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.

Selenium species transforming along soil–plant continuum and their beneficial roles for horticultural crops

Selenium(Se)acquirement from daily diet can help reduce the risk of many diseases.The edible parts of crop plants are the main source of dietary Se,while the Se content in crops is determined by Se bioavailability in soil.We summarize recent research on the biogeochemical cycle of Se driven by specific microorganisms and emphasize the oxidizing process in the Se cycle.Moreover,we discuss how plant root exudates and rhizosphere microorganisms affect soil Se availability.Finally,we cover beneficial microorganisms,including endophytes,that promote crop quality and improve crop tolerance to environmental stresses.Se availability to plants depends on the balance between adsorption and desorption,reduction,methylation and oxidation,which are determined by interactions among soil properties,microbial communities and plants.Reduction and methylation processes governed by bacteria or fungi lead to declined Se availability,while Se oxidation regulated by Se-oxidizing microorganisms increases Se availability to plants.Despite a much lower rate of Se oxidization compared to reduction and methylation,the potential roles of microbial communities in increasing Se bioavailability are probably largely underestimated.Enhancing Se oxidation and Se desorption are crucial for the promotion of Se bioavailability and uptake,particularly in Se-deficient soils.Beneficial roles of Se are reported in terms of improved crop growth and quality,and enhanced protection against fungal diseases and abiotic stress through improved photosynthetic traits,increased sugar and amino acid contents,and promoted defense systems.Understanding Se transformation along the plant-soil continuum is crucial for agricultural production and even for human health.

Feeding the world: impacts of elevated [CO_(2)] on nutrient content of greenhouse grown fruit crops and options for future yield gains

Several long-term studies have provided strong support demonstrating that growing crops under elevated[CO_(2)]can increase photosynthesis and result in an increase in yield,flavour and nutritional content(including but not limited to Vitamins C,E and pro-vitamin A).In the case of tomato,increases in yield by as much as 80%are observed when plants are cultivated at 1000 ppm[CO_(2)],which is consistent with current commercial greenhouse productionmethods in the tomato fruit industry.These results provide a clear demonstration of the potential for elevating[CO_(2)]for improving yield and quality in greenhouse crops.The major focus of this review is to bring together 50 years of observations evaluating the impact of elevated[CO_(2)]on fruit yield and fruit nutritional quality.In the final section,we consider the need to engineer improvements to photosynthesis and nitrogen assimilation to allow plants to take greater advantage of elevated CO_(2) growth conditions.

Oil Crops:A Potential Source of Biodiesel

1.Introduction Oil crops such as soybeans,sunflower,canola,rapeseed,and peanuts play a vital role in the agricultural economy,second only to food crops in terms of area and yield.Vegetable oil is known for its high energy density,containing approximately 2.25 times more calories per unit mass than carbohydrates or protein.Therefore,vegetable oil is an important source of energy and provides a variety of fatty acids necessary for human health.

Germplasm and molecular breeding in horticultural crops

Horticulture is an important part of agricultural planting and production, which is of great significance for enriching human nutrition and beautifying and transforming the human living environment. At present, the area of horticultural crops in China is about 40 million ha, accounting for about onefourth of the national crop planting area, while the production of primary agricultural products is 1 billion tons, and the output value accounts for more than half of the total output value of the planting industry.

DNA cytosine methylation dynamics and functional roles in horticultural crops

Methylation of cytosine is a conserved epigenetic modification that maintains the dynamic balance of methylation in plants under the regulation of methyltransferases and demethylases.In recent years,the study of DNA methylation in regulating the growth and development of plants and animals has become a key area of research.This review describes the regulatory mechanisms of DNA cytosine methylation in plants.It summarizes studies on epigenetic modifications of DNA methylation in fruit ripening,development,senescence,plant height,organ size,and under biotic and abiotic stresses in horticultural crops.The review provides a theoretical basis for understanding the mechanisms of DNA methylation and their relevance to breeding,genetic improvement,research,innovation,and exploitation of new cultivars of horticultural crops.

