Use of GreenSeeker and CM-100 as manual tools for nitrogen management and yield prediction in irrigated potato (Solanum tuberosum) production

Satognon, Felix; Lelei, Joyce J.; Owido, Seth F. O.

doi:10.26832/24566632.2021.060202

Cited by 11 publications

(6 citation statements)

References 37 publications

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“…While red fluorescence emission and fluorescence peak ratio, in addition to CCI, red edge reflectance and MTCI were all correlated with Group 1 nutrients (nitrogen, phosphorus, potassium and magnesium), NDVI was not. As such, the NDVI signal has been found to saturate in high leaf chlorophyll conditions, which was also the case in our study (Gitelson et al 1996;Satognon et al 2021). The connection between MTCI, red edge reflectance and the nutrients was through their coupling to the leaf chlorophyll amounts: increasing chlorophyll amounts in the leaf shifts the red edge feature towards higher wavelengths (Filella & Peñuelas, 1994), causing it to be less susceptible to saturation than the red reflectance band (Kanke et al 2012).…”

Section: Co-registration Of Leaf Physiological Processes and Spectral...supporting

confidence: 79%

Novel methods facilitating the mechanistic interpretation of multiscale optical remote sensing measurements

Oivukkamäki

2024

Diss. For.

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Plant physiology concentrates on the study of plant internal processes, such as growth, nutrient uptake and photosynthesis. The quantification of photosynthesis regulation is significant in understanding how plants react to the changing climate. Spectral remote sensing methods, using both reflected light in the visible and near infrared wavelengths, as well as chlorophyll fluorescence, are used to gather information about plant physiological variables. These methods have developed rapidly, prompted by the advances in remote sensing platforms and sensors. However, interpretation of remote sensing signals can be challenging. Due to canopy heterogeneity, the signal is affected by various elements, such as scattering, soil background and canopy structural effects. Additionally, open questions remain linked to the underlying mechanistic processes in the leaf modulating the optical signal, such as nutrient contents and leaf photochemistry, and how these processes and the optical signals diverge in response to temporal variation. Through multi-scale measurements, this thesis aims to advance the interpretation of optical remote sensing signals as they are affected by spatial and temporal variation, while promoting the use of novel methods and devices. Results indicate that diurnal and long-term variation of solar induced fluorescence (SIF) is driven by photosynthetic and structural factors, causing possible misinterpretations in SIF data. Additionally, depending on the scale of observation, results show that the capacity of remote sensing to detect changes in foliar nutrients depends on the covariation of nutrients, pigments and canopy structure, underlining the need for both leaf and canopy level measurements. Finally, we advocate for the implementation of a novel miniaturized fluorometer, demonstrating the ability to track the seasonal regulation of photosynthesis using integrated measurements of chlorophyll fluorescence and gas exchange. The results from this thesis underline the need for simultaneous multi-scale measurements of leaf and canopy physiological factors to further our understanding of photosynthesis regulation.

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Section: Co-registration Of Leaf Physiological Processes and Spectral...supporting

confidence: 79%

Novel methods facilitating the mechanistic interpretation of multiscale optical remote sensing measurements

Oivukkamäki

2024

Diss. For.

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“…They analyze crop attributes and estimate crop production during the harvest. Optical sensors, such as OptRx [58], Cloro-fiLOG [59], Dualex [27], Multiplex [60], Isaria, Crop Circle [61], SPAD-502 [10], Crop-Spec [62], GreenSeeker [63], and ALS-2 N [10], provide crop monitoring under day and night conditions [64], as shown in Table 1. The method of analysis involves collecting a large quantity of recordings per field with many measurements per second [65].…”

Section: Optical Sensorsmentioning

confidence: 99%

“…Optical sensors have been successfully implemented for N prediction in a variety of crops, such as T. aestivum [27], S. tuberosum [63], Oryza sativa (L.) [72], Z. mays [73], Capsicum annuum (L.) [74], and Vitis vinifera (L.) [75].…”

