Testing of three sensor systems to predict water and nutrient contents of soccer field turfgrass clippings

Şekerli, Yunus Emre; Keskin, Muharrem; Soysal, Yurtsever

doi:10.1016/j.ufug.2020.126909

Cited by 3 publications

(4 citation statements)

References 29 publications

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“…The performance of the model developed for the K content determination was observed to have similar success (R 2 > 0.80) compared to other studies conducted using NIRS on different plant leaves (Gálvez-Sola et al, 2015;Whittier et al, 2021;Yarce & Rojas, 2012). Predictions of Ca, Cu, Mg, and Fe concentrations also exhibit modest yet reasonable performance (R 2 = 0.70-0.80), which is comparable to or even superior to certain NIRS-utilizing studies (Cuq et al, 2020;Gálvez-Sola et al, 2015;Sekerli et al, 2021aSekerli et al, , 2021bWhittier et al, 2021;Yarce & Rojas, 2012). However, this technique did not offer good results for the prediction of N, P, Zn, and Mn in the present study (R 2 < 0.70).…”

Section: Discussionmentioning

confidence: 60%

“…Sekerli et al. (2021b) developed a low‐cost prototype reflectance‐based indoor sensor and compared it with two commercial sensors (a handheld color meter and NIRS) to appraise water and nutrient contents of turfgrass clippings ( Lolium perenne L.) collected from a soccer field. They reported that the NIRS presented the best estimation for nutrient and water contents, except for Cu content.…”

Section: Discussionmentioning

confidence: 99%

“…Consequently, these leaf characteristics could be employed for appraising the inadequate nutrient levels in crops. Various tools like machine vision with digital cameras, chlorophyll meters, normalized difference vegetation index (NDVI) meters, fluorescence meters, chromameters, spectroradiometers, and near‐infrared reflectance spectroscopy (NIRS) have been investigated for the assessment of leaf visual quality, water content, and nutrient concentrations (Acosta, Quiñones, et al., 2023; Keskin et al., 2021; Padilla et al., 2018; Sekerli et al., 2021b).…”

Section: Introductionmentioning

confidence: 99%

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Rapid and cost‐effective assessment of nutrients in pistachio (Pistacia vera L.) leaves through Fourier transform near‐infrared spectroscopy (FT‐NIRS)

Sekerli,

Buyuk,

Keskin

et al. 2024

J. Plant Nutr. Soil Sci.

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BackgroundPistachio nuts provide many health benefits in human diet. Nutrient levels in plant leaves and fertilizer schedules are determined based on traditional soil and leaf chemical analyses. However, these methods require additional labor, time, and cost, which is why most farmers do not prefer them and cannot detect nutrient deficiencies in time. Fast, easy‐to‐use and low‐cost nutrient level assessment techniques are needed.AimThis study aims to explore the viability of near‐infrared reflectance spectroscopy (NIRS) as a fast, user friendly, and cost effective technique for evluating the major macro‐ and micronutrient contents of dried and ground pistachio leaf sample.MethodsThe feasibility of NIRS for estimating nutrient contents was investigated by analyzing samples from 200 pistachio trees. Dried and ground pistachio leaves were subjected to NIRS analysis. PLSR (Partial least square regression) analyses were performed to develop nutrient content prediction models using spectral information of samples.ResultsIt was found that the NIRS system had a very good potential to estimate the K, Ca, Cu, and Mg contents of the leaf samples (R2 > 0.80). It was also found that Fe and Mn concentrations could also be estimated with good accuracy (R2 = 0.70–0.80). However, the NIRS system did not give good results for the prediction of N, P, and Zn (R2 < 0.40).ConclusionIn conclusion, the NIRS system can be used to quickly, easily, and economically assess the K, Ca, Cu, Mg, Fe, and Mn contents of dried and ground pistachio leaves. This technique has the potential to improve nutrient management practices in pistachio farming within a sustainable and environmentally conscious framework. Fourier transform NIRS (FT‐NIRS) can provide valuable insights by complementing rather than replacing traditional chemical analysis. Laboratory analysis is still required for definitive nutrient content information, but FT‐NIRS can significantly reduce the reliance on such analysis, thereby mitigating the environmental impact caused by the excessive use of chemical fertilizers and minimizing the health risks to laboratory staff. In addition, the rapid information‐gathering capabilities of the FT‐NIRS can be emphasized.

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Section: Discussionmentioning

confidence: 60%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rapid and cost‐effective assessment of nutrients in pistachio (Pistacia vera L.) leaves through Fourier transform near‐infrared spectroscopy (FT‐NIRS)

Sekerli,

Buyuk,

Keskin

et al. 2024

J. Plant Nutr. Soil Sci.

Self Cite

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“…The increased property value is closely related to aesthetics due to the aesthetic attributes that vegetation brings to a property [14]. Moreover, natural turfgrass offers economic advantages, such as lower energy costs in comparison to shrubs and trees [7,14], as well as reduced heating and cooling expenses attributed to the temperature regulation effects of vegetation [14,30].…”

Section: Property Value and Maintenancementioning

confidence: 99%

Knowledge Transfer and Innovation: Universities as Catalysts for Sustainable Decision Making in Industry

et al. 2023

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The urgency of addressing the climate crisis has heightened the need to make sustainable decisions. Universities and research institutions are uniquely able to help develop and disseminate useful information for industry, specifically small and medium enterprises. This case study examines the collaboration between the Guelph Turfgrass Institute (GTI) and the turfgrass industry that culminated in the creation of a “Turf Net Present Value Model”. This model enables turfgrass installers, managers, and local municipalities to determine the structure of their turfgrass systems, natural or artificial, and estimate the net present value (NPV) over an extended period. A conceptual model for effective industry-university collaboration is then used to evaluate the knowledge transfer between academia and industry, showcasing a knowledge-transfer framework for improved decision-making and sustainability in sports facilities.

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Rapid measurement of classification levels of primary macronutrients in durian (Durio zibethinus Murray CV. Mon Thong) leaves using FT-NIR spectrometer and comparing the effect of imbalanced and balanced data for modelling

et al. 2022

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Testing of three sensor systems to predict water and nutrient contents of soccer field turfgrass clippings

Cited by 3 publications

References 29 publications

Rapid and cost‐effective assessment of nutrients in pistachio (Pistacia vera L.) leaves through Fourier transform near‐infrared spectroscopy (FT‐NIRS)

Rapid and cost‐effective assessment of nutrients in pistachio (Pistacia vera L.) leaves through Fourier transform near‐infrared spectroscopy (FT‐NIRS)

Knowledge Transfer and Innovation: Universities as Catalysts for Sustainable Decision Making in Industry

Rapid measurement of classification levels of primary macronutrients in durian (Durio zibethinus Murray CV. Mon Thong) leaves using FT-NIR spectrometer and comparing the effect of imbalanced and balanced data for modelling

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