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BACKGROUND: Lentil is a significant legume that are consumed as a staple food and have a significant economic impact around the world. The purpose of the present research on lentil was to assess the hydrothermal time model's capacity to explain the dynamics of Lens culinaris L. var. Markaz-09 seed germination, as well as to ascertain the germination responses at various sub-optimal temperatures (T) and water potentials (Ψ). In order to study lentil seed germination (SG) behavior at variable water potentials (Ψs) and temperatures (Ts). A lab experiment employing the hydrothermal time model was created. Seeds were germinated at six distinct temperatures: 15 0С, 20 0С, 25 0С, 30 0С, 35 0С, and 40 0С, with five Ψs of 0, -0.3, -0.6, -0.9, and - 1.2 MPa in a PEG-6000 (Polyethylene glycol 6000) solution. RESULTS: The results indicated that the agronomic parameters like Germination index (GI), Germination energy (GE), Timson germination index (TGI), were maximum in 25 0C at (-0.9 MPa) and lowest at 40 0C in 0 MPa. On other hand, mean germination time (MGT) value was highest at 15 0C in -1.2 MPa and minimum at 40 0C in (-0.6 MPa) while Mean germination rate (MGR) was maximum at 40 0C in (0 MPa) and minimum at 15 0C in (-0.6 MPa). CONCLUSIONS: The HTT model eventually defined the germination response of Lens culinaris L. var. Markaz-09 (Lentil) for all Ts and Ψs, allowing it to be employed as a predictive tool in Lens culinaris L. var. Markaz-09 (Lentil) seed germination simulation models.
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Germinação , Lens (Planta) , Sementes , Temperatura , Germinação/fisiologia , Sementes/fisiologia , Sementes/crescimento & desenvolvimento , Lens (Planta)/fisiologia , Lens (Planta)/crescimento & desenvolvimento , Água/metabolismo , Modelos Biológicos , Pressão OsmóticaRESUMO
BACKGROUND: The rate of germination and other physiological characteristics of seeds that are germinating are impacted by deep sowing. Based on the results of earlier studies, conclusions were drawn that deep sowing altered the physio-biochemical and agronomic characteristics of wheat (Triticum aestivum L.). RESULTS: In this study, seeds of wheat were sown at 2 (control) and 6 cm depth and the impact of exogenously applied salicylic acid and tocopherol (Vitamin-E) on its physio-biochemical and agronomic features was assessed. As a result, seeds grown at 2 cm depth witnessed an increase in mean germination time, germination percentage, germination rate index, germination energy, and seed vigor index. In contrast, 6 cm deep sowing resulted in negatively affecting all the aforementioned agronomic characteristics. In addition, deep planting led to a rise in MDA, glutathione reductase, and antioxidants enzymes including APX, POD, and SOD concentration. Moreover, the concentration of chlorophyll a, b, carotenoids, proline, protein, sugar, hydrogen peroxide, and agronomic attributes was boosted significantly with exogenously applied salicylic acid and tocopherol under deep sowing stress. CONCLUSIONS: The results of the study showed that the depth of seed sowing has an impact on agronomic and physio-biochemical characteristics and that the negative effects of deep sowing stress can be reduced by applying salicylic acid and tocopherol to the leaves.
