On the Description of Soil Variability Through EMI Sensors and Traditional Soil Surveys in Precision Agriculture

2020 ◽  
pp. 29-37
Author(s):  
Bianca Ortuani ◽  
Enrico Casati ◽  
Camilla Negri ◽  
Arianna Facchi
Keyword(s):  
Precision Agriculture ◽  
Soil Variability ◽  
Soil Surveys

scholarly journals Assessing the financial and environmental impacts of precision irrigation in a humid climate 

2019 ◽  
Vol 46 (No. 1) ◽  
pp. 43-52 ◽  
Author(s):  
Daniel El Chami ◽  
Jerry W. Knox ◽  
André Daccache ◽  
Edward Keith Weatherhead
Keyword(s):  
Precision Agriculture ◽  
Energy Savings ◽  
Irrigation System ◽  
Cost Benefit ◽  
Added Value ◽  
Soil Variability ◽  
Humid Climate ◽  
Water Savings ◽  
Additional Equipment ◽  
Precision Irrigation

Precision agriculture is increasingly used where in-field spatial variability exists; however, the benefits of its use in humid climates are less apparent. This paper reports on a cost-benefit assessment of precision irrigation with variable rate technique (VRI) versus conventional irrigation, both compared to rainfed production, using a travelling hose-reel irrigator fitted with a boom on onions in eastern England. Selected environmental outcomes including water savings and CO<sub>2</sub>e emissions are evaluated. The modelled precision irrigation system, which responds to soil variability, generates better environmental outcomes than the conventional system in terms of water savings and reduced CO<sub>2</sub>e emissions (22.6% and 23.0% lower, respectively). There is also an increase in the ‘added value’ of the irrigation water used (£3.02/m<sup>3</sup> versus £2.36/m<sup>3</sup>). Although precision irrigation leads to significant financial benefits from water and energy savings, these alone do not justify the additional equipment investment costs. However, any changes in yield or quality benefits, equipment costs or greater soil variability than on this site would make investment in precision irrigation more viable. 

scholarly journals Clustering Tools for Integration of Satellite Remote Sensing Imagery and Proximal Soil Sensing Data

2019 ◽  
Vol 11 (9) ◽  
pp. 1036 ◽  
Author(s):  
Md Saifuzzaman ◽  
Viacheslav Adamchuk ◽  
Roberto Buelvas ◽  
Asim Biswas ◽  
Shiv Prasher ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Data Clustering ◽  
Bare Soil ◽  
Neighborhood Search ◽  
Soil Variability ◽  
Agricultural Fields ◽  
Essential Information ◽  
Spatial Continuity ◽  
Proximal Soil Sensing

Remote sensing (RS) and proximal soil sensing (PSS) technologies offer an advanced array of methods for obtaining soil property information and determining soil variability for precision agriculture. A large amount of data collected by these sensors may provide essential information for precision or site-specific management in a production field. Data clustering techniques are crucial for data mining, and high-density data analysis is important for field management. A new clustering technique was introduced and compared with existing clustering tools to determine the relatively homogeneous parts of agricultural fields. A DUALEM-21S sensor, along with high-accuracy topography data, was used to characterize soil variability in three agricultural fields situated in Ontario, Canada. Sentinel-2 data assisted in quantifying bare soil and vegetation indices (VIs). The custom Neighborhood Search Analyst (NSA) data clustering tool was implemented using Python scripts. In this algorithm, part of the variance of each data layer is accounted for by subdividing the field into smaller, relatively homogeneous, areas. The algorithm’s attributes were illustrated using field elevation, shallow and deep apparent electrical conductivity (ECa), and several VIs. The unique feature of this proposed protocol was the successful development of user-friendly and open source options for defining the spatial continuity of each group and for use in the zone delineation process.

scholarly journals DISTRIBUIÇÃO HORIZONTAL DA FERTILIDADE DO SOLO EM SISTEMAS DE TRÁFEGO CONTROLADO COM FERTILIZAÇÃO EM LINHA

Nativa ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 251
Author(s):  
Anderson Lange ◽  
Rodrigo Sinaidi Zandonadi ◽  
Fernando Cesar Gobbi
Keyword(s):  
Soil Fertility ◽  
Precision Agriculture ◽  
Sampling Strategy ◽  
Horizontal Distribution ◽  
Soil Sampling ◽  
Soil Variability ◽  
Sampling Strategies ◽  
No Till ◽  
Harvest Data ◽  
Controlled Traffic

Tendo em vista a variabilidade do solo em sistemas de semeadura direta, as dificuldades encontradas pelos produtores em amostrar corretamente o solo principalmente em operações em que se usa o tráfego controlado, o objetivo do trabalho foi avaliar o perfil de distribuição horizontal da fertilidade do solo em torno da linha de semeadura em sistema de produção de soja utilizando a mesma pista de semeadura em sistema de tráfego controlado. Em fevereiro de 2017, após a colheita da soja, em um talhão que os últimos 5 anos se usou a mesma pista de semeadura, o solo foi amostrado sobre a linha de semeadura/fertilização, a 8, 16 e 25 cm (para ambos os lados), na camada de 0-20 cm, num total de seis repetições. Os resultados mostram que há concentração de alguns nutrientes na linha de deposição, principalmente o P, que é um fator altamente positivo, pois reduz a fixação deste elemento. Existe também a acidificação da linha de semeadura devido aos fertilizantes nitrogenados, extração/exportação de cátions e balanço eletroquímico que a planta realiza. Assim recomenda-se observar atentamente o método de adubação da propriedade para definir a melhor estratégia de amostragem de solo, desta forma evitando equívocos de interpretação nos resultados analíticos.Palavras-chave: amostragem de solo, agricultura de precisão, fósforo. HORIZONTAL DISTRIBUTION OF SOIL FERTILITY IN CONTROLLED TRAFFIC FARMING PLANTING OPERATION WITH ROW FERTILIZATION ABSTRACT: Considering the soil variability in no-till system, along with the difficulties encountered by the producers regarding soil sampling strategies, especially in the Controlled Traffic Farming setup where same furrow can be used year after year; the objective of the work was to evaluate soil fertility horizontal profile across the furrow. In February 2017, after the soybean harvest, data was collected in a farm where soybean plating has been taken place using same furrow for at least 5 years. Soil was sampled (0-20 cm layer) at the furrow and at 8, 16 and 25 cm for both sides. A total of six replicates (six different furrows in the field) was collected. The results showed that there is concentration of some nutrients in furrow, mainly P, which is a good aspect, because it reduces the fixation of this element. Therefore, the sampling strategy (furrow + with in the row), is important, independent of the use of precision agriculture (AP) or grids because it can hamper the interpretation of the analytical results, leading in erroneous recommendations. Thus, it is recommended to carefully observe the fertilization method used to define the best soil sampling strategy, thus avoiding misunderstandings in the analytical results.Keywords: soil sampling, precision agriculture, phosphorus.

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