A dual-RPA based lateral flow strip for sensitive,on-site detection of CP4-EPSPS and Cry1Ab/Ac genes in genetically modified crops

Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.

Adding Value to Crop Production Systems by Integrating Forage Cover Crop Grazing

In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance was compared in the spring following autumn establishment as for age cover crops after soybean [Glycine max (L.) Merr.] grain harvest. Replicated pastures (0.4 ha) were no-till seeded in three consecutive years into soybean stubble in autumn, fertilized, and grazed the following spring near Ithaca, NE, USA. Each pasture (n = 3) was continuously stocked in spring with four yearling steers (380 ± 38 kg) for 17, 32, and 28 d in 2005, 2006, and 2007, respectively. In 2005, average daily gain (ADG) for steers grazing triticale exceeded the ADG for wheat by 0.31 kghd-1d-1. In 2006, wheat ADG exceeded that for triticale by 0.12 kghd-1d-1. In 2007, steers grazing wheat lost weight, while steers grazing triticale gained 0.20 kghd-1d-1. Based on the 3-year average animal gains valued at $1.32 kg-1, mean net return ($ ha-1 yr-1) was $62.15 for triticale and $22.55 for wheat. Since these grazed cover crops provide ecosystem services in addition to forage, grazing could be viewed as a mechanism for recovering costs and adds additional value to the system. Based on this 3-year grazing trial, triticale was superior to wheat and likely will provide the most stable beef yearling performance across years with variable weather for the western Cornbelt USA.

Straw return increases crop production by improving soil organic carbon sequestration and soil aggregation in a long-term wheat-cotton cropping system

Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.

Assessment of Crop Yield in China Simulated by Thirteen Global Gridded Crop Models

Global gridded crop models(GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national-and provincial-scale evaluation of the simulations by13 GGCMs [12 from the GGCM Intercomparison(GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops(wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national-and provincial-scale crop yield prediction in China.

The multiple roles of crop structural change in productivity,nutrition and environment in China:A decomposition analysis

China's crop structure has undergone significant changes in the last two decades since 2000,with an increase in the share of cereals,vegetables,and fruit,squeezing out other crops.As a result,land productivity,nutrient supply,and carbon emissions have changed.How to reallocate limited farmland among crops to achieve the multiple goals of agrifood systems becomes an important issue.This study explores the sources of land productivity and nutrition supply growth and carbon emissions reduction,and identifies the multiple roles of crop structural change from 2003 to 2020 based on a decomposition analysis.The results reveal that the growth within crops is still the primary driver in land productivity and nutrition supply and the reduction in carbon emissions.However,structural change also plays various roles at different periods.From 2003 to 2010,crop structural change increased the total calorie supply but lowered land productivity and contributed at least 70%of the total growth of carbon emissions.The crop structure was relatively stable,and their effects were modest from 2010 to 2015.From 2015 to 2020,the crop structural change began to play a greater role and generate synergistic effects in improving land productivity,micronutrient supply,and reducing carbon emissions,contributing to approximately a quarter of the growth of land productivity and 30%of total carbon emissions reduction.These results suggest that strategies for crop structural change should comprehensively consider its multiple impacts,aiming to achieve co-benefits while minimizing trade-offs.

Nitrogen rhizodeposition from corn and soybean,and its contribution to the subsequent wheat crops