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Germinação , Ácido Salicílico , Tocoferóis , Triticum , Triticum/crescimento & desenvolvimento , Triticum/metabolismo , Triticum/efeitos dos fármacos , Ácido Salicílico/farmacologia , Ácido Salicílico/metabolismo , Tocoferóis/metabolismo , Germinação/efeitos dos fármacos , Sementes/efeitos dos fármacos , Sementes/crescimento & desenvolvimento , Antioxidantes/metabolismo , Estresse Fisiológico , Desenvolvimento Sustentável , Clorofila/metabolismoRESUMO
Robust quantification of vegetative biomass using satellite imagery using one or more forms of machine learning (ML) has hitherto been hindered by the extent and quality of training data. Here, we showcase how ML predictive demonstrably improves when additional training data is used. We collated field datasets of pasture biomass obtained via destructive sampling, 'C-Dax' reflective measurements and rising plate meters (RPM) from ten livestock farms across four States in Australia. Remotely sensed data from the Sentinel-2 constellation was used to retrieve aboveground biomass using a novel machine learning paradigm hereafter termed "SPECTRA-FOR" (Spectral Pasture Estimation using Combined Techniques of Random-forest Algorithm for Features Optimisation and Retrieval). Using this framework, we show that the low temporal resolution of Sentinel-2 in high latitude regions with persistent cloud cover leads to extensive gaps between cloud-free images, hindering model performance and, thus, contemporaneous ability to forecast real-time pasture biomass. By leveraging the spectral consistency between Sentinel-2 and Planet Lab SuperDove to overcome this limitation, we used ten spectral bands of Sentinel-2, four bands of Sentinel-2 as a proxy for pre-2022 SuperDove (referred to as synthetic SuperDove or SSD), and the actual SuperDove (ASD), given that SuperDove imagery has a higher resolution and more frequent passage compared with Sentinel-2. Using their respective bands as input features to SPECRA-FOR, model performance for the ten bands of Sentinel-2 were R2 = 0.87, root mean squared error (RMSE) of 439 kg DM/ha and mean absolute error (MAE) of 255 kg DM/ha, while that for SSD increased to an R2 of 0.92, RMSE of 346 kg DM/ha and MAE = 208 kg DM/ha. The study revealed the importance of robust data mining, imagery harmonisation and model validation for accurate real-time modelling of pasture biomass with ML.
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Aprendizado de Máquina , Imagens de Satélites , Imagens de Satélites/métodos , Biomassa , Fazendas , AustráliaRESUMO
The livestock industry accounts for a considerable proportion of agricultural greenhouse gas emissions, and in response, the Australian red meat industry has committed to an aspirational target of net-zero emissions by 2030. Increasing soil carbon storage in grazing lands has been identified as one method to help achieve this, while also potentially improving production and provision of other ecosystem services. This review examined the effects of grazing management on soil carbon and factors that drive soil carbon sequestration in Australia. A systematic literature search and meta-analysis was used to compare effects of stocking intensity (stocking rate or utilisation) and stocking method (i.e, continuous, rotational or seasonal grazing systems) on soil organic carbon, pasture herbage mass, plant growth and ground cover. Impacts on below ground biomass, soil nitrogen and soil structure are also discussed. Overall, no significant impact of stocking intensity or method on soil carbon sequestration in Australia was found, although lower stocking intensity and incorporating periods of rest into grazing systems (rotational grazing) had positive effects on herbage mass and ground cover compared with higher stocking intensity or continuous grazing. Minimal impact of grazing management on pasture growth rate and below-ground biomass has been reported in Australia. However, these factors improved with grazing intensity or rotational grazing in some circumstances. While there is a lack of evidence in Australia that grazing management directly increases soil carbon, this meta-analysis indicated that grazing management practices have potential to benefit the drivers of soil carbon sequestration by increasing above and below-ground plant production, maintaining a higher residual biomass, and promoting productive perennial pasture species. Specific recommendations for future research and management are provided in the paper.
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Ecossistema , Solo , Austrália , Biomassa , Carbono/análise , Solo/químicaRESUMO
Livestock have long been integral to food production systems, often not by choice but by need. While our knowledge of livestock greenhouse gas (GHG) emissions mitigation has evolved, the prevailing focus has been-somewhat myopically-on technology applications associated with mitigation. Here, we (1) examine the global distribution of livestock GHG emissions, (2) explore social, economic and environmental co-benefits and trade-offs associated with mitigation interventions and (3) critique approaches for quantifying GHG emissions. This review uncovered many insights. First, while GHG emissions from ruminant livestock are greatest in low- and middle-income countries (LMIC; globally, 66% of emissions are produced by Latin America and the Caribbean, East and southeast Asia and south Asia), the majority of mitigation strategies are designed for developed countries. This serious concern is heightened by the fact that 80% of growth in global meat production over the next decade will occur in LMIC. Second, few studies concurrently assess social, economic and environmental aspects of mitigation. Of the 54 interventions reviewed, only 16 had triple-bottom line benefit with medium-high mitigation potential. Third, while efforts designed to stimulate the adoption of strategies allowing both emissions reduction (ER) and carbon sequestration (CS) would achieve the greatest net emissions mitigation, CS measures have greater potential mitigation and co-benefits. The scientific community must shift attention away from the prevailing myopic lens on carbon, towards more holistic, systems-based, multi-metric approaches that carefully consider the raison d'être for livestock systems. Consequential life cycle assessments and systems-aligned 'socio-economic planetary boundaries' offer useful starting points that may uncover leverage points and cross-scale emergent properties. The derivation of harmonized, globally reconciled sustainability metrics requires iterative dialogue between stakeholders at all levels. Greater emphasis on the simultaneous characterization of multiple sustainability dimensions would help avoid situations where progress made in one area causes maladaptive outcomes in other areas.