Section: Optical Sensorsmentioning

confidence: 99%

Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring

et al. 2022

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Digital farming approach merges new technologies and sensor data to optimize the quality of crop monitoring in agriculture. The successful fusion of technology and data is highly dependent on the parameter collection, the modeling adoption, and the technology integration being accurately implemented according to the specified needs of the farm. This fusion technique has not yet been widely adopted due to several challenges; however, our study here reviews current methods and applications for fusing technologies and data. First, the study highlights different sensors that can be merged with other systems to develop fusion methods, such as optical, thermal infrared, multispectral, hyperspectral, light detection and ranging and radar. Second, the data fusion using the internet of things is reviewed. Third, the study shows different platforms that can be used as a source for the fusion of technologies, such as ground-based (tractors and robots), space-borne (satellites) and aerial (unmanned aerial vehicles) monitoring platforms. Finally, the study presents data fusion methods for site-specific crop parameter monitoring, such as nitrogen, chlorophyll, leaf area index, and aboveground biomass, and shows how the fusion of technologies and data can improve the monitoring of these parameters. The study further reveals limitations of the previous technologies and provides recommendations on how to improve their fusion with the best available sensors. The study reveals that among different data fusion methods, sensors and technologies, the airborne and terrestrial LiDAR fusion method for crop, canopy, and ground may be considered as a futuristic easy-to-use and low-cost solution to enhance the site-specific monitoring of crop parameters.

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“…Globally, 368 Tg of potato were produced in 2018 on an estimated area of 17.58 million ha (FAOSTAT, 2020). In Kenya, it is the second staple food and cash crop (Satognon et al., 2021b; Waaswa et al., 2021b). This sector has been negatively impacted by climate change events that have lowered potato yield to 8.6 Mg ha −1 , which is below the global average yield of 21 Mg ha −1 (Waaswa & Satognon, 2020; Waaswa et al., 2021a).…”

Section: Introductionmentioning

confidence: 99%

Water use efficiency and nitrogen use efficiency of apical rooted cuttings of potato grown in a mollic Andosol

Satognon

Owido

Lelei

2022

Urban Agric & Regnl Food Sys

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Water and nitrogen (N) are key interacting factors that control plant growth. The objective of the study was to determine the effect of N rates and drip irrigation regimes on water use efficiency (WUE) and N use efficiency (NUE) of apical rooted cuttings of potato (Solanum tuberosum L.) grown in a mollic Andosol. The treatments comprised four drip irrigation regimes of 50%, 75%, 85% and 100% of the crop evapotranspiration (ETC), where ETC100% was irrigated according to the soil water depletion 2 d after full irrigation and four N rates: 0 (N0), 60 (N1), 90 (N2) and 130 kg N ha −1 (N3). The results showed that potato tuber yield, WUE, and NUE were significantly (P < .001) affected by irrigation regimes, N rates, and the interaction of both factors. The highest potato tuber yield, 58.29 Mg ha −1 , was obtained under ETC100% with N3, whereas the highest WUE, 17.5 kg m −3 , was found under ETC50% with N3. The apical rooted cuttings of potato grown under ETC100% with N2 produced the maximum NUE, 208.30 kg kg −1 . The correlation coefficient (r = 0.31; P < .01) obtained between WUE and NUE was weak. It was also observed that an increase in irrigation amount decreased WUE and increased NUE, whereas a high N dosage increased WUE and decreased NUE of potato grown in a mollic Andosol. This study suggests that if the farmers aim to maximize NUE of apical rooted cuttings in a mollic Andosol, then they will do so at the expense of potato WUE, and yield will be looked at as a secondary factor. INTRODUCTIONPotato (Solanum tuberosum L.) is one of the major root and tuber food crops for many people around the world (FAO-STAT, 2017). Globally, 368 Tg of potato were produced in 2018 on an estimated area of 17.58 million ha (FAOSTAT, 2020). In Kenya, it is the second staple food and cash crop

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Use of GreenSeeker and CM-100 as manual tools for nitrogen management and yield prediction in irrigated potato (Solanum tuberosum) production

Cited by 11 publications

References 37 publications

Novel methods facilitating the mechanistic interpretation of multiscale optical remote sensing measurements

Novel methods facilitating the mechanistic interpretation of multiscale optical remote sensing measurements

Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring

Water use efficiency and nitrogen use efficiency of apical rooted cuttings of potato grown in a mollic Andosol

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