Designing of future ornamental crops: a biotechnological driven perspective

With a basis in human appreciation of beauty and aesthetic values,the new era of ornamental crops is based on implementing innovative technologies and transforming symbols into tangible assets.Recent advances in plant biotechnology have attracted considerable scientific and industrial interest,particularly in terms ofmodifying desired plant traits and developing future ornamental crops.By utilizing omics approaches,genomic data,genetic engineering,and gene editing tools,scientists have successively explored the underlying molecular mechanism and potential gene(s)behind trait regulation such as floral induction,plant architecture,stress resistance,plasticity,adaptation,and phytoremediation in ornamental crop species.These signs of progress lay a theoretical and practical foundation for designing and enhancing the efficiency of ornamental plants for a wide range of applications.In this review,we briefly summarized the existing literature and advances in biotechnological approaches for the improvement of vital traits in ornamental plants.The future ornamental plants,such as light-emitting plants,biotic/abiotic stress detectors,and pollution abatement,and the introduction of new ornamental varieties via domestication of wild species are also discussed.

Genic male and female sterility in vegetable crops

Vegetable crops are greatly appreciated for their beneficial nutritional and health components.Hybrid seeds are widely used in vegetable crops for advantages such as high yield and improved resistance,which require the participation of male(stamen)and female(pistil)reproductive organs.Male-or female-sterile plants are commonly used for production of hybrid seeds or seedless fruits in vegetables.In this review we will focus on the types of genic male sterility and factors affecting female fertility,summarize typical gene function and research progress related to reproductive organ identity and sporophyte and gametophyte development in vegetable crops[mainly tomato(Solanum lycopersicum)and cucumber(Cucumis sativus)],and discuss the research trends and application perspectives of the sterile trait in vegetable breeding and hybrid production,in order to provide a reference for fertility-related germplasm innovation.

Multi-omics-driven development of alternative crops for natural rubber production

Natural rubber(NR)is an irreplaceable biopolymer of economic and strategic importance owing to its unique physical and chemical properties.The Parárubber tree(Hevea brasiliensis(Willd.ex A.Juss.)Müll.Arg.)is currently the exclusive commercial source of NR,and it is primarily grown in plantations restricted to the tropical and subtropical areas of Southeast Asia.However,current Parárubber production barely meets the sharply increasing global industrial demand for rubber.Petroleum-based synthetic rubber(SR)has been used to supplement the shortage of NR but its industrial performance is not comparable to that of NR.Thus,there is an urgent need to develop new productive rubber crops with broader environmental adaptability.This review summarizes the current research progress on alternative rubberproducing plants,including horticultural plants(Taraxacum kok-saghyz Rodin and Lactuca L.species),woody plants(Parthenium argentatum A.Gray and Eucommia ulmoides Oliv.),and other plant species with potential for NR production.With an emphasis on the molecular basis of NR biosynthesis revealed by a multi-omics approach,we highlight new integrative strategies and biotechnologies for exploring the mechanism of NR biosynthesis with a broader scope,which may accelerate the breeding and improvement of new rubber crops.

Crops Leaf Diseases Recognition:A Framework of Optimum Deep Learning Features

Manual diagnosis of crops diseases is not an easy process;thus,a computerized method is widely used.Froma couple of years,advancements in the domain ofmachine learning,such as deep learning,have shown substantial success.However,they still faced some challenges such as similarity in disease symptoms and irrelevant features extraction.In this article,we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases recognition.The proposed architecture consists of five steps.In the first step,data augmentation is performed to increase the numbers of training samples.In the second step,pre-trained DarkNet19 deep model is opted and fine-tuned that later utilized for the training of fine-tuned model through transfer learning.Deep features are extracted from the global pooling layer in the next step that is refined using Improved Cuckoo search algorithm.The best selected features are finally classified using machine learning classifiers such as SVM,and named a few more for final classification results.The proposed architecture is tested using publicly available datasets–Cucumber National Dataset and Plant Village.The proposed architecture achieved an accuracy of 100.0%,92.9%,and 99.2%,respectively.Acomparison with recent techniques is also performed,revealing that the proposed method achieved improved accuracy while consuming less computational time.

