ABSTRACT
Quantitative evaluation of the effects of diverse greenhouse vegetable production systems (GVPS) on vegetable yield, soil water consumption, and nitrogen (N) fates could provide a scientific basis for identifying optimum water and fertilizer management practices for GVPS. This research was conducted from 2013 to 2015 in a greenhouse vegetable field in Quzhou County, North China. Three production systems were designed: conventional (CON), integrated (INT), and organic (ORG) systems. The WHCNS-Veg model was employed for simulating vegetable growth, water dynamics, and fates of N, as well as water and N use efficiencies (WUE and NUE) for four continuous growing seasons. The simulation results revealed that nitrate leaching and gaseous N emissions constituted the predominant N loss within GVPS, which separately accounted for 11.5-59.4% and 6.0-21.1% of the N outputs. The order of vegetable yield, N uptake, WUE, and NUE under different production systems was ORG > INT > CON, while the order of nitrate leaching and gaseous N loss was CON > INT > ORG. Compared to CON, ORG exhibited a significant increase in yield, N uptake, WUE, and NUE by 24.6%, 24.2%, 26.1%, and 89.7%, respectively, alongside notable reductions in nitrate leaching and gaseous N loss by 67.7% and 63.2%, respectively. The ORG system should be recommended to local farmers.
ABSTRACT
Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 $$ 13.2\pm 1.16 $$ Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 ± 0.02 $$ 0.39\pm 0.02 $$ Tg N2 O-N year-1 and 0.21 ± 0.01 $$ 0.21\pm 0.01 $$ Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 $$ 122.3\pm 11.46 $$ Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.
Subject(s)
Greenhouse Gases , Soil , Carbon Dioxide/analysis , Ecosystem , Carbon , Agriculture , Nitrous Oxide/analysis , Methane/analysis , Crops, Agricultural , Greenhouse EffectABSTRACT
The ground cover rice production system (GCRPS) has been proposed as a potential solution to alleviate seasonal drought and early low-temperature stress in hilly mountainous areas; clarifying its impact on crop growth is crucial to enhance rice productivity in these areas. A two-year (2021-2022) field experiment was conducted in the hilly mountains of southwest China to compare the effects of the traditional flooding paddy (Paddy) and GCRPS under three different nitrogen (N) management practices (N1, zero-N fertilizer; N2, 135 kg N ha-1 as a urea-based fertilizer; and N3, 135 kg N ha-1 with a 3:2 base-topdressing ratio as urea fertilizer for the Paddy or a 1:1 basal application ratio as urea and manure for GCRPS) on soil water storage, soil mineral N content and crop growth parameters, including plant height, tiller numbers, the leaf area index (LAI), aboveground dry matter (DM) dynamics and crop yield. The results showed that there was a significant difference in rainfall between the two growth periods, with 906 mm and 291 mm in 2021 and 2022, respectively. While GCRPS did not significantly affect soil water storage, soil mineral N content, and plant height, it led to a reduction in partial tiller numbers (1.1% to 31.6%), LAI (0.6% to 20.4%), DM (4.4% to 18.8%), and crop yield (7.4% to 22.0%) in 2021 (wet year) compared to the Paddy. However, in 2022 (dry year), GCRPS led to an increase in tiller numbers (13.7% to 115.4%), LAI (17.3% to 81.0%), DM (9.0% to 62.6%), and crop yield (2.9% to 9.2%) compared to the Paddy. Structural equation modeling indicated that GCRPS significantly affected tiller numbers, plant height, LAI, DM, and productive tiller numbers, which indirectly influenced crop yield by significantly affecting tiller numbers and productive tiller numbers in 2022. Overall, the effects of GCRPS on soil water and N dynamics were not significant. In 2021, with high rainfall, no drought, and no early, low-temperature stress, the GCRPS suppressed crop growth and reduced yield, while in 2022, with drought and early low-temperature stress and low rainfall, the GCRPS promoted crop growth and increased yield, with tiller numbers and productive tiller numbers being the key factors affecting crop yield.
