Winter wheat yield improvement by genetic gain across different provinces in China

The replacement of winter wheat varieties has contributed significantly to yield improvement worldwide,with remarkable progress in China.Drawing on two sets of data,production yield from the National Bureau of Statistics of China and experimental yield from literature,this study aims to(1)illustrate the increasing patterns of production yield among different provinces from 1978 to 2018 in China,(2)explore the genetic gain in yield and yield relevant traits through the variety replacement based on experimental yield from 1937 to 2016 in China,and(3)compare the yield gap between experimental yield and production yield.The results show that both the production and experimental yields significantly increased along with the variety replacement.The national annual yield increase ratio for the production yield was 1.67%from 1978 to 2018,varying from 0.96%in Sichuan Province to 2.78%in Hebei Province;such ratio for the experimental yield was 1.13%from 1937 to 2016.The yield gap between experimental and production yields decreased from the 1970s to the 2010s.This study reveals significant increases in some yield components consequent to variety replacement,including thousand-grain weight,kernel number per spike,and grain number per square meter;however,no change is shown in spike number per square meter.The biomass and harvest index consistently and significantly increased,whereas the plant height decreased significantly.

A novel AgNPs/MOF substrate-based SERS sensor for high-sensitive on-site detection of wheat gluten

Gluten,known as the major allergen in wheat,has gained increasing concerns in industrialized countries,resulting in an urgent need for accurate,high-sensitive,and on-site detection of wheat gluten in complex food systems.Herein,we proposed a silver nanoparticles(AgNPs)/metal-organic framework(MOF)substrate-based surface-enhanced Raman scattering(SERS)sensor for the high-sensitive on-site detection of wheat gluten.The detection occurred on the newly in-situ synthesized AgNPs/MOF-modified SERS substrate,providing an enhancement factor(EF)of 1.89×10^(5).Benefitting from the signal amplification function of AgNPs/MOF and the superiority of SERS,this sensor represented high sensitivity performance and a wide detection range from 1×10^(-15)mol/L to 2×10^(-6)mol/L with a detection limit of 1.16×10^(-16)mol/L,which allowed monitoring the trace of wheat gluten in complex food system without matrix interference.This reliable sandwich SERS sensor may provide a promising platform for high-sensitive,accurate,and on-site detection of allergens in the field of food safety.

Effect of Ozone Treatment on Microbiological Properties of Stored Wheat

In this study, ozone gas was applied to samples of durum wheat stored in four experimental groups (durum wheat without any treatment for comparison, durum wheat treated with ozone, purified durum wheat, and purified durum wheat treated with ozone). Two groups were treated with ozone gas at 3 ppm concentration for 1 hour. Groups were then placed in air-tight glass jars and stored for 6 months at variable temperatures between 24.7°C to 34.8°C. Microbiological (total count bacteria, yeast/molds and coliform) and physical properties (moisture, color and ash) evaluated. Ozone application statistically caused a significant reduction in the numbers of bacteria, yeast, molds and coliforms. Ozone application, washing process and storage temperature are the major factors affecting the microbial counts. No significant differences were determined in moisture and ash contents of samples after ozone treatment. The color measurement results showed that color values of wheat samples were affected by ozone treatment, storage and washing.

Assessing the Efficacy of Wheat-Soybean Based Intercropping System at Different Plant Densities in Bambili, Cameroon

Wheat is one of the most important cereals in the world, serving as a staple for millions globally. In the wake of the geopolitical crisis between Russia and Ukraine, it has become incumbent for many countries to invest in wheat production. Improving cropping systems for wheat production is paramount. Intercropping cereals with legumes has tremendous advantages. Therefore, this study was designed to optimize wheat production by intercropping it with soybean at different densities. Between March and August 2023, a randomized complete block design trial was conducted in Bambili, North West of Cameroon with treatments T1 (wheat monocrop at 200,000 plants ha−1), T2 (soybean monocrop at 250,000 plants ha−1), T3 (200,000 wheat and 125,000 soybean ha−1), T4 (100,000 wheat and 250,000 soybean ha−1), T5 (200,000 wheat and 250,000 soybean ha−1) and T6 (100,000 wheat and 125,000 soybean ha−1). Results revealed that growth parameters of wheat were not significantly influenced by monocrop or intercrop. The yield of wheat was significantly higher in the monocrop than the intercrop treatments, with slight variation amongst the intercrop treatments. Soybean yield was higher in the monocrop than in the intercrop, with no variations amongst the intercrop treatments. Only the land equivalence ratio (LER) for T5 was greater than 1.0. The competitive ratio for T5 was 0.54 for wheat and 1.90 for soybean, comparatively lower than the other monocrop treatments. Intercropping wheat and soybean at 200,000:250,000 ratio is recommended.