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Gases de Efeito Estufa , Miopia , Animais , Carbono , Efeito Estufa , Gases de Efeito Estufa/análise , GadoRESUMO
Optimizing crop distribution stands as a pivotal approach to climate change adaption, enhancing crop production sustainability, and has been recognized for its immense potential in ensuring food security while minimizing environmental impacts. Here, we developed a climate-adaptive framework to optimize the distribution of staple crops (i.e., wheat, maize, and rice) to meet the multi-dimensional needs of crop production in China. The framework considers the feasibility of the multiple cropping systems (harvesting more than once on a cropland a year) and adopts a multi-dimensional approach, incorporating goals related to crop production, water consumption, and greenhouse gas (GHG) emissions. By optimizing, the total irrigated area of three crops would decrease by 7.7 % accompanied by a substantial 69.8 % increase in rain-fed areas compared to the baseline in 2010. This optimized strategy resulted in a notable 10.0 % reduction in total GHG emissions and a 13.1 % decrease in irrigation water consumption while maintaining consistent crop production levels. In 2030, maintaining the existing crop distribution and relying solely on yield growth would lead to a significant maize production shortfall of 27.0 %, highlighting a looming challenge. To address this concern, strategic adjustments were made by reducing irrigated areas for wheat, rice, and maize by 2.3 %, 12.8 %, and 6.1 %, respectively, while simultaneously augmenting rain-fed areas for wheat and maize by 120.2 % and 55.9 %, respectively. These modifications ensure that production demands for all three crops are met, while yielding a 6.9 % reduction in GHG emissions and a 15.1 % reduction in irrigation water consumption. This optimization strategy offers a promising solution to alleviate severe water scarcity issues and secure a sustainable agricultural future, effectively adapting to evolving crop production demands in China.
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Mudança Climática , Produtos Agrícolas , Gases de Efeito Estufa , Gases de Efeito Estufa/análise , China , Produtos Agrícolas/crescimento & desenvolvimento , Agricultura/métodos , Abastecimento de Alimentos/métodos , Abastecimento de Água , Zea mays/crescimento & desenvolvimento , Triticum/crescimento & desenvolvimento , Produção Agrícola/métodosRESUMO
For thousands of years, plants have been utilized for medicinal purposes. For its naturally existing antibacterial properties, Nigella sativa is one of the most researched herbs. A study was conducted during rabi 2020-21 at The University of Haripur in order to evaluate the potential of ascorbic acid as plant growth enhancer. Two concentrations of ascorbic acid i-e 350 µm and 400 µm were sprayed along with control and water only spray on Nigella sativa crop. The study was arranged in RCBD two factor factorial arrangement. Factor A: ascorbic acid concentrations along with control and water spray, factor B: Growth stages (Stage1 = 40 days after sowing, Stage 2 = 80 DAS, Stage 3 = 120 DAS, Stage 4 = 40 + 80 DAS, Stage 5 = 40 + 120 DAS, Stage 6 = 80 + 120 DAS, Stage 7 = 40 + 80 + 120 DAS). Crop was sown in first week of November. Results reviled that chlorophyll b content, fixed oil content, 1000 seed weight, grain yield, Photosynthetic rate (µ mole m-2s-1), Transpiration rate (mmole m-2s-1), photosynthetic water use efficiency, Internal CO2 concentration (Ci) of leaf tissue and Stomatal conductance (mmole m-2s-1) were significantly affected by ascorbic acid concentrations and stage of application. Crop growth rate increased by 19.88% and 17.29%, chlorophyll b by 12.3% and 11.2%, fixed oil by 11.7% and 9%, grain yield by 10.29% and 9.8%, harvest index by 4% and 5.7% photosynthetic rate by 33%, 20% and stomatal conductance by 24.24% and 24.25 with application of ascorbic acid @ 350 µm, over control and water spray respectively. On the basis of these results it is concluded that application of ascorbic acid at the rate of 350 µm, followed by ascorbic acid at the rate of 400 µm significantly improves black cumin (Nigella sativa) yield and production. Hence it is recommended to apply ascorbic acid at the rate of 350 µm at 40 + 80+120 days after sowing of Nigella sativa crop for obtaining maximum results.
