load, respectively, compared with the experiment. The predicted failure loads of the additional two vertebrae were larger by about 41-44% when compared to the measured values, while the stiffness differed by 129 and 40%. The predicted fracture patterns matched fairly well with the visually observed experimental cracks. Our feasibility study indicated that the QCT/X-FEM method used to predict vertebral compression fractures is a promising tool to consider in future applications for improving vertebral fracture risk prediction in the elderly.

Uptake and distribution of stable strontium in 26 cultivars of three crop species: oats, wheat, and barley for their potential use in phytoremediation.

The main objective of this study was to investigate the accumulation and distribution of strontium (Sr) in 26 cultivars of wheat (Triticum aestivum L.), husk oat (Avena sativa L) and naked oat (Avena nuda), and barley (Hordeum vulgare L.) for their potential use in phytoremediation.Sr levels had no effect on the accumulation of shoot biomass at tillering or at maturity. Mean shoot Sr concentration of naked oat and barley at tillering was significantly (P<0.05) higher than that of wheat; Neimengkeyimai-1, a naked oat cultivar, had the highest Sr concentrations. At maturity, of four naked oat cultivars, Neimengkeyimai-1 had the highest Sr content at all measured Sr levels. Leaves had the highest Sr concentrations, followed by roots and straw, and then grain with the lowest. Mean enrichment coefficients from soil to shoots ranged from 0.521 to 1.343; the percentage of stable Sr removed from the soil to the shoots at harvest time was more than 1.4% after 120 days. Neimengkeyimai-1 could be used as a model for further research to find more effective cultivars; and naked oat plants could be selected for phytoremediation to clean up contaminated soil.

The effects of domestication on the scaling of below- vs. aboveground biomass in four selected wheat (Triticum; Poaceae) genotypes.

PREMISE OF THE STUDY: Theory and empirical studies have shown that, on average, belowground biomass (M(B)) scales one-to-one (isometrically) with aboveground biomass (M(A)) within and across plant species both at the individual and population level, i.e., M(B) ∝ M(A)(α=1), where α is the scaling exponent. However, little is known about how domestication affects this relationship. METHODS: To examine the effects of domestication, we investigated the root vs. shoot biomass relationship during the first 30 d of growth of four wheat genotypes: two older genotypes, MO4 (T. monococcum, a diploid) and DM31 (T. dicoccum, a tetraploid) and two more recent genotypes, DX24 and L8275 (T. aestivum, both hexaploids). RESULTS: Biomass allocation to roots scaled more or less isometrically with respect to shoot biomass allocation during the first 30 d of growth for both of the older genotypes, whereas shoot biomass allocation exceeded root allocation for the two more recent genotypes. This difference was attributable to the first 15 d of growth. Although root biomass allocation exceeded shoot biomass allocation during the first 15 d of growth for the two older genotypes, shoot biomass exceeded root biomass allocation during this critical phase of development for the two more recent genotypes. CONCLUSIONS: Based on a very limited sample of wheat genotypes, these results indicate that domestication has resulted in an increased biomass allocation to shoots compared to root biomass allocation. This shift possibly reflects artificial selection under agricultural conditions (for which water and nutrients are not limiting) favoring higher crop yields.