Optical sensors have potential for determining nitrogen fertilizer topdressing requirements of canola in Saskatchewan

Holzapfel, C. B.; Lafond, G. P.; Brandt, S.A.; Bullock, Paul; Irvine, R. B.; James, D.C.; Morrison, Malcolm J.; May, William E.

doi:10.4141/cjps08127

Cited by 14 publications

(9 citation statements)

References 26 publications

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“…The NDVI readings of the plant canopy were used in our study to differentiate possible changes in overall plant health among the treatments as it may be considered a proxy for general nutrient uptake [39,40]. The Black Chernozem soil displayed a higher average NDVI than the Dark Grey Luvisol; however, both soils displayed similar trends among treatments.…”

Section: Normalized Difference Vegetation Indexmentioning

confidence: 99%

Can Faba Bean Physiological Responses Stem from Contrasting Traffic Management Regimes?

Guenette

Hernandez‐Ramirez

2018

Agronomy

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Our study examined how faba beans (Vicia faba L.) grown in soil conditions that simulate common traffic management regimes and water availabilities displayed alterations to their physiological state. Physiological changes were tracked through plant and sensor-based measurements, such as evapotranspiration, water use efficiency, aboveground biomass, stomatal conductance, and normalized difference vegetation index. A greenhouse experiment comprised of faba beans were sown into pots of two different soil types that were separated by treatments of dry bulk density and volumetric water content. The compaction treatment with a bulk density of 1.2 g cm −3 coupled with a volumetric water content of 41% displayed more favorable changes to the physiological state of the faba beans than the contrasting treatment of 1.4 g cm −3 bulk density at 33% volumetric water content. Handheld sensor-based measurements, such as the normalized difference vegetation index, exhibited a strong correlation with faba bean biomass production. Furthermore, the stomatal conductance was able to reveal plant water stress and capture evapotranspiration responses. Conclusive observations showed that increasing soil compaction restricted plant productivity. However, the presence of high water content was shown to offset the negative effects of heavily applied compaction while relatively lower water contents exacerbated differences in plant responses across compaction treatments.

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Section: Normalized Difference Vegetation Indexmentioning

confidence: 99%

Can Faba Bean Physiological Responses Stem from Contrasting Traffic Management Regimes?

Guenette

Hernandez‐Ramirez

2018

Agronomy

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“…12). Holzapfel et al (2009) found that the NDVI data obtained between the six-leaf stage (BBCH 16) and the beginning of flowering (BBCH 60) are correlated with the canola harvest. In this study, correlation results between BBCH 16 and 60 are moderate, but BBCH stages 71 and 77 perform even better.…”

Section: Phenologymentioning

confidence: 99%

Suitability of satellite remote sensing data for yield estimation in northeast Germany

et al. 2021

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Information provided by satellite data is becoming increasingly important in the field of agriculture. Estimating biomass, nitrogen content or crop yield can improve farm management and optimize precision agriculture applications. A vast amount of data is made available both as map material and from space. However, it is up to the user to select the appropriate data for a particular problem. Without the appropriate knowledge, this may even entail an economic risk. This study therefore investigates the direct relationship between satellite data from six different optical sensors as well as different soil and relief parameters and yield data from cereal and canola recorded by the thresher in the field. A time series of 13 years is considered, with 947 yield data sets consisting of dense point data sets and 755 satellite images. To answer the question of how well the relationship between remote sensing data and yield is, the correlation coefficient r per field is calculated and interpreted in terms of crop type, phenology, and sensor characteristics. The correlation value r is particularly high when a field and its crop are spatially heterogeneous and when the correct phenological time of the crop is reached at the time of satellite imaging. Satellite images with higher resolution, such as RapidEye and Sentinel-2 performed better in comparison with lower resolution sensors of the Landsat series. The additional Red Edge spectral band also has advantage, especially for cereal yield estimation. The study concludes that there are high correlation values between yield data and satellite data, but several conditions must be met which are presented and discussed here.

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“…Using Nitrogen fertilisation optimization technique based on canopy optical reflectance, VRT for N-application in wheat which enhance Nitrogen use efficiency by >15% compared to uniform rate N-application. Biermacher et al [52] and Boyer et al [53] compared the profitability of a sensor based VRT approach for N application with traditional uniform N-application. The system's controller used the optical reflectance data to calculate Napplication rate for each 0.37 m 2 grid on-the-go in situ and Napplication depending on the rate using an algorithm.…”

Section: Real-time Vrt For Fertilizer Applicationmentioning

confidence: 99%

Variable rate fertilizer application technology for nutrient management: A review

Pramod Pawase,

Madhukar Nalawade,

Balasaheb Bhanage

et al. 2023

International Journal of Agricultural and Biological Engineering

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The efficient and effective application of fertilizers to crops is a major challenge. Conventionally, constant rate or equal dose of fertilizer is applied to each plant. Constant rate fertilizer application across entire field can result in over or under incorporation of nutrients. Fertilizer application is influenced by soil parameters as well as geographical variation in the field. The nutrient management depends on selection of nutrient, application rate and placement of nutrient at the optimal distance from the crop and soil depth. Variable rate technology (VRT) is an input application technology that allows for the application of inputs at a certain rate, time, and place based on soil properties and spatial variation in the field or plants. There are two approaches for implementing VRT, one is sensor based and another is map based. The sensor based approach; with suitable sensors, measures the soil and crop characteristics on-the-go calculating the amount of nutrients required per unit area/plant and micro controlling unit which uses suitable algorithms for controlling the flow of fertilizer with required amount of nutrient. In map based approach; Grid sampling and soil analysis are used to create a prescription map. According to the soil and crop conditions, the microcontroller regulates the desired application rate. The sensor-based VRT system includes a fertilizer tank, sensors, GPS, microcontroller, actuators, and other components, whereas the map-based system does not require an on-the-go sensor. Both approaches of VRT for fertilizer application in orchards and field crops are reviewed in this paper. The use of this advance technology surely increases the fertilizer use efficiency; improve crop yield and profitability with reduced environment impacts.

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Optical sensors have potential for determining nitrogen fertilizer topdressing requirements of canola in Saskatchewan

Cited by 14 publications

References 26 publications

Can Faba Bean Physiological Responses Stem from Contrasting Traffic Management Regimes?

Can Faba Bean Physiological Responses Stem from Contrasting Traffic Management Regimes?

Suitability of satellite remote sensing data for yield estimation in northeast Germany

Variable rate fertilizer application technology for nutrient management: A review

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