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Multispectral remote sensing in participatory on-farm variety trials

{Tool} Multispectral remote sensing in participatory on-farm variety trials. Creator(s): Drexler, Dora; Kovács, Tina and Varga, Korinna. Issuing Organisation(s): Hungarian Research Institute of Organic Agriculture ÖMKi. OK-Net Arable Practice abstract, no. 021. (2018)

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Online at: https://orgprints.org/32539/

Summary

On the one hand, through the analysis of remote sensing images, it was possible to determine weed infestation, field heterogeneity and NDVI values/pixel (app. 1 cm per pixel). In some cases, we even discovered previously unknown underground field objects (e.g. a drainage system from the 70s).
On the other hand, NDVI data did not correlate with traditional sampling results (SPAD values and yield estimations), probably because the multicopter covered 100 % of the large plot area, while sampling only provided data from specific points (50 SPAD points/plot and three yield sampling quadrats/plot). We can thus assume that for large plot variety trials, remote sensing can give substantially more precise results than traditional sampling methods. Further tests are needed to prove this assumption.
Practical recommendations
• A multicopter with a RGB and NIR camera was tested on four organic on-farm research sites in Hungary. Farm-scale plots (cc. 120 m2 per variety) were set up with 8 to 15 winter wheat varieties per farm.
• Data collection was performed at flowering/anthesis, on a sunny day, between 11 am and 1 pm (sun position, wind and clouds can highly affect image capturing).
• Ground data validation (chlorophyll readings (SPAD) from 50 randomly selected flag leaves/plot), phytopathology and weed bonitation were performed at the same time as image capturing (<1 cm resolution).
• 3 x 1 m2 yield sampling squares per plot were collected at harvest for quantitative and qualitative yield estimation.
• Validation sample numbers (SPAD, squares) were most probably too small to assess field heterogeneity correctly and to validate remote sensing (NDVI-Normalized Difference Vegetation Index) results.


EPrint Type:Practice tool
What problem does the tool address?:In participatory on-farm variety trials, there is usually no possibility to set up a randomized, complete block design to collect eligible scientific results due to the lack of space, time and equipment of organic arable farmers.
What solution does the tool offer?:We tested multicopters equipped with RGB and NIR cameras to assess field heterogeneity and crop health, to predict yield, and to identify N-efficient varieties within and between on-farm research sites. Our remote sensing tools were tested and successfully validated from 2014 to 2016 on conventional small plots of N-treatment trials. In order to compare results from remote sensing, standard sampling methods were applied.
Country:Hungary
Type of Practice Tool:Practice abstracts
Theme:Soil quality and fertility, Nutrient management, Weed management
Keywords:crop management, diagnostic tool, weed management
Keywords:arable farming, crop management, measuring instruments, monitoring and evaluation, weed management
Agrovoc keywords:
LanguageValueURI
Englishcrop managementhttp://aims.fao.org/aos/agrovoc/c_16094
Englishweed controlhttp://aims.fao.org/aos/agrovoc/c_8345
Englishmeasuring instrumentshttp://aims.fao.org/aos/agrovoc/c_12457
Englishsoil fertilityhttp://aims.fao.org/aos/agrovoc/c_7170
Englishsoil propertieshttp://aims.fao.org/aos/agrovoc/c_330883
Englishnutrient managementhttp://aims.fao.org/aos/agrovoc/c_330697
Englishmonitoring and evaluationhttp://aims.fao.org/aos/agrovoc/c_bea12d1e
Englisharable farminghttp://aims.fao.org/aos/agrovoc/c_36528
Subjects: Soil > Soil quality
Soil > Nutrient turnover
Soil
Crop husbandry > Weed management
Farming Systems > Farm nutrient management
Research affiliation: European Union > Horizon 2020 > OK-Net Arable
Hungary > Hungarian Research Institute of Organic Agriculture
International Organizations > International Federation of Organic Agriculture Movements IFOAM > IFOAM EU Group
H2020 or FP7 Grant Agreement Number:652654
Related Links:http://farmknowledge.org/index.php/search-for-ok-tools?v=32539
Project ID:oknet
Deposited By: Basler, Andreas
ID Code:32539
Deposited On:31 Jan 2018 15:07
Last Modified:23 Jan 2019 13:14
Document Language:English
Status:Published

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