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| 1 | Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India显示文摘Drought is a natural phenomenon posing severe implications for soil,groundwater and agricultural yield.It has been recognized as one of the most pervasive global change drivers to affect the soil.Soil being a weakly renewable resource takes a long time to form,but it takes no time to degrade.However,the response of soil to drought conditions as soil loss is not manifested in the existing literature.Thus,this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India.MODIS remote sensing data was utilized for driving drought indices during 2000-2019.Firstly,we constricted Temperature condition index(TCI)and Vegetation Condition Index(VCI)from Land Surface Temperature(LST)and Enhanced Vegetation Index(EVI)derived from MODIS data.TCI and VCI were then integrated to determine the Vegetation Health Index(VHI).Revised Universal Soil Loss Equation(RUSLE)was utilized for estimating soil loss.The relationship between drought condition and vegetation was ascertained using the Pearson correlation.Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during2000-2019.The mean frequency of the drought occurrence was 7.95 months.The average soil erosion in the sub-basin was estimated to be 9.88 t ha^(-1)year^(-1).A positive relationship was observed between drought indices and soil erosion values(r value being 0.35).However,wide variations were observed in the distribution of spatial correlation.Among various factors,the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin.Thus,the study calls for policy measures to lessen the impact of drought and soil erosion. | Md Masroor Haroon Sajjad Sufia Rehman Roshani Singh Md Hibjur Rahaman Mehebub Sahana Raihan Ahmed Ram Avtar | 2022 | Geoscience Frontiers2022，13，2： | 4 |
| 2 | Genetic linkage mapping and QTL identification for salinity tolerance in Indian mustard(Brassica juncea L.Czern and Coss.)using SSR markers显示文摘Soil salinity is one of the major environmental constraints that limits crop yield and nearly 7%of the total area worldwide is affected by salinity.Salinity-induced oxidative stress causes membrane damage during germination and seedling growth.Indian mustard is a major oilseed crop in India and its production and productivity are severely affected by salt stress.Breeding Brassica cultivars for salinity tolerance by conventional means is very difficult and time-consuming.Therefore,understanding the molecular components associated with salt tolerance is needed to facilitate breeding for salt tolerance in Brassica.In this investigation,quantitative trait loci(QTLs)associated with salt tolerance were identified using F_(2:3)mapping population developed from a cross between CS52(salinity tolerant)and RH30(salinity sensitive).Parents and F_(2:3)were evaluated under controlled and salinity stress conditions for 14 morpho-physiological traits for two consecutive generations(F2 and F_(2:3)),explaining proportion of the phenotypic variance under control condition.Simple sequence repeat(SSR)markers were used for mapping studies.A genetic linkage map based on 42 simple sequence repeats(SSRs)markers was constructed covering 2298.5 cM(Haldane)to identify the loci associated with salt tolerance in Brassica juncea.Forty-one SSRs showing polymorphism in the parents(CS52 and RH30)were mapped on 8 linkage groups(C1–C8).One marker(nga 129)did not map to any of the linkage group and was excluded from mapping.Linkage group 5(C5;317.9 cM)was longest and linkage group 1(C1,255.0 cM)was shortest.Further,we identified 15 QTLs controlling 8 traits using F_(2:3)population.These QTLs explained 12.44–60.63%of the phenotypic variation with a LOD score range of 3.62–5.97.Out of these QTLs,QMI4.1 related to membrane injury showed 51.28%phenotypic variance with a LOD score of 3.34.QTL QBYP8.1 related to biological yield per plant showed 60.63%phenotypic variance at a LOD score of 3.62.The highest LOD score of 5.97 was recorded for QTL related to seed yield per plant(QSYP4.1).Major QTLs were QTL for biological yield per plant(QBYP8.1),QTL for siliquae per plant(QSP4.1),QTL for primary branches(QPB4.1),QTLs for seed per siliqua(QSS4.1,QSS4.2),QTL for seed yield per plant(QSYP4.1),and QTL for membrane injury(QMI8.1)which showed more than 50%phenotypic variance.These QTLs identified in our study need to be confirmed in other populations as well so that these can be used in marker-assisted selection and breeding to enhance salt tolerance in Brassica juncea. | Rekha Patel Sumit Jangra Ram Avtar Neelam R.Yadav Ram C.Yadav | 2023 | Oil Crop Science2023，8，3： | 0 |
| 3 | Full polarimetric PALSAR-based land cover monitoring in Cambodia for implementation of REDD policies显示文摘Forest cover monitoring plays an important role in the implementation of climate change mitigation policies such as Kyoto protocol and Reducing Emissions from Deforestation and Forest Degradation(REDD).In this study,we have monitored land cover using the PALSAR(Phased Array type L-band Synthetic Aperture Radar)full polarimetric data based on incoherent target decomposition.Supervised classification technique has been applied on CloudePottier decomposition,FreemanDurden three component,and Yamaguchi four component decomposition for accurate mapping of different types of land cover classes.Based on confusion matrix derived from the predicted and defined pixels,the evergreen and sparsely deciduous forests have shown high producer’s accuracy by FreemanDurden three component and Yamaguchi four component classifications.The overall accuracy of Maximum Likelihood Classification by Yamaguchi four component is 94.1%with 0.93 kappa coefficient as compared to the 90.3%with 0.88 kappa coefficient by FreemanDurden three component and 89.7%with 0.88 kappa coefficient by CloudePottier decomposition.High accuracy of classification in a forested area using full polarimetric PALSAR data may have been because of high penetration of L-band SAR.The content of this study could be useful for the forest cover mapping during cloudy days needed for proper implementation of REDD policies in Cambodia. | Ram Avtar Wataru Takeuchi Haruo Sawada | 2013 | International Journal of Digital Earth2013，6，3： | 0 |
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