ABSTRACT
The threat of global climate change on wheat production may be underestimated by the limited capacity of many crop models to predict grain quality and protein composition. This study aimed to integrate a wheat quality module of protein components into the CROPSIM-CERES-Wheat model to investigate the impact of climate change on wheat grain yield and protein quality in the North China Region (NCR) using five Global Climate Models (GCMs) from CMIP6 under three shared socioeconomic pathways. The CERES-Wheat model with a quality module was developed and calibrated and validated using data from several sites in the NCR. The results of the calibration and validation showed that the modified CERES-Wheat model can accurately predict grain yield, protein content and its components in field experiments. Compared with the baseline period (1981-2010), the annual mean temperature and annual cumulative precipitation increased in the NCR in the 2030's, 2050's and 2080's. The radiation was higher under the SSP126 and SSP585 scenarios, and lower under the SSP370 scenario compared to the baseline period. The anthesis and maturity date occurred earlier under the three future scenarios. The average grain yield increased by 13.3-30.9 % under three future scenarios. However, the regional average grain protein content of winter wheat in the future decreased by 2.0 %- 3.5 %. The reduction in wheat grain protein at the regional was less pronounced under SSP370 than that under SSP126 and SSP585. The structural protein content of winter wheat decreased under future climate conditions compared with the baseline period, but the storage protein content showed the opposite tendency. The model provided a useful tool to study the effects of future climate on grain quality and protein composition. These findings are important for developing agricultural practices and strategies to mitigate the potential impacts of climate change on wheat production and wheat quality in the future.
Subject(s)
Grain Proteins , Triticum , Climate Change , Edible Grain , Agriculture/methods , ChinaABSTRACT
[This corrects the article DOI: 10.1371/journal.pone.0259929.].
ABSTRACT
Sap-sucking insects cause severe damage to cotton production. Long non-coding RNAs (lncRNAs) play vital regulatory roles in various development processes and stress response, however, the function of lncRNAs during sap-sucking insect infection in cotton is largely unknown. In this study, the transcriptome profiles between resistant (HR) and susceptible (ZS) cotton cultivars under whitefly infestation at different time points (0, 4, 12, 24, and 48 h) were compared. A total of 6,651 lncRNAs transcript and 606 differentially expressed lncRNAs were identified from the RNA-seq data. A co-expression network indicated that lncA07 and lncD09 were potential hub genes that play a regulatory role in cotton defense against aphid infestation. Furthermore, CRISPR/Cas9 knock-out mutant of lncD09 and lncA07 showed a decrease of jasmonic acid (JA) content, which potentially lead to increased susceptibility toward insect infestation. Differentially expressed genes between wild type and lncRNA knock-out plants are enriched in modulating development and resistance to stimulus. Additionally, some candidate genes such as Ghir_A01G022270, Ghir_D04G014430, and Ghir_A01G022270 are involved in the regulation of the JA-mediated signaling pathway. This result provides a novel insight of the lncRNA role in the cotton defense system against pests.
ABSTRACT
China feeds 19.1% of the world's population with 8.6% of the arable land. Here we propose an integrated approach combining crop redistribution and improved management to meet China's food demand in 2030. We simulated the food demand, estimated the national crop production through the productivity of the top 10% of producers in each county, and optimized the spatial distribution of 11 groups of crop types among counties using the data of the top producers. Integrating crop redistribution and improved management increased crop production and can meet the food demand in 2030, while the agricultural inputs (N and P fertilizers and irrigation water) and environmental impacts (reactive N loss and greenhouse gas emissions) were reduced. Although there are significant socio-economic and cultural barriers to implementing such redistribution, these results suggest that integrated measures can achieve food security and decrease negative environmental impacts. County-specific policies and advisory support will be needed to achieve the promises of combining optimization strategies.