Nitrogen(N)is a key factor in the positive response of cereal crops that follow leguminous crops when compared to gramineous crops in rotations,with the nonrecyclable rhizosphere-derived N playing an important role.However,quantitative assessments of differences in the N derived from rhizodeposition(NdfR)between legumes and gramineous crops are lacking,and comparative studies on their contributions to the subsequent cereals are scarce.In this study,we conducted a meta-analysis of NdfR from leguminous and gramineous crops based on 34 observations published worldwide.In addition,pot experiments were conducted to study the differences in the NdfR amounts,distributions and subsequent effects of two major wheat(Triticum aestivum L.)-preceding crops,corn(Zea mays L.)and soybean(Glycine max L.),by the cotton wick-labelling method in the main wheat-producing areas of China.The meta-analysis results showed that the NdfR of legumes was significantly greater by 138.93%compared to gramineous crops.In our pot experiment,the NdfR values from corn and soybean were 502.32 and 944.12 mg/pot,respectively,and soybean was also significantly higher than corn,accounting for 76.91 and 84.15%of the total belowground nitrogen of the plants,respectively.Moreover,in different soil particle sizes,NdfR was mainly enriched in the large macro-aggregates(>2 mm),followed by the small macro-aggregates(2–0.25 mm).The amount and proportion of NdfR in the macro-aggregates(>0.25 mm)of soybean were 3.48 and 1.66 times higher than those of corn,respectively,indicating the high utilization potential of soybean NdfR.Regarding the N accumulation of subsequent wheat,the contribution of soybean NdfR to wheat was approximately 3 times that of corn,accounting for 8.37 and 4.04%of the total N uptake of wheat,respectively.In conclusion,soybean NdfR is superior to corn in terms of the quantity and distribution ratio of soil macro-aggregates.In future field production,legume NdfR should be included in the nitrogen pool that can be absorbed and utilized by subsequent crops,and the role and potential of leguminous plants as nitrogen source providers in crop rotation systems should be fully utilized.

Coordinated responses of leaf and nodule traits contribute to the accumulation of N in relay intercropped soybean

Maize(Zea mays L.)-soybean(Glycine max L.Merr.)relay intercropping provides a way to enhance land productivity.However,the late-planted soybean suffers from shading by the maize.After maize harvest,how the recovery growth influences the leaf and nodule traits remains unclear.A three-year field experiment was conducted to evaluate the effects of genotypes,i.e.,supernodulating(nts1007),Nandou 12(ND12),and Guixia 3(GX3),and crop configurations,i.e.,the interspecific row spacing of 45(I45),60(I60),75 cm(I75),and sole soybean(SS),on soybean recovery growth and N fixation.The results showed that intercropping reduced the soybean total leaf area(LA)by reducing both the leaf number(LN)and unit leaflet area(LUA),and it reduced the nodule dry weight(NW)by reducing both the nodule number(NN)and nodule diameter(ND)compared with the SS.The correlation and principal component analysis(PCA)indicated a co-variability of the leaf and nodule traits in response to the genotype and crop configuration interactions.During the recovery growth stages,the compensatory growth promoted soybean growth to reduce the gaps of leaf and nodule traits between intercropping and SS.The relative growth rates of ureide(RGR_U)and nitrogen(RGR_N)accumulation were higher in intercropping than in SS.Intercropping achieved more significant sucrose and starch contents compared with SS.ND12 and GX3 showed more robust compensatory growth than nts1007 in intercropping.Although the recovery growth of relay intercropping soybean improved biomass and nitrogen accumulation,ND12 gained a more significant partial land equivalent ratio(pLER)than GX3.The I60 treatment achieved more robust compensation effects on biomass and N accumulation than the other configurations.Meanwhile,I60 showed a higher nodule sucrose content and greater shoot ureide and N accumulation than SS.Finally,intercropping ND12 with maize using an interspecific row spacing of 60 cm was optimal for both yield advantage and N accumulation.

Characteristics of the microbial communities regulate soil multi-functionality under different cover crop amendments in Ultisol

The use of cover crops is a promising strategy for influencing the soil microbial consortium,which is essential for the delivery of multiple soil functions(i.e.,soil multifunctionality).Nonetheless,relatively little is known about the role of the soil microbial consortium in mediating soil multifunctionality under different cover crop amendments in dryland Ultisols.Here,we assessed the multifunctionality of soils subjected to four cover crop amendments(control,non-amended treatment;RD,radish monoculture;HV,hairy vetch monoculture;and RDHV,radish-hairy vetch mixture),and we investigated the contributions of soil microbial richness,network complexity,and ecological clusters to soil multifunctionality.Our results demonstrated that cover crops whose chemical composition differed from that of the main plant crop promoted higher multifunctionality,and the radish-hairy vetch mixture rendered the highest enhancement.We obtained evidence that changes in soil microbial richness and network complexity triggered by the cover crops were associated with higher soil multifunctionality.Specifically,specialized microbes in a key ecological cluster(ecological cluster 2)of the soil microbial network were particularly important for maintaining soil multifunctionality.Our results highlight the importance of cover crop-induced variations in functionally important taxa for promoting the soil multifunctionality of dryland Ultisols.

