EIP-AGRI Focus Group : Precision farming

Final report201

Review : Holistic pest management against early blight disease towards sustainable agriculture

Alternaria species are well-known aggressive pathogens that are widespread globally and warmer temperatures caused by climate change might increase their abundance more drastically. Early blight (EB) disease, caused mainly by Alternaria solani, and brown spot, caused by Alternaria alternata, are major concerns in potato, tomato and eggplant production. The development of EB is strongly linked to varieties, crop development stages, environmental factors, cultivation and field management. Several forecasting models for pesticide application to control EB were created in the last century and more recent scientific advances have included modern breeding technology to detect resistant genes and precision agriculture with hyperspectral sensors to pinpoint damage locations on plants. This paper presents an overview of the EB disease and provides an evaluation of recent scientific advances to control the disease. First of all, we describe the outline of this disease, encompassing biological cycles of the Alternaria genus, favorite climate and soil conditions as well as resistant plant species. Second, versatile management practices to minimize the effect of this pathogen at field level are discussed, covering their limitations and pitfalls. A better understanding of the underlying factors of this disease and the potential of novel research can contribute to implementing integrated pest management systems for an ecofriendly farming system.</p

Unmanned Aerial Vehicle (UAV) for Detection and Prediction of Damage Caused by Potato Cyst Nematode G. pallida on Selected Potato Cultivars

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)