ABSTRACT
BACKGROUND: Optimal nitrogen (N) application and plant growth regulators can improve wheat productivity. This can help to improve yield level and ensure food security with limited resources in the Huang-Huai-Hai Plain of China (HPC). METHODS: A 2-year field experiment was conducted using a randomized block design with four treatments (TS-N topdressing at pseudostem erection stage ; TPS-N topdressing combined with paclobutrazol application at pseudostem erection stage; TJ-N topdressing at jointing stage; TPJ-N topdressing at combined with paclobutrazol application at jointing stage) in 2011-2013. RESULTS: The grain number per ear, thousand kernel weight and yield for the TJ and TPJ treatments were higher than those of the TS and TPS treatments. Grain number per ear, yield, and thousands kernel weigh for the TPJ treatment were significantly higher than for the TS and TPS in 2011-2012 (9.82% and 7.27%, 10.23% and 8.99%, 6.12% and 5.58%) and in 2012-2013 (10.21% and 11.55%, 8.00% and 6.58%, 0.00 and 0.00), respectively. Thousands kernel weight under TJ were significantly higher than those under TS and TPS by 13.21% and 14.03%, respectively in 2012-2013. The floret number, significantly correlated with cytokinin content, was also significantly increased under TJ and TPJ at connectivum differentiation stage. For TPJ treatment, the floret number was significantly higher than for the TS, TPS, and TJ by 19.92%, 10.21%, 6.10% in 2011-2012; it was higher than for the TS and TPS by 28.06% and 29.61% in 2012-2013, respectively. The relative expression level of cytokinin oxidase/dehydrogenase gene (TaCKX2.2) was improved during flowering, when cytokinin content was at high level and was also inhibited by paclobutrazol with different degrees. CONCLUSIONS: Therefore, nitrogen topdressing at jointing stage had increased grain number per ear, thousand kernel weight, and grain yield of wheat. Paclobutrazol could delay spike differentiation and promote cytokinin accumulation that induced expression of TaCKX2.2, maintaining hormonal balance and affecting wheat spike morphogenesis.
ABSTRACT
Increasing domestic rapeseed production is an important national goal in China. Researchers often use tools such as crop models to determine optimum management practices for new varieties to increased production. The CROPGRO-Canola model has not been used to simulate rapeseed in China. The overall goal of this work was to identify key inputs to the CROPGRO-Canola model for calibration with limited datasets in the Yangtze River basin. First, we conducted a global sensitivity analysis to identify key genetic and soil inputs that have a large effect on simulated days to flowering, days to maturity, yield, above-ground biomass, and maximum leaf area index. The extended Fourier amplitude test method (EFAST) sensitivity analysis was performed for a single year at 8 locations in the Yangtze River basin (spatial analysis) and for seven years at a location in Wuhan, China (temporal analysis). The EFAST software was run for 4520 combinations of input parameters for each site and year, resulting in a sensitivity index for each input parameter. Parameters were ranked using the top-down concordance method to determine relative sensitivity. Results indicated that the model outputs of days to flowering, days to maturity, yield, above-ground biomass, and maximum leaf area index were most sensitive to parameters that affect the duration of critical growth periods, such as emergence to flowering, and temperature response to these stages, as well as parameters that affect total biomass at harvest. The five model outputs were also sensitive to several soil parameters, including drained upper and lower limit (SDUL and SLLL) and drainage rate (SLDR). The sensitivity of parameters was generally spatially and temporally stable. The results of the sensitivity analysis were used to calibrate and evaluate the model for a single rapeseed experiment in Wuhan, China. The model was calibrated using two seasons and evaluated using three seasons of data. Excellent nRMSE values were obtained for days to flowering (≤1.71%), days to maturity (≤ 1.48%), yield (≤ 9.96%), and above-ground biomass (≤ 9.63%). The results of this work can be used to guide researchers on model calibration and evaluation across the Yangtze River basin in China.
Subject(s)
Brassica napus/growth & development , Models, Biological , Brassica napus/genetics , Calibration , China , Datasets as Topic , Flowers/genetics , Flowers/growth & development , Sensitivity and Specificity , Soil , Spatial AnalysisABSTRACT
China purchases around 66% of the soy that is traded internationally. This strains the global food supply and contributes to greenhouse gas emissions. Here we show that optimizing the maize and soy production of China can improve its self-sufficiency and also alleviate adverse environmental effects. Using data from more than 1,800 counties in China, we estimate the area-weighted yield potential (Ypot) and yield gaps, setting the attainable yield (Yatt) as the yield achieved by the top 10% of producers per county. We also map out county-by-county acreage allocation and calculate the attainable production capacity according to a set of sustainability criteria. Under optimized conditions, China would be able to produce all the maize and 45% of the soy needed by 2035-while reducing nitrogen fertilizer use by 26%, reactive nitrogen loss by 28% and greenhouse gas emissions by 19%-with the same acreage as 2017, our reference year.