Optimization of inter-seasonal nitrogen allocation increases yield and resource-use efficiency in a water-limited wheat-maize cropping system in the North China Plain

Winter wheat–summer maize cropping system in the North China Plain often experiences droughtinduced yield reduction in the wheat season and rainwater and nitrogen(N)fertilizer losses in the maize season.This study aimed to identify an optimal interseasonal water-and N-management strategy to alleviate these losses.Four ratios of allocation of 360 kg N ha^(-1)between the wheat and maize seasons under one-time presowing root-zone irrigation(W0)and additional jointing and anthesis irrigation(W2)in wheat and one irrigation after maize sowing were set as follows:N1(120:240),N2(180:180),N3(240:120)and N4(300:60).The results showed that under W0,the N3 treatment produced the highest annual yield,crop water productivity(WPC),and nitrogen partial factor productivity(PFPN).Increased N allocation in wheat under W0 improved wheat yield without affecting maize yield,as surplus nitrate after wheat harvest was retained in the topsoil layers and available for the subsequent maize.Under W2,annual yield was largest in the N2 treatment.The risk of nitrate leaching increased in W2 when N application rate in wheat exceeded that of the N2 treatment,especially in the wet year.Compared to W2N2,the W0N3 maintained 95.2%grain yield over two years.The WPCwas higher in the W0 treatment than in the W2 treatment.Therefore,following limited total N rate,an appropriate fertilizer N transfer from maize to wheat season had the potential of a“triple win”for high annual yield,WPCand PFPN in a water-limited wheat–maize cropping system.

Comprehensive Overview and Analytical Study on Automatic Bird Repellent Laser System for Crop Protection

Birds are a huge hazard to agriculture all around the world,causing harm to profitable field crops.Growers use a variety of techniques to keep them away,including visual,auditory,tactile,and olfactory deterrents. This study presents a comprehensive overview of current bird repellant approaches used in agricultural contexts,as well as potential new ways. The bird repellent techniques include Internet of Things technology,Deep Learning,Convolutional Neural Network,Unmanned Aerial Vehicles,Wireless Sensor Networks and Laser biotechnology. This study’s goal is to find and review about previous approach towards repellent of birds in the crop fields using various technologies.

Research Progress on the Growth-Promoting Effect of Plant Biostimulants on Crops

A Plant Biostimulant is any substance or microorganism applied to plants to enhance nutrition efficiency,abioticstress tolerance,and/or crop quality traits,regardless of its nutrient content.The application of Plant biostimulants(PBs)in production can reduce the application of traditional pesticides and chemical fertilizers and improvethe quality and yield of crops,which is conducive to the sustainable development of agriculture.An in-depthunderstanding of the mechanism and effect of various PBs is very important for how to apply PBs reasonablyand effectively in the practice of crop production.This paper summarizes the main classification of PBs;Thegrowth promotion mechanism of PBs was analyzed from four aspects:improving soil physical and chemical properties,enhancing crop nutrient absorption capacity,photosynthesis capacity,and abiotic stress tolerance;At thesame time,the effects of PBs application on seed germination,seedling vigor,crop yield,and quality were summarized;Finally,how to continue to explore and study the use and mechanism of PBs in the future is analyzedand prospected,to better guide the application of PBs in crop production in the future.

Advanced Thermochemical Conversion Approaches for Green Hydrogen Production from Crop Residues

The huge volumes of crop residues generated during the production,processing,and consumption of farm products constitute an ecological nuisance when ineffectively managed.The conversion of crop residues to green hydrogen is one of the sustainable management strategies for ubiquitous crop residues.Production of green hydrogen from crop residue sources will contribute to deepening access to clean and affordable energy,mitigating climate change,and ensuring environmental sustainability.However,the deployment of conventional thermochemical technologies for the conversion of crop residues to green hydrogen is costly,requires long residence time,produces low-quality products,and therefore needs to be upgraded.The current review examines the conventional,advanced,and integrated thermochemical conversion technologies for crop residues for green hydrogen production.After a brief overview of the conventional thermochemical techniques,the review delves into the broad narration of advanced thermochemical technologies including catalytic pyrolysis,microwave pyrolysis,co-pyrolysis,hyropyrolysis,and autothermal pyrolysis.The study advocates the deployment of integrated pyrolysis,anaerobic digestion,pyrolysis,and gasification technologies will ensure scalability,decomposition of recalcitrant feedstocks,and generation of high grade green hydrogen.The outlook provides suggestions for future research into cost-saving and sustainable integrated technologies for green hydrogen production towards achieving carbon neutrality and a circular bio-economy.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