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Purpose of current study was to determine physicochemical, triglyceride composition, and functional groups of wild adlay accessions (brown, black, yellow, grey, green, off white, and purple) to find out its scope as cereal crop. Triglycerides, minerals and functional groups were determined through Gas chromatography, spectrophotometer and Fourier Transform Infrared (FTIR) spectrophotometer respectively. Results revealed variation among bulk densities, specific densities, percent empty spaces, and corresponding grain counts per 10 g of sample are useful in distinguishing brown, black, yellow, grey, green, off white, and purple wild adlay accessions. Specific density and grain count per 10 g sample was significantly related. No statistical relationship exists among the pronounced physical characteristics. Brown adlay expressed the highest protein, fat, and fiber contents 15.82%, 4.76% and 2.37% respectively. Protein, fat, ash, and fiber percent contents were found comparable to cultivated adlay. Spectrophotometric analysis revealed macro elements including phosphorus, potassium, calcium, and sodium in the range 0.3% - 2.2% and micro elements boron, iron, copper, zinc, and manganese in the range 1.6 mg/kg - 20.8 mg/kg. Gas chromatography showed polyunsaturated fatty acids (PUFA) constitute the primary fraction (39% ± 7.2) of wild adlay triglycerides. Linoleic and palmitic acids were present as prominent fatty acids, 43.5% ±1.4 and 26.3% ±1.4 respectively. Infra-red frequencies distinguished functional groups in narrow band and fingerprint region of protein in association with out of plane region leading to structural differences among adlay accessions. Comparison of major distinguishing vibrational frequencies among different flours indicated black adlay containing highest functional groups appeared promising for varietal development.
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Soil organic carbon (SOC) can influence atmospheric CO2 concentration and then the extent to which the climate emergency is mitigated globally. It follows the elucidation of the driving factors of cropland SOC stocks, which is fundamental to reducing soil carbon loss and promoting soil carbon sequestration. Here, we examined the influence of 16 environmental variables on SOC stocks and sequestration based on three machine learning soil mapping methods, i.e. multiple linear regression (MLR), random forest (RF) and extreme gradient boosting (XGBOOST), with 2875 observed soil samples from cropland topsoil across Hunan Province, China in 2010. We employed a structural equation model (SEM) to extricate the driving mechanisms of environmental variables on SOC stocks at the regional scale. Our results show that XGBOOST had the most reliable performance in predicting SOC stocks, explaining 66 % of the total SOC stock variation. Croplands with high SOC stocks were distributed in low-altitude and water-sufficient areas. The partial dependence of SOC on precipitation showed a trend of increasing and then slowly decreasing. In addition, the grid-based SEM results clearly presented the direct and indirect routes of environmental variables' impacts on cropland SOC stocks. Soil properties regulated by elevation, were the most influential natural factor on SOC stocks. Precipitation and elevation drove SOC stocks through direct and indirect effects respectively. Our SEM combined with machine learning approach can provide an effective explanation of the driving mechanism for SOC accumulation. We expect our proposed modelling approach can be applied to other regions and offer new insights, as a reference for mitigating cropland soil carbon loss under climate emergency conditions.
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Carbono , Solo , Solo/química , Carbono/química , Sequestro de Carbono , Altitude , Produtos AgrícolasRESUMO
Waterlogging constrains crop yields in many regions around the world. Despite this, key drivers of crop sensitivity to waterlogging have received little attention. Here, we compare the ability of the SWAGMAN Destiny and CERES models in simulating soil aeration index, a variable contemporaneously used to compute three distinct waterlogging indices, denoted hereafter as WI Destiny, WIASD1, and WIASD2. We then account for effects of crop growth stage and soil temperature on waterlogging impact by introducing waterlogging severity indices, WI Growth, which accommodates growth stage tolerance, and WI Plus, which accounts for both soil temperature and growth stage. We evaluate these indices using data collected in pot experiments with genotypes "Yang mai 11" and "Zheng mai 7698" that were exposed to both single and double waterlogging events. We found that WI Plus exhibited the highest correlation with yield (-0.82 to -0.86) suggesting that waterlogging indices which integrate effects of temperature and growth stage may improve projections of yield penalty elicited by waterlogging. Importantly, WI Plus not only allows insight into physiological determinants, but also lends itself to remote computation through satellite imagery. As such, this index holds promise in scalable monitoring and forecasting of crop waterlogging.