ABSTRACT
Melatonin is effective in enhancing various abiotic stress resistances of plants. However, its underlying mechanisms in drought-resistance in winter wheat (Triticum aestivum L.) is not clear. The goal of this work was to investigate the effect of melatonin on seed germination and to evaluate leaf antioxidant physiology for two wheat varieties. Experiments included 20% PEG, melatonin plus 20% PEG and a control using two contrasting wheat varieties (JM22- drought sensitive and HG35- drought resistant). Melatonin levels were 0, 1, 10, 100 and 300 µmol L-1. Results revealed that 300 µmol L-1 of melatonin alleviated the negative effect of water stress on germination and increased radicle length, radicle number, and plumule length of the germinated seeds. Principal component analysis showed a significant change in amino acid content during germination and this change was dependent on melatonin concentration and the variety. Lysine (Lys) content in wheat seeds under the PEG plus 300 µmol L-1 melatonin treatment increased compared with that of the seeds under PEG alone. There was a significant and positive correlation between Lys content and morphological index of germination. During seedling growth, soluble protein was involved in osmotic adjustment and superoxide dismutase (SOD) activity was increased to mitigate the damage in the cytomembrane of JM 22 leaf under 300 µmol L-1 melatonin plus PEG treatment. The effect of melatonin was dependent on SOD activity increasing significantly for HG35-a drought resistant variety. The results of this work lays a foundation for further studies to determine if melatonin can be economically used to mitigate the impact of dry planting conditions on wheat productivity in North China Plain.
Subject(s)
Antioxidants/pharmacology , Germination/drug effects , Melatonin/pharmacology , Polyethylene Glycols/toxicity , Seeds/drug effects , Stress, Physiological , Triticum/drug effects , Droughts , Osmosis , Seeds/growth & development , Seeds/metabolism , Triticum/growth & development , Triticum/metabolismABSTRACT
Excessive ammonia (NH3 ) emitted from nitrogen (N) fertilizer applications in global croplands plays an important role in atmospheric aerosol production, resulting in visibility reduction and regional haze. However, large uncertainty exists in the estimates of NH3 emissions from global and regional croplands, which utilize different data and methods. In this study, we have coupled a process-based Dynamic Land Ecosystem Model (DLEM) with the bidirectional NH3 exchange module in the Community Multiscale Air-Quality (CMAQ) model (DLEM-Bi-NH3 ) to quantify NH3 emissions at the global and regional scale, and crop-specific NH3 emissions globally at a spatial resolution of 0.5° × 0.5° during 1961-2010. Results indicate that global NH3 emissions from N fertilizer use have increased from 1.9 ± 0.03 to 16.7 ± 0.5 Tg N/year between 1961 and 2010. The annual increase of NH3 emissions shows large spatial variations across the global land surface. Southern Asia, including China and India, has accounted for more than 50% of total global NH3 emissions since the 1980s, followed by North America and Europe. Rice cultivation has been the largest contributor to total global NH3 emissions since the 1990s, followed by corn and wheat. In addition, results show that empirical methods without considering environmental factors (constant emission factor in the IPCC Tier 1 guideline) could underestimate NH3 emissions in context of climate change, with the highest difference (i.e., 6.9 Tg N/year) occurring in 2010. This study provides a robust estimate on global and regional NH3 emissions over the past 50 years, which offers a reference for assessing air quality consequences of future nitrogen enrichment as well as nitrogen use efficiency improvement.
Subject(s)
Air Pollutants/analysis , Ammonia/analysis , Crop Production/methods , Fertilizers/analysis , Nitrogen/analysis , Models, BiologicalABSTRACT
The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3-4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994-2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water savings. These results showed that there is a cost to the farmer for water conservation, but limiting irrigation to a single irrigation at jointing would minimize impact on farmer net return in North China Plain.
Subject(s)
Agricultural Irrigation/methods , Conservation of Natural Resources/methods , Crops, Agricultural/growth & development , Triticum/growth & development , Biomass , Calibration , China , Crops, Agricultural/economics , Models, Theoretical , RainABSTRACT
An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China.