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Abstract
High population densities of the potato cyst nematodes (PCN) Globodera pallida and G. rostochiensis cause substantial yield losses to potato production (Solanum tuberosum) due to the delay caused to tuber formation by the retardation of plant growth. It requires meticulous estimation of the population densities by using soil sampling and applying the right combination of nematode management to deal with the PCN problem. This study aims to assess the use of an unmanned vehicle (UAV) in detecting and estimating the effect of ranges of densities of a PCN, G. pallida, on four cultivated potato cultivars with resistance to PCN in a naturally infested potato field in The Netherlands. First, the initial population density (Pi) of G. pallida was estimated by using an intensive sampling method of collecting about 1.5 kg of soil per m2 from the center of each 3 × 5 m plot. At harvest, the fresh tuber yield of the potato cultivars (Avarna, Fontane, Sarion, and Serresta) were assessed. The Seinhorst yield loss model was used to investigate the relationship between Pi and fresh tuber yield. Secondly, the spatial data of UAV with optical and thermal sensors were analyzed to find any relationship between Pi and UAV indices. By using the classical yield loss model, all four cultivars were found to be affected by Pi with a relative minimum fresh tuber yield m, which ranged from 0.26 to 0.40. The maximum fresh tuber yield varied from 49.48 to 80.36 tons (ha)−1. The density at which the fresh tuber yield started to deteriorate was in the range of 0.62–2.16 eggs (g dry soil)−1. A regression was observed between Pi, and all UAV indices in a similar pattern to that of the fresh tuber yield by using the Seinhorst yield loss model, except for the cultivar Avarna for the two UAV indices (NDRE and NDVI). Unlike the tolerance limit, the relative minimum values of the UAV indices—except the chlorophyll index—differ when compared among each other and when compared with that of the fresh tuber yield within the same cultivar. This indicates that all indices can be useful for detection and decision making for statutory purposes but not for estimating damage (except the chlorophyll index).
Original language | English |
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Article number | 1429 |
Number of pages | 15 |
Journal | Remote Sensing |
Volume | 15 |
Issue number | 5 |
DOIs | |
Publication status | Published - 3 Mar 2023 |
Keywords
- drones
- nematode management
- pest and disease
- precision agriculture
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Dive into the research topics of 'Unmanned Aerial Vehicle (UAV) for Detection and Prediction of Damage Caused by Potato Cyst Nematode G. pallida on Selected Potato Cultivars'. Together they form a unique fingerprint.Projects
- 1 Finished
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LWV19250 Transition To A Data-Driven Agriculturen (TTADDA) - for a new Dutch & Japanese Potato Circular Value Chain (BO-67-001-018)
van de Zedde, R. (Project Leader)
1/01/20 → 31/12/23
Project: LVVN project