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The remarkable yield performance of super hybrid rice has played a crucial role in ensuring global food security. However, there is a scarcity of studies investigating the contribution of radiation use efficiency (RUE) to hybrid rice yields under different nitrogen and potassium treatments. In this three-year field experiment, we aimed to evaluate the impact of two hybrid rice varieties (Y-liangyou 900: YLY900 and Quanyouhuazhan: QYHZ) under varying nitrogen regimes (N90: 90 kg N ha-1, N120: 120 kg N ha-1, N180: 180 kg N ha-1) and potassium regimes (K120: 120 kg K2O ha-1, K160: 160 kg K2O ha-1, K210: 210 kg K2O ha-1) on grain yield and its physiological determinants, including RUE, intercepted photosynthetically active radiation (IPAR), aboveground biomass production, and harvest index (HI). Our results revealed that both rice varieties exhibited significantly higher yields when coupled with nitrogen and potassium fertilization. Compared to the N90 × K120 treatment, the N120 × K160 and N180 × K210 combinations resulted in substantial increases in grain yield (12.0% and 21.1%, respectively) and RUE (11.9% and 21.4%, respectively). The YLY900 variety showed notable yield improvement due to enhanced aboveground biomass production resulting from increased IPAR and RUE. In contrast, the QYHZ variety's aboveground biomass accumulation was primarily influenced by RUE rather than IPAR, resulting in higher RUE and grain yields of 9.2% and 5.3%, respectively, compared to YLY900. Importantly, fertilization led to significant increases in yield, biomass, and RUE, while HI remained relatively constant. Both varieties demonstrated a positive relationship between grain yield and IPAR and RUE. Multiple regression analysis indicated that increasing RUE was the primary driver of yield improvement in hybrid rice varieties. By promoting sustainable agriculture and enhancing fertilizer management, elevating nitrogen and potassium levels from a low base would synergistically enhance rice yield and RUE, emphasizing the critical importance of RUE in hybrid rice productivity compared to HI.
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Water deficit stress exposure frequently constrains plant and agri-food production globally. Biostimulants (BSs) can be considered a new tool in mitigating water deficit stress. This study aimed to understand how BSs influence water deficit stress perceived by savory plants (Satureja hortensis L.), an important herb used for nutritional and herbal purposes in the Middle East. Three BS treatments, including bio-fertilizers, humic acid and foliar application of amino acid (AA), were implemented. Each treatment was applied to savory plants using three irrigation regimes (low, moderate and severe water deficit stress FC100, FC75 and FC50, respectively). Foliar application of AA increased dry matter yield, essential oil (EO) content and EO yield by 22%, 31% and 57%, respectively. The greatest EO yields resulted from the moderate (FC75) and severe water deficit stress (FC50) treatments treated with AA. Primary EO constituents included carvacrol (39-43%), gamma-terpinene (27-37%), alpha-terpinene (4-7%) and p-cymene (2-5%). Foliar application of AA enhanced carvacrol, gamma-terpinene, alpha-terpinene and p-cymene content by 6%, 19%, 46% and 18%, respectively. Physiological characteristics were increased with increasing water shortage and application of AA. Moreover, the maximum activities of superoxide dismutase (3.17 unit mg-1 min-1), peroxidase (2.60 unit mg-1 min-1) and catalase (3.08 unit mg-1 min-1) were obtained from plants subjected to severe water deficit stress (FC50) and treated with AA. We conclude that foliar application of AA under water deficit stress conditions would improve EO quantity and quality in savory.
