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Mapping summer soybean and corn with remote sensing on Google Earth Engine cloud computing in Parana state – Brazil 被引量:3
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作者 Alex Paludo Willyan Ronaldo Becker +2 位作者 Jonathan Richetti Laíza Cavalcante De Albuquerque Silva Jerry Adriani Johann 《International Journal of Digital Earth》 SCIE 2020年第12期1624-1636,共13页
Brazilian farming influences directly the worldwide economy.Thus,fast and reliable information on areas sown with the main crops is essential for planning logistics and public or private commodity market policies.Rece... Brazilian farming influences directly the worldwide economy.Thus,fast and reliable information on areas sown with the main crops is essential for planning logistics and public or private commodity market policies.Recent farming practices have embraced remote sensing to provide fast and reliable information on commodity dynamics.Medium-to-low resolution free orbital images,such as those from Landsat 8 and Sentinel 2,have been used for crop mapping;however,satellite image processing requires high computing power,especially when monitoring vast areas.Therefore,cloud data processing has been the only feasible option to deal with a large amount of orbital data and its processing and analysis.Thus,our goal was to develop a method to map the two main crops(soybeans and corn)in Paraná,one of the major Brazilian state producers.Landsat-8,Sentinel-2,SRTM+,and field data from 2016 to 2018 were used with the Simple Non-Iterative Clustering segmentation method and the Continuous Naive Bayes classifier,to identify cropped areas.A minimum global accuracy of 90%was found for both crops.Comparison with field data showed correlations of 0.96 and agreement coefficients no lower than 0.86.This ensures mapping quality when using Sentinel and/or Landsat imagery on the GEE platform. 展开更多
关键词 Continuous Naive Bayes SEGMENTATION machine learning land classification
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Microbiological biostimulant promotes rooting of olive cuttings
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作者 Giovana Ritter Fabíola Villa +4 位作者 Daniel Fernandes da Silva Odair Alberton Fernanda Jaqueline Menegusso Tatiane Eberling Joyce Dória 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2021年第6期207-212,共6页
The most widely used method of olive propagation is cutting,although for some cultivars the technique is still limited.The objective of this work was to evaluate the use of plant growth promoter bacteria and arbuscula... The most widely used method of olive propagation is cutting,although for some cultivars the technique is still limited.The objective of this work was to evaluate the use of plant growth promoter bacteria and arbuscular mycorrhizal fungi in the rooting of olive cuttings.Two experiments were conducted from October 2017 to January 2018 with cuttings from 4 olive cultivars(Ascolano 315,Koroneiki,Maria da Féand Picual)from four-year-old plants.The first experiment consisted of 4 olive cultivars and 3 mycorrhizal species plus the control and the second experiment of 3 concentrations of commercial inoculant(Nitro1000®),containing Azospirillum brasilense plus control.The cuttings were treated with 3000 mg/L of indolebutyric acid(IBA).The experimental design used in the two experiments was randomized blocks,in a 4×4 factorial scheme,containing 25 stakes per replicate and 3 replicates.The cuttings were kept under weaver conditions and within a low rooting tunnel.After 75 d,the percentage of rooted cuttings,callus and sprouts,length of the largest root,number and length of shoots were evaluated.The use of FMA in Maria da Féand Picual has a positive response to cutting rooting and the fungi benefit the quality of the seedlings by the higher number of shoots and larger root length.The relation of Azospirillum brasilense cultivar is specific,being that,the cultivar Picual does not respond to inoculation of the bacterium having less viability in the propagation by cutting.Maria da Féand Koroneiki have the best percentages of rooting with the use of 75.00 and 52.00 mL/L of inoculant,respectively. 展开更多
关键词 Azospirillum brasilense Arbuscular mycorrhizal fungi Propagation Olea europaea L. MICROORGANISM
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