|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | IBDV-induced bursal T lympho-cy-tes inhibit mitogenic response of normal splenocytes显示文摘 | Kim I-J Jagdev M Sharma | 2000 | Veterinary Immunology and Immunopathology2000，，74： | 1 |
| 2 | IFN γ upregulation and protection by macrophage adapted infectious bursal disease virus显示文摘 | Mahesh Khatri Jagdev M Sharma | 2008 | Vaccine2008，26，36： | 1 |
| 3 | Mechanisms of infectious bursal disease virus-induced immunosuppression显示文摘 | Jagdev M Sharma | 2006 | American Association of Avian Pathologists2006，2527，： | 1 |
| 4 | Reovirus Infection in Chickens Primes Splenic Adherent Macrophages to Produce Nitric Oxide in Response to T Cell-Produced Factors显示文摘 | Terence L. Pertile Jagdev M. Sharma Mary M. Walser | 1995 | Cellular Immunology1995，，2： | 1 |
| 5 | Recombinant fowlpox viruses coexpressing chicken type I IFN and Newcastle disease virus HN and F genes: influence of IFN on protective efficacy and humoral responses of chickens following in ovo or posthatch administration of recombinant viruses 显示文摘 | Karaca K Jagdev M Sharma J | 1998 | Vaccine1998，16，： | 1 |
| 6 | Enhanced Field-Based Detection of Potato Blight in Complex Backgrounds Using Deep Learning显示文摘Rapid and automated identification of blight disease in potato will help farmers to apply timely remedies to protect their produce.Manual detection of blight disease can be cumbersome and may require trained experts.To overcome these issues,we present an automated system using the Mask Region-based convolutional neural network(Mask R-CNN)architecture,with residual network as the backbone network for detecting blight disease patches on potato leaves in field conditions.The approach uses transfer learning,which can generate good results even with small datasets.The model was trained on a dataset of 1423 images of potato leaves obtained from fields in different geographical locations and at different times of the day.The images were manually annotated to create over 6200 labeled patches covering diseased and healthy portions of the leaf.The Mask R-CNN model was able to correctly differentiate between the diseased patch on the potato leaf and the similar-looking background soil patches,which can confound the outcome of binary classification.To improve the detection performance,the original RGB dataset was then converted to HSL,HSV,LAB,XYZ,and YCrCb color spaces.A separate model was created for each color space and tested on 417 field-based test images.This yielded 81.4%mean average precision on the LAB model and 56.9%mean average recall on the HSL model,slightly outperforming the original RGB color space model.Manual analysis of the detection performance indicates an overall precision of 98%on leaf images in a field environment containing complex backgrounds. | Joe Johnson Geetanjali Sharma Srikant Srinivasan Shyam Kumar Masakapalli Sanjeev Sharma Jagdev Sharma Vijay Kumar Dua | 2021 | Plant Phenomics2021，3，1： | 0 |
| 7 | Plant Community and Nutrient Status of the Soils of Schirmacher Oasis,East Antarctica显示文摘Investigations on plant community and micronutrient status of Schirmacher Oasis,East Antarctica have been presented in this paper.The dominant plant com- munities include moss and lichen.The frequency of species occurrence and changes in species composition at different location varied.Thirty-four soil samples were ana- lyzed for chemical properties of the soils of Schirmacher Oasis and Nunatak,East Ant- arctica.The most common plant species growing throughout the areas of Schirmacher Oasis and Nunataks are:Candelariella flava (lichen) and Bryum pseudotriquetrum (moss).Large variations were observed among different soil samples in all the nutri- ents and other measured soil chemical parameters.The soils are characterized by a- cidic pH ranging from 4.42-6.80.The mean organic carbon content was 0.62 and ranged from 0.06-1.29%.The electrical conductivity in 1:2 soil water ratio ranged from 0.06-1.29.The average content of macronutrient cation,which are ammonium acetate extractable was in the order of Ca>K>Na>Mg.The average content of DTPA extractable micronutrient cations was in the order of Fe>Mn>Cu>Zn.Thirty one out of 34 samples contained less than 0.80 ppm DTPA extractable Zn. Correlation studies revealed that content of macronutrient cations significantly and positively correlated to that of chlorides.Electrical conductivity exhibited significant and positive relationship with pH,K,Ca,Mg,Na and chloride content.Sodium (r =0.876^(**)) exhibited highest correlation followed by K (r=0.831^(**)) with chlo- ride content.The correlation coefficient for chlorides was higher with electrical con- ductivity (r=0.732^(**)) than pH (r=0.513^(**)).Organic carbon content of the soil was positively correlated with Fe (r=0.442~*).The nutrient status did not ap- pear to be a limiting factor in growth of plants.Lichen and moss community structure and composition in the study area were not related with fertility status of soil.Terres- trial mosses are most abundant and luxuriant along the soil habitats near bank of water bodies and the melt water streams. | Shiv Mohan Singh Jagdev Sharma Rasik Ravindra Purnima Singh | 2008 | Chinese Journal of Polar Science2008，19，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员