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Óleos Voláteis , Satureja , Óleos Voláteis/farmacologia , Óleos Voláteis/química , Desidratação , Satureja/química , ÁguaRESUMO
The present study was conducted to determine the effect of indole acetic acid (IAA) and Citrate Capped Silver Nanoparticles (Cit-AgNPs) on various attributes of maize under induced salinity stress. Seeds of the said variety were collected from Cereal Crop Research Institute (CCRI) Pirsabaq, Nowshera, sterilized and sown in earthen pots filled with 2 kg silt and soil (1:2) in triplicates in the green house of the Botany Department, University of Peshawar. Nanoparticles were analyzed by scanning electron microscopy (SEM), Energy Dispersive X-Ray Spectroscopy (EDX), Thermo-gravimetric analysis (TGA) and Differential thermal analysis (DTA). Results of SEM revealed spherical morphology of Cit-AgNPs while EDX showed various elemental composition. TGA showed dominant weight loss up to 300 °C while the DTA showed major exothermic peaks at 420 °C. High Salinity concentration (80 mM) imposed significant detrimental impacts by reducing the agronomic attributes, photosynthetic pigments, osmolytes and antioxidant enzymes, which was remarkably ameliorated by the foliar application of Cit-AgNPs and IAA. Agronomic attributes including leaf, root and shoot fresh and dry weight was improved by 52-74%, 43-69% and 36-79% in individual as well as combined treatments of IAA and NPs. Photosynthetic pigments were amplified by 35-63%, total osmolytes were augmented by 39-68% and antioxidant enzymes including SOD and POD were boosted by 42-57% and 37-62% respectively, in combined as well as individual application. Conclusively, Cit-AgNPs are considered as salt mitigating entities that enhance the tolerance level of crop plants along with IAA, which may be beneficial for the plants growing in saline stressed environment.
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Antioxidantes , Nanopartículas Metálicas , Antioxidantes/química , Nanopartículas Metálicas/química , Ácido Cítrico , Prata/farmacologia , Prata/química , Zea mays , Estresse SalinoRESUMO
Significant advancements have been made in understanding the genetic regulation of nitrogen use efficiency (NUE) and identifying crucial NUE genes in rice. However, the development of rice genotypes that simultaneously exhibit high yield and NUE has lagged behind these theoretical advancements. The grain yield, NUE, and greenhouse gas (GHG) emissions of newly-bred rice genotypes under reduced nitrogen application remain largely unknown. To address this knowledge gap, field experiments were conducted, involving 80 indica (14 to 19 rice genotypes each year in Wuxue, Hubei) and 12 japonica (8 to 12 rice genotypes each year in Yangzhou, Jiangsu). Yield, NUE, agronomy, and soil parameters were assessed, and climate data were recorded. The experiments aimed to assess genotypic variations in yield and NUE among these genotypes and to investigate the eco-physiological basis and environmental impacts of coordinating high yield and high NUE. The results showed significant variations in yield and NUE among the genotypes, with 47 genotypes classified as moderate-high yield with high NUE (MHY_HNUE). These genotypes demonstrated the higher yields and NUE levels, with 9.6 t ha-1, 54.4 kg kg-1, 108.1 kg kg-1, and 64 % for yield, NUE for grain and biomass production, and N harvest index, respectively. Nitrogen uptake and tissue concentration were key drivers of the relationship between yield and NUE, particularly N uptake at heading and N concentrations in both straw and grain at maturity. Increase in pre-anthesis temperature consistently lowered yield and NUE. Genotypes within the MHY_HNUE group exhibited higher methane emissions but lower nitrous oxide emissions compared to those in the low to middle yield and NUE group, resulting in a 12.8 % reduction in the yield-scaled greenhouse gas balance. In conclusion, prioritizing crop breeding efforts on yield and resource use efficiency, as well as developing genotypes resilient to high temperatures with lower GHGs, can mitigate planetary warming.
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Gases de Efeito Estufa , Oryza , Nitrogênio , Oryza/genética , Fertilizantes/análise , Melhoramento Vegetal , Solo , Agricultura/métodos , Óxido Nitroso/análise , Grão Comestível/química , GenótipoRESUMO
Extreme weather events threaten food security, yet global assessments of impacts caused by crop waterlogging are rare. Here we first develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a farming systems model to discern changes in global crop waterlogging under future climates. Third, we develop avenues for adapting cropping systems to waterlogging contextualised by environment. We find that yield penalties caused by waterlogging increase from 3-11% historically to 10-20% by 2080, with penalties reflecting a trade-off between the duration of waterlogging and the timing of waterlogging relative to crop stage. We document greater potential for waterlogging-tolerant genotypes in environments with longer temperate growing seasons (e.g., UK, France, Russia, China), compared with environments with higher annualised ratios of evapotranspiration to precipitation (e.g., Australia). Under future climates, altering sowing time and adoption of waterlogging-tolerant genotypes reduces yield penalties by 18%, while earlier sowing of winter genotypes alleviates waterlogging by 8%. We highlight the serendipitous outcome wherein waterlogging stress patterns under present conditions are likely to be similar to those in the future, suggesting that adaptations for future climates could be designed using stress patterns realised today.