Modified Metaheuristics with Transfer Learning Based Insect Pest Classification for Agricultural Crops

Crop insect detection becomes a tedious process for agronomists because a substantial part of the crops is damaged,and due to the pest attacks,the quality is degraded.They are the major reason behind crop quality degradation and diminished crop productivity.Hence,accurate pest detection is essential to guarantee safety and crop quality.Conventional identification of insects necessitates highly trained taxonomists to detect insects precisely based on morphological features.Lately,some progress has been made in agriculture by employing machine learning(ML)to classify and detect pests.This study introduces a Modified Metaheuristics with Transfer Learning based Insect Pest Classification for Agricultural Crops(MMTL-IPCAC)technique.The presented MMTL-IPCAC technique applies contrast limited adaptive histogram equalization(CLAHE)approach for image enhancement.The neural architectural search network(NASNet)model is applied for feature extraction,and a modified grey wolf optimization(MGWO)algorithm is employed for the hyperparameter tuning process,showing the novelty of the work.At last,the extreme gradient boosting(XGBoost)model is utilized to carry out the insect classification procedure.The simulation analysis stated the enhanced performance of the MMTL-IPCAC technique in the insect classification process with maximum accuracy of 98.73%.

Prediction of Suitable Crops Using Stacked Scaling Conjugant Neural Classifier

Agriculture plays a vital role in economic development.The major pro-blem faced by the farmers are the selection of suitable crops based on environ-mental conditions such as weather,soil nutrients,etc.The farmers were following ancestral patterns,which could sometimes lead to the wrong selection of crops.In this research work,the feature selection method is adopted to improve the performance of the classification.The most relevant features from the dataset are obtained using a Probabilistic Feature Selection(PFS)approach,and classifi-cation is done using a Neural Fuzzy Classifier(NFC).Scaling Conjugate Gradient(SCG)optimization method is used to update the weights.The data set used for analysis contain various parameters such as soil characteristics,geographical loca-tion,and environmental factors such as temperature and rainfall.The proposed method recommends suitable crops for cultivation based on site-specific para-meters.Experimental result shows that the proposed method provides high accu-racy and efficiency as compared to existing methodologies.

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.

Impacts of climate change on the yields of leguminous crops in the Guinea Savanna agroecological zone of Ghana

The impacts of climate change on crop yields are receiving renewed interest,with focus on cereals and staple crops at the regional and national scales.Yet,the impacts of climate change on the yields of leguminous crops in the local context has not been explored.Thus,an in-depth understanding of climate change in the local context may support the design of locally relevant adaptation responses to current and future climate risks.This study examined the impacts of climate variables(annual rainfall,annual average temperature,rainfall indices(rainfall onset,rainfall cessation,and the length of rainy days),and the number of dry days)on the yields of leguminous crops(groundnuts,cowpeas,and soybeans)in the Guinea Savanna agroecological zone of Ghana during the period of 1989-2020.The data were analysed using Mann-Kendall’s trend,Sen’s slope test,correlation analysis,and Multiple Regression Analysis(MRA).The findings revealed that annual rainfall,annual average temperature,rainfall onset,rainfall cessation,and the length of rainy days,and the number of dry days all showed varied impacts on the yields of groundnuts,cowpeas,and soybeans.The trend analysis detected a marginal decrease in the amount of rainfall,rainfall onset,and the number of dry days from 1989 to 2020(P>0.050).Annual average temperature and the length of rainy days substantially varied(P<0.050)from 1989 to 2020,showing an increasing trend.The findings also showed a marked upward trend for the yields of groundnuts,cowpeas,and soybeans during 2005-2020.The climate variables analysed above increased the yields of groundnuts,cowpeas,and soybeans by 49.0%,55.0%,and 69.0%,respectively.The yields of groundnuts,cowpeas,and soybeans fluctuated with the variability of 30.0%,28.0%,and 27.0%from 2005 to 2020,respectively.The three leguminous crops under study demonstrated unpredictable yields due to the variations of annual rainfall,annual average temperature,rainfall onset,rainfall cessation,the length of rainy days,and the number of dry days,which stressed the need for agricultural diversification,changing planting dates,using improved seed variety,and irrigation to respond to climate change.The results of this study implied that climate change considerably impacts crop production in the Guinea Savanna agroecological zone of Ghana,emphasizing the urgency of locally based and farmer-induced adaptation measures for food security and resilient agricultural systems.

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.

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.

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.

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.