Effect of Gum Arabic from Acacia senegal var. kerensis as an Improver on the Rheological Properties of Wheat Flour Dough

Dough improvers are substances with functional characteristics used in baking industry to enhance dough properties. Currently, the baking industry is faced with increasing demand for natural ingredients owing to increasing consumer awareness, thus contributing to the rising demand for natural hydrocolloids. Gum Arabic from Acacia senegal var. kerensis is a natural gum exhibiting excellent water binding and emulsification capacity. However, very little is reported on how it affects the rheological properties of wheat dough. The aim of this study was therefore, to determine the rheological properties of wheat dough with partial additions of gum Arabic as an improver. Six treatments were analyzed comprising of: flour-gum blends prepared by adding gum Arabic to wheat flour at different levels (1%, 2% and 3%), plain wheat flour (negative control), commercial bread flour and commercial chapati flour (positive controls). The rheological properties were determined using Brabender Farinograph, Brabender Extensograph and Brabender Viscograph. Results showed that addition of gum Arabic significantly (p chapati. These findings support the need to utilize gum Arabic from Acacia senegal var. kerensis as a dough improver.

The Advantages of Methane Production by Combined Fermentation of Lignite and Wheat Straw

Biogasification of coal is important for clean utilization of coal. Experiments on the fermentation of single lignite, single straw and their mixture were performed to explore the variation characteristics of gas production potential, microbial community and methanogenic metabolic pathways of mixture. Research has shown that mixed fermentation of lignite and straw significantly promoted biomethane production. The abundance of hydrolytic acidifying functional bacteria genera (Sphaerochaeta, Lentimicrobium) in mixed fermentation was higher than that in the fermentation of single lignite and single straw. The abundance of some key CAZy metabolic enzyme gene sequences in mixed fermentation group was increased, which was favorable to improve methane production. Aceticlastic methanogenesis was the most critical methanogenic pathway and acetic acid pathway was more competitive in methanogenic mode during peak fermentation. Macrogenomics provided theoretical support for the claim that mixed fermentation of coal and straw promoted biomethane metabolism, which was potentially valuable in expanding methanogenesis from mixed fermentation of lignite with different biomasses.

Genome-wide association study of grain micronutrient concentrations in bread wheat

Bread wheat(Triticum aestivum)is a staple food crop worldwide.The genetic dissection of important nutrient traits is essential for the biofortification of wheat to meet the nutritional needs of the world's growing population.Here,45,298 single-nucleotide polymorphisms(SNPs)from 55K chip arrays were used to genotype a panel of 768 wheat cultivars,and a total of 154 quantitative trait loci(QTLs)were detected for eight traits under three environments by genome-wide association study(GWAS).Three QTLs(qMn-3B.1,qFe-3B.4,and qSe-3B.1/qFe-3B.6)detected repeatedly under different environments or traits were subjected to subsequent analyses based on linkage disequilibrium decay and the P-values of significant SNPs.Significant SNPs in the three QTL regions formed six haplotypes for qMn-3B.1,three haplotypes for qFe-3B.4,and three haplotypes for qSe-3B.1/qFe-3B.6.Phenotypic analysis revealed significant differences among haplotypes.These results indicated that the concentrations of several nutrient elements have been modified during the domestication of landraces to modern wheat.Based on the QTL regions,we identified 15 high-confidence genes,eight of which were stably expressed in different tissues and/or developmental stages.TraesCS3B02G046100 in qMn-3B.1 and TraesCS3B02G199500 in qSe-3B.1/qFe-3B.6 were both inferred to interact with metal ions according to the Gene Ontology(GO)analysis.TraesCS3B02G199000,which belongs to qSe-3B.1/qFe-3B.6,was determined to be a member of the WRKY gene family.Overall,this study provides several reliable QTLs that may significantly affect the concentrations of nutrient elements in wheat grain,and this information will facilitate the breeding of wheat cultivars with improved grain properties.