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Aclimatação , Água , Estações do Ano , Adaptação Fisiológica , AgriculturaRESUMO
Rice-wheat (RW) cropping systems are integral to global food security. Despite being practiced for decades, Chinese RW cropping systems often suffer from low productivity and poor nitrogen use efficiency (NUE), reflecting management approaches that are not well-contextualized to region and season. Here, we develop the best management guides for N fertilizer in RW systems that are designed to help raise the productivity, NUE, and environmental sustainability of winter wheat over the long term. 2-year field experiments were conducted with four N fertilizer rates (0, 135, 180, and 225 kg N ha-1), allowing contrasts of yields, soil moisture, and NUE of wheat in RW in the humid climates zones on the Jianghan Plain. We compared RW systems with soybean/maize dryland wheat (DW) systems that are similarly endemic to China: after soybean/maize is harvested, soils are often drier compared with moisture content following rice harvest. With high seasonal N application rates (180-225 kg N ha-1), wheat crop yields increased by 24% in RW which were greater than comparable yields of wheat in DW, mainly due to greater kernels per spike in the former. Across treatments and years, N accumulation in plant tissue and kernel dry matter of DW was higher than that in RW, although mean agronomic efficiency of nitrogen (AEN) and physiological efficiency of nitrogen (PEN) of RW systems were greater. As N application rates increased from 135 to 225 kg ha-1, AEN and PEN of DW decreased but changed little for RW. Soil ammonium N was much lower than that of nitrate N; changes in NH4 + and NO3 - as a consequence of increasing N fertilization were similar for RW and DW. We recommend that tactical application of N fertilizer continue seasonally until midgrain filling for both the DW and RW systems. At fertilization rates above 180 kg N ha-1, yield responses disappeared but nitrate leaching increased significantly, suggesting declining environmental sustainability above this N ceiling threshold. Collectively, this study elicits many functional and agronomic trade-offs between yields, NUE, and environmental sustainability as a function of N fertilization. Our results show that yield and NUE responses measured as part of crop rotations are both more robust and more variable when derived over multiple seasons, management conditions, and sites.
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Intensive cereal production has brought about increasingly serious environmental threats, including global warming, environmental acidification, and water shortage. As an important grain producer in the world, the rice cultivation system in central China has undergone excessive changes in the past few decades. However, few articles focused on the environmental impacts of these shifts from the perspective of ecological footprints. In this study, a 2-year field trial was carried out in Hubei province, China, to gain insight into carbon footprint (CF), nitrogen footprint (NF), and water footprint (WF) performance. The three treatments were, namely, double-rice system (DR), ratoon rice system (RR), and rice-wheat system (RW). Results demonstrated that RR significantly increased the grain yield by 10.22-15.09% compared with DR, while there was no significant difference in the grain yield between RW and DR in 2018-2019. All of the calculation results by three footprint approaches followed the order: RR < RW < DR; meanwhile, RR was always significantly lower than DR. Methane and NH3 field emissions were the hotspots of CF and NF, respectively. Blue WF accounts for 40.90-42.71% of DR, which was significantly higher than that of RR and RW, primarily because DR needs a lot of irrigation water in both seasons. The gray WF of RW was higher than those of DR and RR, mainly due to the higher application rate of N fertilizer. In conclusion, RR possesses the characteristics of low agricultural inputs and high grain yield and can reduce CF, NF, and WF, considering the future conditions of rural societal developments and rapid demographic changes; we highlighted that the RR could be a cleaner and sustainable approach to grain production.
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Super hybrid rice genotypes have transformed the rate of genetic yield gain primarily due to intersubspecific heterosis, although the physiological basis underpinning this yield transformation has not been well quantified. We assessed the radiation use efficiency (RUE) and nitrogen use efficiency (NUE) of novel hybrid rice genotypes under four management practices representative of rice cropping systems in China. Y-liangyou 900 (YLY900), a new super hybrid rice widely adopted in China, was examined in field experiments conducted in Jingzhou and Suizhou, Hubei Province, China, from 2017 to 2020. Four management practices were conducted: nil fertilizer (CK), conventional farmer practice (FP), optimized cultivation with reduced nitrogen (OPT-N), and optimized cultivation with increased nitrogen (OPT+N). Yield differences across the treatment regimens were significant (p < 0.05). Grain yield of OPT+N in Jingzhou and Suizhou were 11 and 12 t ha-1, which was 14 and 27% greater than yields obtained under OPT-N and FP, respectively. Relative to OPT-N and FP, OPT+N had greater panicle numbers (9 and 18%), spikelets per panicle (7 and 12%), spikelets per unit area (17 and 32%), and total dry weight (9 and 19%). The average RUE of OPT+N was 2.7 g MJ-1, which was 5 and 9% greater than that of OPT-N and FP, respectively, due to higher intercepted photosynthetically active radiation (IPAR). The agronomic efficiency of applied N (AEN) of OPT+N was 17 kg grain kg-1 N, which was 9 and 68% higher than that of OPT-N and FP. These results show that close correlations exist between yield and both the panicles number (R 2 = 0.91) and spikelets per panicle (R 2 = 0.83) in OPT+N. We conclude that grain yields of OPT+N were associated with greater IPAR, RUE, and total dry matter. We suggest that integrated cropping systems management practices are conducive to higher grain yield and resource use efficiency through expansion of sink potential in super hybrid rice production.