Impact on Soil Organic C and Total Soil N from Cool- and Warm-Season Legumes Used in a Green Manure-Forage Cropping System

Annual forage legumes are important components of livestock production systems in East Texas and the southeastern US. Forage legumes contribute nitrogen (N) to cropping systems through biological N fixation, and their seasonal biomass production can be managed to complement forage grasses. Our research objectives were to evaluate both warm- and cool-season annual forage legumes as green manure for biomass, N content, ability to enhance soil organic carbon (SOC) and soil N, and impact on post season forage grass crops. Nine warm-season forage legumes (WSL) were spring planted and incorporated as green manure in the fall. Forage rye (Secale cereale L.) was planted following the incorporation of WSL treatments. Eight cool-season forage legumes (CSL) were fall planted in previously fallow plots and incorporated as green manure in late spring. Sorghum-sudangrass (Sorghum bicolor x Sorghum bicolor var. sudanense) was planted over all treatments in early summer after forage rye harvest and incorporation of CSL treatments. Sorghum-sudangrass was harvested in June, August and September, and treatments were evaluated for dry matter and N concentration. Soil cores were taken from each plot, split into depths of 0 to 15, 15 to 30 and 30 to 60 cm, and soil C and N were measured using combustion analysis. Nylon mesh bags containing plant samples were buried at 15 cm and used to evaluate decomposition rate of above ground legume biomass, including change in C and N concentrations. Mungbean (Vigna radiata L. [Wilczek]) had the highest shoot biomass yield (6.24 t DM ha-1) and contributed the most total N (167 kg∙ha-1) and total C (3043 kg∙ha-1) of the WSL tested. Decomposition rate of WSL biomass was rapid in the first 10 weeks and very slow afterward. Winter pea (Pisum sativum L. spp. sativum), arrow leaf clover (Trifolium vesiculosum Savi.), and crimson clover (Trifolium incarnatum L.) were the most productive CSL in this trial. Austrian winter pea produced 8.41 t DM ha-1 with a total N yield of 319 kg N ha-1 and total C production of 3835 kg C ha-1. The WSL treatments had only small effects on rye forage yield and N concentration, possibly due to mineralization of N from a large SOC pool already in place. The CSL treatments also had only minimal effects on sorghum-sudangrass forage production. Winter pea, arrow leaf and crimson clover were productive cool season legumes and could be useful as green manure crops. Mungbean and cowpea (Vigna unguiculata [L.] Walp.) were highly productive warm season legumes but may include more production risk in green manure systems due to soil moisture competition.

Research Progress on Effects of Continuous Cropping on Soil Microbial Florae and Its Restoration

Continuous cropping has become a common form of agricultural production at present, but with the increase of continuous cropping years, continuous cropping obstacles such as soil-borne diseases and plant growth potential decline are becoming more and more common. At present, the causes of continuous cropping obstacles and continuous cropping restoration have become a hot issue in agricultural research. This paper summarized the effects of continuous cropping obstacles on soil microbial community structure and main technical methods to repair continuous cropping obstacles, such as agricultural measure management, microbial balance adjustment and soil improvement, aiming to provide theoretical reference for protecting the sustainable utilization of soil ecosystem and ensuring the stability of crop production.

A Germplasm Resource Repository:The Book Review of Illustrated Flora of Food Crops and Their Wild Related Plants in China

Illustrated Flora of Food Crops and Their Wild Related Plants in China systematically examines the botanical and morphological characteristics of China's major food crops,such as rice,wheat,corn,sweet potato,potato,mung bean,and buckwheat.Featuring more than 5000 color photos and 200 line drawings,it offers a comparative study that highlights the kinship and internal connections between cultivated and wild species.The book is an invaluable resource for breeders,offering a comprehensive morphological and genetic database that aids in the development of high-yielding,high-quality,and disease-resistant crop varieties.