Transcriptomic and metabolomic analysis provides insights into lignin biosynthesis and accumulation and differences in lodging resistance in hybrid wheat

The use of hybrid wheat is one way to improve the yield in the future.However,greater plant heights increase lodging risk to some extent.In this study,two hybrid combinations with differences in lodging resistance were used to analyze the stem-related traits during the filling stage,and to investigate the mechanism of the difference in lodging resistance by analyzing lignin synthesis of the basal second internode(BSI).The stem-related traits such as the breaking strength,stem pole substantial degree(SPSD),and rind penetration strength(RPS),as well as the lignin content of the lodging-resistant combination(LRC),were significantly higher than those of the lodgingsensitive combination(LSC).The phenylpropanoid biosynthesis pathway was significantly and simultaneously enriched according to the transcriptomics and metabolomics analysis at the later filling stage.A total of 35 critical regulatory genes involved in the phenylpropanoid pathway were identified.Moreover,42%of the identified genes were significantly and differentially expressed at the later grain-filling stage between the two combinations,among which more than 80%were strongly up-regulated at that stage in the LRC compared with LSC.On the contrary,the LRC displayed lower contents of lignin intermediate metabolites than the LSC.These results suggested that the key to the lodging resistance formation of LRC is largely the higher lignin synthesis at the later grain-filling stage.Finally,breeding strategies for synergistically improving plant height and lodging resistance of hybrid wheat were put forward by comparing the LRC with the conventional wheat applied in large areas.

Epigenetic control on transcription of vernalization genes and whole-genome gene expression profile induced by vernalization in common wheat

Vernalization is necessary for winter wheat to flower.However,it is unclear whether vernalization is also required for spring wheat,which is frequently sown in fall,and what molecular mechanisms underlie the vernalization response in wheat varieties.In this study,we examined the molecular mechanisms that regulate vernalization response in winter and spring wheat varieties.For this purpose,we determined how major vernalization genes(VRN1,VRN2,and VRN3)respond to vernalization in these varieties and whether modifications to histones play a role in changes in gene expression.We also identified genes that are differentially regulated in response to vernalization in winter and spring wheat varieties.We found that in winter wheat,but not in spring wheat,VRN1 expression decreases when returned to warm temperature following vernalization.This finding may be associated with differences between spring and winter wheat in the levels of tri-methylation of lysine 27 on histone H3(H3K27me3)and tri-methylation of lysine 4 on histone H3(H3K4me3)at the VRN1 gene.Analysis of winter wheat transcriptomes before and after vernalization revealed that vernalization influences the expression of several genes,including those involved in leucine catabolism,cysteine biosynthesis,and flavonoid biosynthesis.These findings provide new candidates for further study on the mechanism of vernalization regulation in wheat.

Creating large EMS populations for functional genomics and breeding in wheat

Wheat germplasm is a fundamental resource for basic research,applied studies,and wheat breeding,which can be enriched normally by several paths,such as collecting natural lines,accumulating breeding lines,and introducing mutagenesis materials.Ethyl methane sulfonate(EMS)is an alkylating agent that can effectively introduce genetic variations in a wide variety of plant species.In this study,we created a million-scale EMS population(MEP)that started with the Chinese wheat cultivars‘Luyan 128’,‘Jimai 38’,‘Jimai 44’,and‘Shannong 30’.In the M1 generation,the MEP had numerous phenotypical variations,such as>3,000 chlorophyll-deficient mutants,2,519 compact spikes,and 1,692 male sterile spikes.There were also rare mutations,including 30 independent tillers each with double heads.Some M1 variations of chlorophyll-deficiency and compact spikes were inheritable,appearing in the M2 or M3 generations.To advance the entire MEP to higher generations,we adopted a single-seed descendent(SSD)approach.All other seed composites of M2 were used to screen other agronomically important traits,such as the tolerance to herbicide quizalofop-P-methyl.The MEP is available for collaborative projects,and provides a valuable toolbox for wheat genetics and breeding for sustainable agriculture.

Effects of dense planting patterns on photosynthetic traits of different vertical layers and yield of wheat under different nitrogen rates

A two-year field experiment was conducted to measure the effects of densification methods on photosynthesis and yield of densely planted wheat.Inter-plant and inter-row distances were used to define ratefixed pattern(RR)and row-fixed pattern(RS)density treatments.Meanwhile,four nitrogen(N)rates(0,144,192,and 240 kg N ha-1,termed N0,N144,N192,and N240)were applied with three densities(225,292.5,and 360×10^(4)plants ha^(-1),termed D225,D292.5,and D360).The wheat canopy was clipped into three equal vertical layers(top,middle,and bottom layers),and their chlorophyll density(Ch D)and photosynthetically active radiation interception(FIPAR)were measured.Results showed that the response of Ch D and FIPAR to N rate,density,and pattern varied with different layers.N rate,density,and pattern had significant interaction effects on Ch D.The maximum values of whole-canopy Ch D in the two seasons appeared in N240 combined with D292.5 and D360 under RR,respectively.Across two growing seasons,FIPAR values of RR were higher than those of RS by 29.37%for the top layer and 5.68%for the middle layer,while lower than those of RS by 20.62%for the bottom layer on average.With a low N supply(N0),grain yield was not significantly affected by density for both patterns.At N240,increasing density significantly increased yield under RR,but D360 of RS significantly decreased yield by 3.72%and 9.00%versus D225 in two seasons,respectively.With an appropriate and sufficient N application,RR increased the yield of densely planted wheat more than RS.Additionally,the maximum yield in two seasons appeared in the combination of D360 with N144 or N192 rather than of D225 with N240 under both patterns,suggesting that dense planting combined with an appropriate N-reduction application is feasible to increase photosynthesis capacity and yield.

