Forecasting of Hypoallergenic Wheat Productivity Based on Unmanned Aerial Vehicles Remote Sensing Approach—Case Study
Bogdan Kulig,
Jacek Waga,
Andrzej Oleksy,
Marcin Rapacz,
Marek Kołodziejczyk,
Piotr Wężyk,
Agnieszka Klimek-Kopyra (),
Robert Witkowicz,
Andrzej Skoczowski,
Grażyna Podolska and
Wiesław Grygierzec
Additional contact information
Bogdan Kulig: Department of Agroecology and Crop Production, University of Agriculture in Krakow, 31-120 Krakow, Poland
Jacek Waga: Department of Physiology, Plant Breeding and Seed Production, University of Agriculture in Krakow, 30-239 Krakow, Poland
Andrzej Oleksy: Department of Agroecology and Crop Production, University of Agriculture in Krakow, 31-120 Krakow, Poland
Marcin Rapacz: Department of Physiology, Plant Breeding and Seed Production, University of Agriculture in Krakow, 30-239 Krakow, Poland
Marek Kołodziejczyk: Department of Agroecology and Crop Production, University of Agriculture in Krakow, 31-120 Krakow, Poland
Piotr Wężyk: Department of Forest Resource Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, Poland
Agnieszka Klimek-Kopyra: Department of Agroecology and Crop Production, University of Agriculture in Krakow, 31-120 Krakow, Poland
Robert Witkowicz: Department of Agroecology and Crop Production, University of Agriculture in Krakow, 31-120 Krakow, Poland
Andrzej Skoczowski: The Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, 31-342 Krakow, Poland
Grażyna Podolska: Cereal Crop Department, Institute of Soil Science and Plant Cultivation, 24-100 Puławy, Poland
Wiesław Grygierzec: Department of Statistics and Social Policy, University of Agriculture in Krakow, 31-120 Krakow, Poland
Agriculture, 2023, vol. 13, issue 2, 1-21
Abstract:
Remote sensing methods based on UAV and hand-held devices as well have been used to assess the response to nitrogen and sulfur fertilization of hypoallergenic genotypes of winter wheat. The field experiment was conducted using the split-split-plot design with three repetitions. The first factor was the two genotypes of winter wheat specified as V1 (without allergic protein) and V2 (with allergic protein), and the second factor was three doses of sulfur fertilization: 0, 20 and 40 kg S per ha. The third factor consisted of six doses of nitrogen fertilization: 0, 40, 60, 80, 100 and 120 kg N·ha −1 . Monitoring the values of the indicators depending on the level of nitrogen and sulfur fertilization allowed the results to be used in yield forecasting, assessment of plant condition, LAI value, nutritional status in the cultivation of wheat. The maximum yield should be expected at doses of 94 and 101 kg N ha −1 for genotypes V1 and V2, respectively, giving yields of 5.39 and 4.71 Mg ha −1 . On the basis of the tested vegetation indices, the highest doses of N should be applied using the normalized difference RedEdge (NDRE), and the lowest ones based on the enhanced vegetation index (EVI), and, in the latter case, a reduction in yield of more than 200 kg ha −1 in the V2 genotype should be taken into account.
Keywords: hypoallergenic wheat; yield forecasting; vegetation indices; GHG; UAV (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:13:y:2023:i:2:p:282-:d:1045450
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