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Germination and Survival of Maize and Beans Seeds: Effects of Irrigation with NaCl and Heavy Metals Contaminated Water

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Open Journal of Applied Sciences 2022年第5期12卷 769-792页

作者： Cornelius Tsamo Sendze Martinien Alanyuy eric fru zama Chi Christopher Tamu Department of Agricultural and Environmental Engineering College of Technology University of Bamenda Bambili Cameroon Department of Chemistry Higher Teachers’ Training College University of Maroua Maroua Cameroon

Metal toxicity and soil salinity at excessive levels in soils are toxic to plants. The main objective of this study was to demonstrate the effects of water salinity (NaCl) and heavy metal concentration on germination and seedling characteristics of maize and beans seeds. Different concentrations of NaCl (0 to 35000 mg/L) and Zn2+, Cu2+ and Pb2+ with concentrations 0 to 600 μmol/L each were used separately. These solutions were used to irrigate maize and bean seeds for 30 days. Data was taken daily for the following parameters;“the number of germinated seeds, shoot length, shoot circumference, leaf area index, leaf colors, senescence, and disease occurrences.” The crops were uprooted at the end of the 30 days and their wet masses were measured and recorded. Results indicated that seed germination reduced with an increase in the concentration of NaCl for both maize and beans with 0% germination recorded in concentrations > 5000 mg/L. The same trends were observed for other parameters, the shoot length, the leaf area index, and the shoot circumference. “For heavy metals, the trends were similar. Beans growth was more affected by Zn and Cu but maize growth was more affected by Pb.” The dry masses and wet masses of the crops with higher concentrations of metals and salts were very low compared to the control experiments. For the effects of salinity and heavy metals on beans and maize seeds, there was a significant difference (P ≤ 0.001) between all tested concentrations and the control for all growth parameters monitored. It was concluded from the results that salinity and heavy metals affect the germination and seedling characteristics of maize and beans;though some metals are essential, their presence in higher concentrations instead cause harm.

关键词： Salinity Heavy Metals Pollution Seedling Characteristics Irrigation

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A Synthesizing Land-cover Classification Method Based on Google Earth Engine: A Case Study in Nzhelele and Levhuvu Catchments, South Africa

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Chinese Geographical Science 2020年第3期30卷 397-409页

作者： ZENG Hongwei WU Bingfang WANG Shuai MUSAKWA Walter TIAN Fuyou MASHIMBYE zama eric POONA Nitesh SYNDEY Mavengahama State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Earth Surface Proc-esses and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Department of Town and Regional Planning University of JohannesburgJohannesburg 2028South Africa Department of Geography and Envi-ronmental Studies Stellenbosch UniversityStellenbosch 7600South Africa Department of Crop Science Faculty of Natural and Agricultural SciencesNorth West UniversityMmabatho 2745South Africa

This study designed an approach to derive land-cover in the South Africa with insufficient ground samples, and made a case demonstration in Nzhelele and Levhuvu catchments, South Africa. The method was developed based on an integration of Landsat 8, Sentinel-1, and Shuttle Radar Topography Mission(SRTM) Digital Elevation Model(DEM), and the Google Earth Engine(GEE) platform. Random forest classifier with 300 trees is employed as land-cover classification model. In order to overcome the defect of insufficient ground data, the stratified sampling method was used to generate the training and validation samples from the existing land-cover product. Likewise, in order to recognize different land-cover categories, the percentile and monthly median composites were employed to expand input metrics of random forest classifier. Results showed that the overall accuracy of the land-cover of Nzhelele and Levhuvu catchments, South Africa in 2017–2018 reached to 76.43%. Three important results can be drawn from our research. 1) The participation of Sentinel-1 data can slightly improve overall accuracy of land-cover while its contribution on land-cover classification varied with land types. 2) Under-fitting problem was observed in the training of non-dominant land-cover categories using the random sampling, the stratified sampling method is recommended to make sure the classification accuracy of non-dominant classes. 3) When related reflectance bands participated in the training process, individual Normalized Difference Vegetation index(NDVI), Enhanced Vegetation Index(EVI), Soil Adjusted Vegetation Index(SAVI), Normalized Difference Built-up Index(NDBI) have little effect on final land-cover classification result.

关键词： land-cover classification random forest percentile composite Landsat 8 Sentinel-1 Google Earth Engine(GEE)

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Influence of brown stink bug feeding, planting date and sampling time on common smut infection of maize

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Insect Science 2014年第5期21卷 564-571页

作者： Xinzhi Ni Michael D. Toews G. David Buntin James E. Carpenter Alisa Huffaker eric A. Schmelz Ted E. Cottrell Zaid Abdo USDA-ARS Crop Genetics and Breeding Research Unit Tifton GA 31793 Department of Entomology University of Georgia TiftonGA 31793-5766 Department of Entomology University of Georgia Griffin GA 30223 USDA-ARS Crop Protection and Management Research Unit Tifton GA 31793 USDA-ARS Center for Medical Agricultural and Veterinary Entomology Gainesville FL 32608 USDA-ARS Southeast Fru# and Tree Nut Research Laboratory Byron GA 31008 USDA-ARS South Atlantic Area Office 950 College Station Road Athens GA 30605 USA

Phytopathogen infections are frequently influenced by both biotic and abiotic factors in a crop field. The effect of brown stink bug, Euschistus servus （Hemiptera： Pentatomidae）, feeding and planting date and sampling time on common smut （Ustilago maydis） infection percentage of maize plants was examined in 2005 and 2006, and 2010 and 2011, respectively. Brown stink bug adult feeding on maize hybrid ＂DKC6971＂ at flowering in 2005 and 2006 did not influence smut infection percentage when examined using 3 treatments （i.e., 0 adult, 5 adults, and 5 adults mixed with the smut spores）. The smut infection percentages were 〈 3% （n =12） in the 3 treatments. The smut infection percentage among the 4 weekly samplings was the same, so was natural aflatoxin contamination at harvest among the treatments. The 2nd experiment showed that planting date did not affect the smut infection percentage in either 2010 or 2011. But, the smut infection percentage from the postflowering sampling was greater than preflowering sampling in both years. The smut infection percentage varied among the germplasm lines in 2010, but not in 2011. This study demonstrated that brown stink bug feeding at flowering had no effect on smut infection in maize, and the best time for smut evaluation would be after flowering. The temperature and precipitation might have also influenced the percentage of smut-infected maize plants during the 4 years when the experiments were conducted. The similarity between kernel-colonizing U. maydis and Aspergillus flavus infections and genotype × environment interaction were also discussed.

关键词： common smut Euschistus servus planting date Ustilago maydis

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