| 1 | Non-escaping frost tolerant QTL linked genetic loci at reproductive stage in six wheat DH populations显示文摘Reproductive stage frost poses a major constraint for wheat production in countries such as Australia.However,little progress has been made in identifying key genes to overcome the constraint.In the present study,a severe frost event hit two large-scale field trials consisting of six doubled haploid(DH)wheat populations at reproductive stage(young microspore stage)in Western Australia,leading to the identification of 30 robust frost QTL on 17 chromosomes.The major 18 QTL with the phenotype variation over 9.5%were located on 13 chromosomes including 2 A,2 B,2 D,3 A,4 A,4 B,4 D,5 A,5 D,6 D,7 A,7 B and7 D.Most frost QTL were closely linked to the QTL of anthesis,maturity,Zadok stages as well as linked to anthesis related genes.Out of those,six QTL were repetitively detected on the homologous regions on 2 B,4 B,4 D,5 A,5 D,7 A in more than two populations.Results showed that the frost damage is associated with alleles of Vrn-A1 a,Vrn-D1 a,Rht-B1 b,Rht-D1 b,and the high copy number of Ppd-B1.However,anthesis QTL and anthesis related genes of Vrn-B1 a and Ta FT3-1 B on chromosomes 5 B and 1 B did not lead to frost damage,indicating that these early-flowering phenotype related genes are compatible with frost tolerance and thus can be utilised in breeding.Our results also indicate that wild-type alleles Rht-B1 a and Rht-D1 a can be used when breeding for frost-tolerant varieties without delaying flowering time. | Jingjuan Zhang MD Shahidul Islam Yun Zhao Masood Anwar Zaid Alhabbar Maoyun She Rongchang Yang Angela Juhasz Guixiang Tang Jiansheng Chen Hang Liu Yanjie Jiang Shengnan Zhai Xin Hu Junkang Rong Yingquan Zhang Yebo Qin Qier Liu Zitong Yu Yujuan Zhang Sadegh Balotf Mirza Dowla Sonia Afrin Nandita Roy Md Resad Mallik Md Atik Us Saieed Shanjida Rahman Nigarin Sultana Sarah Al-Sheikh Ahmed Chris Florides Kefei Chen Darshan Sharma Nathan Height Ben Biddulph Meiqin Lu Jorge EMayer Wujun Ma | 2022 | The Crop Journal2022，10，1： | 0 |
| 2 | Detection and recognition of veterinary drug residues in beef using hyperspectral discrete wavelet transform and deep learning显示文摘A fast,non-destructive recognition method for veterinary drug residues in beef was proposed to mitigate the laborious sample preparation and long detection times associated with conventional chemical detection techniques.Control beef samples free of veterinary drug residues and four groups of beef sprayed with relevant concentrations of metronidazole,ofloxacin,salbutamol,and dexamethasone under ambient conditions were analyzed by 400-1000 nm hyperspectral imaging followed by multiplicative scatter correction preprocessing.Data dimension reduction was performed using Competitive Adaptive Reweighted Sampling(CARS),Principal Component Analysis(PCA),and Discrete Wavelet Transform(DWT)based on Haar,db3,bior1.5,sym5,and rbio1.3 wavelet basis functions.Treated data were subjected to Convolutional Neural Network(CNN),Multilayer Perceptron(MLP),Random Forest(RF),and Support Vector Machine(SVM)modelling.CNN,MLP,SVM,and RF algorithms achieved overall accuracies of 91.6%,88.6%,87.6%,and 86.2%,respectively,when combined with DWT(wavelet basis functions and numbers of transform layers being Haar-4,db3-2,bior1.5-4,and sym5-3,respectively).The algorithm Kappa coefficients(0.89,0.86,0.85,and 0.83,respectively)and time consumption for prediction(140.60 ms,57.85 ms,70.67 ms,and 87.16 ms,respectively)were also superior to models based on CARS and PCA.DWT combined with deep learning can shorten prediction times,considerably improve the accuracy of classification and recognition,and alleviate the Hughes phenomenon,thus providing a new method for the fast,non-destructive detection and recognition of veterinary drug residues in beef. | Rongchang Jiang Jingxin Shen Xinran Li Rui Gao Qinghe Zhao Zhongbin Su | 2022 | International Journal of Agricultural and Biological Engineering2022，15，1： | 0 |
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