To assess the effects of straw return coupled with deep nitrogen(N)fertilization on grain yield and N use efficiency(NUE)in mechanical pot-seedling transplanting(MPST)rice,the seedlings of two rice cultivars,i.e.,Yuxi...To assess the effects of straw return coupled with deep nitrogen(N)fertilization on grain yield and N use efficiency(NUE)in mechanical pot-seedling transplanting(MPST)rice,the seedlings of two rice cultivars,i.e.,Yuxiangyouzhan and Wufengyou 615 transplanted by MPST were applied with N fertilizer at 150 kg/hm2 and straw return at 6 t/hm2 in early seasons of 2019 and 2020.The experiment comprised of following treatments:CK(no fertilizer and no straw return),MDS(deep N fertilization and straw return),MBS(broadcasting fertilizer and straw return),MD(deep N fertilization without straw return),MB(broadcasting fertilizer without straw return).Results depicted that the MDS treatment significantly increased the rice yield by 41.69%-72.22%due to total above-ground biomass,leaf area index and photosynthesis increased by 54.70%-55.80%,38.52%-52.17%and 17.89%-28.40%,respectively,compared to the MB treatment.In addition,the MDS treatment enhanced the total N accumulation by 37.74%-43.69%,N recovery efficiency by 141.45%-164.65%,N agronomic efficiency by 121.76%-134.19%,nitrate reductase by 46.46%-60.86%and glutamine synthetase by 23.56%-31.02%,compared to the MB treatment.The average grain yield and NUE in both years for Yuxiangyouzhan were higher in the MDS treatment than in the MD treatment.Hence,deep N fertilization combined with straw return can be an innovative technique with improved grain yield and NUE in MPST in South China.展开更多
为实现在自然环境条件下对苦瓜叶部病害的目标检测,该研究提出了一种基于改进的更快速区域卷积神经网络(Faster Region with Convolutional Neural Network Features,Faster R-CNN)的苦瓜叶部病害目标检测方法。Faster R-CNN以残差结构...为实现在自然环境条件下对苦瓜叶部病害的目标检测,该研究提出了一种基于改进的更快速区域卷积神经网络(Faster Region with Convolutional Neural Network Features,Faster R-CNN)的苦瓜叶部病害目标检测方法。Faster R-CNN以残差结构卷积神经网络ResNet-50作为该次试验的特征提取网络,将其所得特征图输入到区域建议网络提取区域建议框,并且结合苦瓜叶部病害尺寸小的特点,对原始的Faster R-CNN进行修改,增加区域建议框的尺寸个数,并在ResNet-50的基础下融入了特征金字塔网络(Feature Pyramid Networks,FPN)。结果表明,该方法训练所得的深度学习网络模型具有良好的鲁棒性,平均精度均值(Mean Average Precision,MAP)值为78.85%;融入特征金字塔网络后,所得模型的平均精度均值为86.39%,提高了7.54%,苦瓜健康叶片、白粉病、灰斑病、蔓枯病、斑点病的平均精确率(Average Precision,AP)分别为89.24%、81.48%、83.31%、88.62%和89.28%,在灰斑病检测精度上比之前可提高了16.56%,每幅图像的检测时间达0.322 s,保证检测的实时性。该方法对复杂的自然环境下的苦瓜叶部病害检测具有较好的鲁棒性和较高的精度,对瓜果类疾病预防有重要的研究意义。展开更多
基金supported by the Guangdong Basic and Applied Basic Research Foundation,China(Grant No.2021A1515011255)Key-Area Research and Development Program of Guangdong Province,China(Grant No.2019B020221003)National Natural Science Foundation of China(Grant No.31471442)。
文摘To assess the effects of straw return coupled with deep nitrogen(N)fertilization on grain yield and N use efficiency(NUE)in mechanical pot-seedling transplanting(MPST)rice,the seedlings of two rice cultivars,i.e.,Yuxiangyouzhan and Wufengyou 615 transplanted by MPST were applied with N fertilizer at 150 kg/hm2 and straw return at 6 t/hm2 in early seasons of 2019 and 2020.The experiment comprised of following treatments:CK(no fertilizer and no straw return),MDS(deep N fertilization and straw return),MBS(broadcasting fertilizer and straw return),MD(deep N fertilization without straw return),MB(broadcasting fertilizer without straw return).Results depicted that the MDS treatment significantly increased the rice yield by 41.69%-72.22%due to total above-ground biomass,leaf area index and photosynthesis increased by 54.70%-55.80%,38.52%-52.17%and 17.89%-28.40%,respectively,compared to the MB treatment.In addition,the MDS treatment enhanced the total N accumulation by 37.74%-43.69%,N recovery efficiency by 141.45%-164.65%,N agronomic efficiency by 121.76%-134.19%,nitrate reductase by 46.46%-60.86%and glutamine synthetase by 23.56%-31.02%,compared to the MB treatment.The average grain yield and NUE in both years for Yuxiangyouzhan were higher in the MDS treatment than in the MD treatment.Hence,deep N fertilization combined with straw return can be an innovative technique with improved grain yield and NUE in MPST in South China.