Comparison of CWSI and T_(s)-T_(a)-VIs in moisture monitoring of dryland crops(sorghum and maize)based on UAV remote sensing

Monitoring agricultural drought using remote sensing data is crucial for precision irrigation in modern agriculture.Utilizing unmanned aerial vehicle(UAV)remote sensing,we explored the applicability of an empirical crop water stress index(CWSI)based on canopy temperature and three-dimensional drought indices(TDDI)constructed from surface temperature(T_(s)),air temperature(T_(a))and five vegetation indices(VIs)for monitoring the moisture status of dryland crops.Three machine learning algorithms(random forest regression(RFR),support vector regression,and partial least squares regression)were used to compare the performance of the drought indices for vegetation moisture content(VMC)estimation in sorghum and maize.The main results of the study were as follows:(1)Comparative analysis of the drought indices revealed that T_(s)-T_(a)-normalized difference vegetation index(TDDIn)and T_(s)-T_(a)-enhanced vegetation index(TDDIe)were more strongly correlated with VMC compared with the other indices.The indices exhibited varying sensitivities to VMC under different irrigation regimes;the strongest correlation observed was for the TDDIe index with maize under the fully irrigated treatment(r=-0.93).(2)Regarding spatial and temporal characteristics,the TDDIn,TDDIe and CWSI indices showed minimal differences Over the experimental period,with coefficients of variation were 0.25,0.18 and 0.24,respectively.All three indices were capable of effectively characterizing the moisture distribution in dryland maize and sorghum crops,but the TDDI indices more accurately monitored the spatial distribution of crop moisture after a rainfall or irrigation event.(3)For prediction of the moisture content of single crops,RFR models based on TDDIn and TDDIe estimated VMC most accurately(R^(2)>0.7),and the TDDIn-based model predicted VMC with the highest accuracy when considering multiple-crop samples,with R^(2)and RMSE of 0.62 and 14.26%,respectively.Thus,TDDI proved more effective than the CWSI in estimating crop water content.

Integration of Multiple Spectral Data via a Logistic Regression Algorithm for Detection of Crop Residue Burned Areas:A Case Study of Songnen Plain,Northeast China

The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate estimation of cropland burned area is both crucial and challenging,especially for the small and fragmented burned scars in China.Here we developed an automated burned area mapping algorithm that was implemented using Sentinel-2 Multi Spectral Instrument(MSI)data and its effectiveness was tested taking Songnen Plain,Northeast China as a case using satellite image of 2020.We employed a logistic regression method for integrating multiple spectral data into a synthetic indicator,and compared the results with manually interpreted burned area reference maps and the Moderate-Resolution Imaging Spectroradiometer(MODIS)MCD64A1 burned area product.The overall accuracy of the single variable logistic regression was 77.38%to 86.90%and 73.47%to 97.14%for the 52TCQ and 51TYM cases,respectively.In comparison,the accuracy of the burned area map was improved to 87.14%and 98.33%for the 52TCQ and 51TYM cases,respectively by multiple variable logistic regression of Sentind-2 images.The balance of omission error and commission error was also improved.The integration of multiple spectral data combined with a logistic regression method proves to be effective for burned area detection,offering a highly automated process with an automatic threshold determination mechanism.This method exhibits excellent extensibility and flexibility taking the image tile as the operating unit.It is suitable for burned area detection at a regional scale and can also be implemented with other satellite data.

Microplastic Can Decrease Enzyme Activities and Microbes in Soil

An in vitro study was conducted to investigate the impacts of microplastics on enzyme activities and soil bacteria. The study included four different treatments of microplastics including a control. Different levels of microplastics were applied to the soil ranging from 0% to 5%, to assess the impacts of microplastics on soil enzymes and subsequent soil bacteria. After 30 days of incubation, the soil samples were collected and growth parameters of bacteria were assessed. Activities of β-glucosidase, urease and dehydrogenase enzymes were also determined. Our results showed that the presence of microplastics in the soil significantly reduced bacterial population together with bacterial strains. The activities of β-glucosidase, urease and dehydrogenase enzymes were reduced significantly to approximately 32%, 40% and 50% in microplastics treated soils respectively. Concentration of microplastic has a role to play towards this direction;the higher the concentration of microplastic the greater is the impact on enzymes and soil bacteria. The present study on the microbial soil health vis-à-vis microplastic application indicates that the material can have negative effect on the soil bacterial population of and thus ultimately may jeopardize soil health and crop production.