Nikrooz Bagheri; Maryam Rahimi Jahangirlou; Mehyar Jaberi Aghdam
Abstract
Objective: In order to present a new, non-destructive, accurate, and fast method for estimating the nitrogen content of corn, Unmanned Aerial Vehicle (UAV) multispectral sensing technology was used.
Methods: The experiments were performed based on a randomized complete block design in four levels of ...
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Objective: In order to present a new, non-destructive, accurate, and fast method for estimating the nitrogen content of corn, Unmanned Aerial Vehicle (UAV) multispectral sensing technology was used.
Methods: The experiments were performed based on a randomized complete block design in four levels of nitrogen fertilizer (zero, 50, 100, and 150%) in Varamin in 2018. Sampling was carried out in two stages of fertilization (8-leaf Stage and Tasseling Stage). Multispectral aerial imaging and ground sampling was performed one week after each fertilizer application. After processing aerial imagery, vegetation indices were calculated and their correlation with the results of ground sampling was determined.
Results: Based on the results obtained from the correlation coefficients (r) and best subsets regression, among the spectral vegetation indices, Normalized Difference Vegetation Index (NDVI), Nitrogen Reflectance Index (NIR), and Modified Triangular Vegetation Index2 (MTVI2) indices in both eight leaf collar (V8) and tasseling (VT) of maize growth stage was identified as the best indicator to estimate the nitrogen content of forage maize. At VT, a positive and significant relationship was obtained between NDVI (R2= 0.86, P≤0.001), NRI (R2= 0.70, P≤0.001) and MTVI2 (R2= 0.46, P≤0.01) indices with maize nitrogen content.
Conclusion: It can be concluded that UAV multispectral imaging provides acceptable accuracy in determining the nitrogen content of maize. This technology can help farmers to determine the appropriate time of fertilization.
Maryam Rahimi Jahangirlou; Gholam Akbari; Iraj Allah dadi; Saeid Soufizadeh; Maryam Rahimi Jahangirlou
Abstract
Studies to assess quality of dent maize grain are noteworthy because of its wide use as food, feed and ethanol production. This study aimed to evaluate the concentration and composition of starch and oil in maize grain in response to different cultivars (KSC704 and KSC260), planting dates (20 June and ...
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Studies to assess quality of dent maize grain are noteworthy because of its wide use as food, feed and ethanol production. This study aimed to evaluate the concentration and composition of starch and oil in maize grain in response to different cultivars (KSC704 and KSC260), planting dates (20 June and 21 July), irrigation (12-day and 6-day intervals) and nitrogen (0 and 184 kg N ha-1) rate as the strip-plot factorial statistical model during the 2018 growing season in Pakdasht county of Iran. The results suggested that nitrogen application increased grain yield by one tonnes ha-1. In addition, KSC260 had higher grain yield than KSC704 by 0.96 tonnes ha-1. All compositional variables except stearic acid were affected by the interaction effect of irrigation and nitrogen rate. In low irrigated treatments, nitrogen application reduced the amount of oil, palmitic acid, oleic acid, linoleic acid and linolenic acid. In low irrigated condition, nitrogen application had no effect on increasing the concentration of starch and amylopectin. The use of nitrogen fertilizer reduced the amount of stearic acid by 0.05 g kg-1. In conclusion, the balance between irrigation and nitrogen utilization seems to be important for improving the oil and starch properties of maize grain.