Night warming increases wheat yield by improving pre-anthesis plant growth and post-anthesis grain starch biosynthesis

Global climate change is characterized by asymmetric warming,i.e.,greater temperature increases in winter,spring,and nighttime than in summer,autumn,and daytime.Field experiments were conducted using four wheat cultivars,namely‘Yangmai 18’(YM18),‘Sumai 188’(SM188),‘Yannong 19’(YN19),and‘Annong 0711’(AN0711),in the two growing seasons of 2019-2020 and 2020-2021,with passive night warming during different periods in the early growth stage.The treatments were night warming during the tillering-jointing(NW_(T-J)),jointing-booting(NWJ-B),and booting-anthesis(NWB-A)stages,with ambient temperature(NN)as the control.The effects of night warming during different stages on wheat yield formation were investigated by determining the characteristics of dry matter accumulation and translocation,as well as sucrose and starch accumulation in wheat grains.The wheat yields of all four cultivars were significantly higher in NW_(T-J)than in NN in the 2-year experiment.The yield increases of semi-winter cultivars YN19 and AN0711 were greater than those of spring cultivars YM18 and SM188.Treatment NW_(T-J)increased wheat yield mainly by increasing the 1,000-grain weight and the number of fertile spikelets,and it increased dry matter accumulation in various organs of wheat at the anthesis and maturity stages by increasing the growth rate at the vegetative growth stage.The flag leaf and spike showed the largest increases in dry matter accumulation.NW_(T-J)also increased the grain sucrose and starch contents in the early and middle grain-filling stages,promoting yield formation.Overall,night warming between the tillering and jointing stages increased the pre-anthesis growth rate,and thus,wheat dry matter production,which contributed to an increase in wheat yield.

Genome-wide association study of seedling nitrogen-use efficiency-associated traits in common wheat(Triticum aestivum L.)

Nitrogen(N)fertilizer application is essential for crop-plant growth and development.Identifying genetic loci associated with N-use efficiency(NUE)could increase wheat yields and reduce environmental pollution caused by overfertilization.We subjected a panel of 389 wheat accessions to N and chlorate(a nitrate analog)treatments to identify quantitative trait loci(QTL)controlling NUE-associated traits at the wheat seedling stage.Genotyping the panel with a 660K single-nucleotide polymorphism(SNP)array,we identified 397 SNPs associated with N-sensitivity index and chlorate inhibition rate.These SNPs were merged into 49 QTL,of which eight were multi-environment stable QTL and 27 were located near previously reported QTL.A set of 135 candidate genes near the 49 QTL included TaBOX(F-box family protein)and TaERF(ethylene-responsive transcription factor).A Tabox mutant was more sensitive to low-N stress than the wild-type plant.We developed two functional markers for Hap 1,the favorable allele of TaBOX.

The first factor affecting dryland winter wheat grain yield under various mulching measures: Spike number

Water is the key factor limiting dryland wheat grain yield.Mulching affects crop yield and yield components by affecting soil moisture.Further research is needed to determine the relationships between yield components and soil moisture with yield,and to identify the most important factor affecting grain yield under various mulching measures.A long-term 9-yearifeld experiment in the Loess Plateau of Northwest China was carried out with three treatments:no mulch (CK),plastic mulch (M_(P)) and straw mulch (M_(S)).Yield factors and soil moisture were measured,and the relationships between them were explored by correlation analysis,structural equation modeling and significance analysis.The results showed that compared with CK,the average grain yields of M_(P) and M_(S) increased by 13.0and 10.6%,respectively.The average annual grain yield of the M_(P) treatment was 134 kg ha^(–1) higher than the M_(S) treatment.There were no significant differences in yield components among the three treatments (P<0.05).Soil water storage of the M_(S) treatment was greater than the M_(P) treatment,although the differences were not statistically signifiant.Soil water storage during the summer fallow period (SWSSF) and soil water storage before sowing (SWSS) of M_(S) were significantly higher than in CK,which increased by 38.5 and 13.6%,respectively.The relationship between M_(P) and CK was not statistically significant for SWSSF,but the SWSS in M_(P) was significantly higher than in CK.In terms of soil water storage after harvest (SWSH) and water consumption in the growth period(ET),there were no signi?cant differences among the three treatments.Based on the three analysis methods,we found that spike number and ET were positively correlated with grain yield.However,the relative importance of spike number to yield was the greatest in the M_(P )and M_(S) treatments,while that of ET was the greatest in CK.Suifcient SWSSF could indirectly increase spike number and ET in the three treatments.Based on these results,mulch can improve yield and soil water storage.The most important factor affecting the grain yield of dryland wheat was spike number under mulching,and ET with CK.These findings may help us to understand the main factors influencing dryland wheat grain yield under mulching conditions compared to CK.

Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.

Effect of No Tillage and Conventional Tillage on Wheat Grain Yield Variability: A Review

Conservation Agriculture(CA)covers more than 205 million hectares in the world.This made it possible to face and mitigate the challenges of climate change,reducing soil erosion and providing multiple ecosystem services.The first elementary factor influenced is the yield evaluation.It has a direct effect on farmers’choices for sustainable production.The present article records a review focused on wheat yield average positive change compared between conventional tillage(CT)and no tillage(NT)systems.The international database collected showed that NT is adaptable everywhere.The results of wheat yield differentiation showed the influence of crop rotation depending on stations located in different climatic zones.In more than 40 years of research,specialists have succeeded in demonstrating the importance of crop productivity like wheat.The whole integrates also experimentations where the initiation starts more than ten years.

A Novel Deep Learning-Based Model for Classification of Wheat Gene Expression

Deep learning(DL)plays a critical role in processing and converting data into knowledge and decisions.DL technologies have been applied in a variety of applications,including image,video,and genome sequence analysis.In deep learning the most widely utilized architecture is Convolutional Neural Networks(CNN)are taught discriminatory traits in a supervised environment.In comparison to other classic neural networks,CNN makes use of a limited number of artificial neurons,therefore it is ideal for the recognition and processing of wheat gene sequences.Wheat is an essential crop of cereals for people around the world.Wheat Genotypes identification has an impact on the possible development of many countries in the agricultural sector.In quantitative genetics prediction of genetic values is a central issue.Wheat is an allohexaploid(AABBDD)with three distinct genomes.The sizes of the wheat genome are quite large compared to many other kinds and the availability of a diversity of genetic knowledge and normal structure at breeding lines of wheat,Therefore,genome sequence approaches based on techniques of Artificial Intelligence(AI)are necessary.This paper focuses on using the Wheat genome sequence will assist wheat producers in making better use of their genetic resources and managing genetic variation in their breeding program,as well as propose a novel model based on deep learning for offering a fundamental overview of genomic prediction theory and current constraints.In this paper,the hyperparameters of the network are optimized in the CNN to decrease the requirement for manual search and enhance network performance using a new proposed model built on an optimization algorithm and Convolutional Neural Networks(CNN).

Model Agnostic Meta-Learning(MAML)-Based Ensemble Model for Accurate Detection of Wheat Diseases Using Vision Transformer and Graph Neural Networks

Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease management.With advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a challenge.This challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease pathogens.In this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data scarcity.This study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural Networks.This paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate classification.The proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens detection.In future,more diseases can be included for detection along with some other modalities like pests and weed.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Subsoil tillage enhances wheat productivity,soil organic carbon and available nutrient status in dryland fields

Tillage practices during the fallow period benefit water storage and yield in dryland wheat crops.However,there is currently no clarity on the responses of soil organic carbon(SOC),total nitrogen(TN),and available nutrients to tillage practices within the growing season.This study evaluated the effects of three tillage practices(NT,no tillage;SS,subsoil tillage;DT,deep tillage)over five years on soil physicochemical properties.Soil samples at harvest stage from the fifth year were analyzed to determine the soil aggregate and aggregate-associated C and N fractions.The results indicated that SS and DT improved grain yield,straw biomass and straw carbon return of wheat compared with NT.In contrast to DT and NT,SS favored SOC and TN concentrations and stocks by increasing the soil organic carbon sequestration rate(SOCSR)and soil nitrogen sequestration rate(TNSR)in the 0-40 cm layer.Higher SOC levels under SS and NT were associated with greater aggregate-associated C fractions,while TN was positively associated with soluble organic nitrogen(SON).Compared with DT,the NT and SS treatments improved soil available nutrients in the 0-20 cm layer.These findings suggest that SS is an excellent practice for increasing soil carbon,nitrogen and nutrient availability in dryland wheat fields in North China.