Performance and stability of yield in response to plant density,year and location in maize hybrids of Northwest China

Identifying desirable genotypes with the best performance in diverse environments is a perpetual aim of plant breeding,and the interaction between genotype and environment(G×E)always plays a key role.This study was conducted to elucidate the genetic behaviour of different hybrid combinations at various densities in diverse environments.According to a line×tester design,32 hybrid combinations were obtained from 16 inbred individuals crossed with two testers and planted at three locations at three density levels(45,000,67,500 and 90,000 plants ha-1)during 2014-2017.Genotype(G),environment(E)and the interaction of genotype and environment(G×E)significantly affected grain yield at different densities.Increasing planting density enhanced grain yield and improved the efficiency of germplasm screening,where the effect of location on grain yield at different densities was larger than that of year and the GCA was larger than the SCA.Finally,four inbred lines(KB102,KB081,KA105,and KB106)with a high GCA,environmental adaptability,and several combinations using them as parents have been approved in ShannXi Province and National of China.In conclusion,the evaluation of combining ability at multiple densities and locations can effectively screen inbred lines and improve breeding efficiency.

Advanced technology in agronomy to secure food,fiber,feed,and fuel supply and maintain environmental sustainability

Corn,wheat,rice,soybean,cotton,rape seeds,alfalfa,and sugar beets are among the top agronomic crops grown around the world for food,fiber,feed,and fuel(4Fs).Huge progress has been made in increasing production of 4Fs over the last few decades.In 2018-2019,approximately 1.09 billion tons of corn,735 million tons of wheat,and 497 million tons of rice were produced worldwide.Increased food production has greatly helped to reduce global starvation and undernourished populations from 15%during 2000-2004 to 8.9%in 2019.

High-throughput estimation of plant height and above-ground biomass of cotton using digital image analysis and Canopeo

Plant height and above-ground biomass are important growth parameters that affect crop yield.Efficient and non-destructive technologies of crop phenotypic monitoring play crucial roles in intelligent farmland management.However,the feasibility of using these technologies to estimate cotton plant height and above-ground biomass has not been determined.This study proposed a low cost and high-throughput imaging method combined with Canopeo to extract the percentages of green color from high-definition digital images and establish a model to estimate the cotton plant height and above-ground biomass.The plant height and above-ground biomass field trials were conducted at two levels of irrigation(soil water content 70%±5% and 40%-45%,respectively)using 80 cotton genotypes.The linear fitting performed well across the different cotton genotypes(PH,R^(2)=0.9829;RMSE=2.4 cm;NRMSE=11%and AGB,R^(2)=0.9609;RMSE=0.6 g/plant;and NRMSE=5%),and two levels of irrigation(PH,R^(2)=0.9604;RMSE=2.15 cm;NRMSE=6%and AGB,R^(2)=0.9650;RMSE=4.51 g/plant;and NRMSE=17%).All reached a higher fitting degree.Additionally,the most comprehensive model to estimate the cotton plant height and above-ground biomass(Y=0.4832*X+11.04;Y=0.4621*X-0.3591)was determined using a simple linear regression modeling method.The percentages of green color positively correlated with plant height and above-ground biomass,and each model exhibited higher accuracy(R2≥0.8392,RMSE≤0.0158,NRMSE≤0.06%).Combining a high-definition digital camera with Canopeo enables the prediction of crop growth in the field.The simple linear regression modeling method and the most comprehensive model enable the rapid estimation of the cotton plant height and above-ground biomass.This method can also be used as a baseline to measure other important crop phenotypes.

Different developments of rice leaf and their response to nitrogen

The study evaluates and compares the leaf number(LN)of two rice types,Hybrid Indica(HI)and Japonica(J),and their response to three different nitrogen rates.A split plot experiment was conducted in Danyang District,Jiangsu Province in China,from 2017 to 2018 both rice growing seasons.It was carried out using the Transplanting machine,and the spacing was 17 cm×30 cm.A split zone design was adopted,with three different levels of nitrogen:N0-0,N1-150 kg hm^(-2) and N2-300 kg hm^(-2).The areas were isolated with a brick wall to ensure that each main area drained separately.Urea appliance:tiller fertilizer:panicle fertilizer=4:3:3,P_(2)O_(5)-150 kg hm^(-2) were used as base fertilizer,Potassium chloride 300 kg hm^(-2):panicle fertilizer=5:5.Nitrogen rates(N)significantly influenced the LN of Hybrid Indica cultivars.The first year N0=15.5,N150=15.7,N300=15.9 and the second year N0=15.9,N150=16.3,N300=16.5 with a significant difference between both years.However,Japonica rice cultivars were not as responsive to N as Hybrid Indica's were.The Japonica LN on N0=16.2,N150=16,N300=16.8,and N0=16.4,N150=16.6,N300=16.5 for 2017 and 2018 respectively,with a significant difference in the first year only at N300.The results revealed that LN varies greatly among varieties,furthermore the nitrogen fertilizer and the year of the experiment played a major role on LN outcome.

Unmanned air vehicle adaptability and application evaluation for new rice panicle fertilizers:Fertilizer characteristics and mechanical adaptability

High-efficiency fertilizers suitable for mechanical spraying can improve the fertilizer application and utilization efficiency.In this study,two types of granular compound fertilizers suitable for unmanned air vehicle spraying were developed using urea,potassium chloride,humic acid,and an amino acid synergist according to the fertilization requirements of rice at the booting stage.The physical and chemical properties of the compound fertilizers were analyzed by Fourier transform infrared spectroscopy and scanning electron microscopy.The release kinetics of the fertilizer was studied via a soil column leaching experiment.The effect of fertilizer particles on unmanned air vehicle spraying uniformity was studied via an orthogonal simulation experiment.Results showed that the chemical interaction between compound-fertilizer raw materials formed complexes such as C-NH-C and-CO-NH-,which caused a change in fertilizer particle morphology.This led to chemical monolayer adsorption or internal fertilizer diffusion,which in turn delayed the fertilizer release by 5−10 d.A simulation bench test showed that the fertilizer particle hardness and roundness exceeded 20 N and 85%,respectively,while the particle size was in the range of 2.07−5.13 mm,which resulted in good unmanned air vehicle spraying uniformity with a lateral variation coefficient of less than 15%.Finally,the experimental field results demonstrated that the new compound fertilizers,when sprayed by an unmanned air vehicle,could improve the economic benefit by 916−2742 CNY ha−1 without reducing the nitrogen utilization rate and rice yield.The new compound fertilizers exhibit delayed release,good spraying uniformity,and improved economic benefit,rendering them suitable for large-scale promotion and application.