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Transient and chronic waterlogging constrains crop production in many regions of the world. Here, we invoke a novel iTRAQ-based proteomic strategy to elicit protein synthesis and regulation responses to waterlogging in tolerant (XM 55) and sensitive genotypes (YM 158). Of the 7,710 proteins identified, 16 were distinct between the two genotypes under waterlogging, partially defining a proteomic basis for waterlogging tolerance (and sensitivity). We found that 11 proteins were up-regulated and 5 proteins were down-regulated; the former included an Fe-S cluster assembly factor, heat shock cognate 70, GTP-binding protein SAR1A-like and CBS domain-containing protein. Down-regulated proteins contained photosystem II reaction center protein H, carotenoid 9, 10 (9', 10')-cleavage dioxygenase-like, psbP-like protein 1 and mitochondrial ATPase inhibitor. We showed that nine proteins responded to waterlogging with non-cultivar specificity: these included 3-isopropylmalate dehydratase large subunit, solanesyl-diphosphate synthase 2, DEAD-box ATP-dependent RNA helicase 3, and 3 predicted or uncharacterized proteins. Sixteen of the 28 selected proteins showed consistent expression patterns between mRNA and protein levels. We conclude that waterlogging stress may redirect protein synthesis, reduce chlorophyll synthesis and enzyme abundance involved in photorespiration, thus influencing synthesis of other metabolic enzymes. Collectively, these factors accelerate the accumulation of harmful metabolites in leaves in waterlogging-susceptible genotypes. The differentially expressed proteins enumerated here could be used as biological markers for enhancing waterlogging tolerance as part of future crop breeding programs.
RESUMO
Yields of wheat crops that succeed rice paddy crops are generally low. To date, it has been unclear whether such low yields were due to rice paddies altering soil physical or mineral characteristics, or both. To investigate this quandary, we conducted field experiments in the Jianghan Plain to analyze differences in the spatial distribution of wheat roots between rice-wheat rotation (RW) and dryland-wheat rotations (DW) using a range of nitrogen treatments. Dryland wheat crops were preceded by either dryland soybean or corn in the prior summer. Biomass of wheat crops in RW systems was significantly lower than that of DW for all N fertilizer treatments, although optimal nitrogen management resulted in comparable wheat yields in both DW and RW. Soil saturated water capacity and non-capillary porosity were higher in DW than RW, whereas soil bulk density was higher in RW. Soil available nitrogen and organic matter were higher in DW than RW irrespective of N application, while soil available P and K were higher under RW both at anthesis and post-harvest stages. At anthesis, root length percentage (RLP) was more concentrated in surface layers (0-20 cm) in RW, whereas at 20-40 cm and 40-60 cm, RLP was higher in DW than RW for all N treatments. At maturity, RLP were ranked 0-20 > 20-40 > 40-60 cm under both cropping systems irrespective of N fertilization. Root length percentage and soil chemical properties at 0-20 cm were positively correlated (r = 0.79 at anthesis, r = 0.68 at post-harvest) with soil available P, while available N (r = -0.59) and soil organic matter (r = -0.39) were negatively correlated with RLP at anthesis. Nitrogen applied at 180 kg ha-1 in three unform amounts of 60 kg N ha-1 at sowing, wintering and jointing resulted in higher yields than other treatments for both cropping systems. Overall, our results suggest that flooding of rice paddies increased bulk density and reduced available nitrogen, inhibiting the growth and yield of subsequent wheat crops relative to rainfed corn or soybean crops.