IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i9p1548-d110271.html
   My bibliography  Save this article

Assessing the Reliability of Thermal and Optical Imaging Techniques for Detecting Crop Water Status under Different Nitrogen Levels

Author

Listed:
  • Daniele Masseroni

    (Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy)

  • Bianca Ortuani

    (Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy)

  • Martina Corti

    (Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy)

  • Pietro Marino Gallina

    (Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy)

  • Giacomo Cocetta

    (Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy)

  • Antonio Ferrante

    (Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy)

  • Arianna Facchi

    (Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy)

Abstract

Efficient management of irrigation water is fundamental in agriculture to reduce the environmental impacts and to increase the sustainability of crop production. The availability of adequate tools and methodologies to easily identify the crop water status in operating conditions is therefore crucial. This work aimed to assess the reliability of indices derived from imaging techniques—thermal indices ( I g (stomatal conductance index) and CWSI (Crop Water Stress Index)) and optical indices ( NDVI (Normalized Difference Vegetation Index) and PRI (Photochemical Reflectance Index))—as operational tools to detect the crop water status, regardless the eventual presence of nitrogen stress. In particular, two separate experiments were carried out in a greenhouse, on two spinach varieties (Verdi F1 and SV2157VB), with different microclimatic conditions and under different levels of water and nitrogen application. Statistical analysis based on ANOVA test was carried out to assess the independence of thermal and optical indices from the crop nitrogen status. These imaging indices were successively compared through correlation analysis with reference destructive and non-destructive measurements of crop water status (stomatal conductance, chlorophyll a fluorescence, and leaf and soil water content), and linear regression models of thermal and optical indices versus reference measurements were calibrated. All models were significant (Fisher p -value lower than 0.05), and the highest R 2 values (greater than 0.6) were found for the regression models between CWSI and the soil water content, NDVI and the leaf water content, and PRI and the stomatal conductance. Further analysis showed that imaging indices acquired by thermal cameras (especially CWSI ) can be used as operational tools to detect the crop water status, since no dependence on plant nitrogen conditions was observed, even when the soil water depletion was very limited. Our results confirmed that imaging indices such as CWSI , NDVI and PRI can be used as operational tools to predict soil water status and to detect drought stress under different soil nitrogen conditions.

Suggested Citation

  • Daniele Masseroni & Bianca Ortuani & Martina Corti & Pietro Marino Gallina & Giacomo Cocetta & Antonio Ferrante & Arianna Facchi, 2017. "Assessing the Reliability of Thermal and Optical Imaging Techniques for Detecting Crop Water Status under Different Nitrogen Levels," Sustainability, MDPI, vol. 9(9), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:9:p:1548-:d:110271
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/9/1548/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/9/1548/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pou, Alícia & Diago, Maria P. & Medrano, Hipólito & Baluja, Javier & Tardaguila, Javier, 2014. "Validation of thermal indices for water status identification in grapevine," Agricultural Water Management, Elsevier, vol. 134(C), pages 60-72.
    2. Ors, Selda & Suarez, Donald L., 2017. "Spinach biomass yield and physiological response to interactive salinity and water stress," Agricultural Water Management, Elsevier, vol. 190(C), pages 31-41.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Urs Feller & Stanislav Kopriva & Valya Vassileva, 2018. "Plant Nutrient Dynamics in Stressful Environments: Needs Interfere with Burdens," Agriculture, MDPI, vol. 8(7), pages 1-6, July.
    2. García, Ana Belén Mira & Romero-Trigueros, Cristina & Gambín, José María Bayona & Sánchez Iglesias, Ma del Puerto & Tortosa, Pedro Antonio Nortes & Nicolás, Emilio Nicolás, 2023. "Estimation of stomatal conductance by infra-red thermometry in citrus trees cultivated under regulated deficit irrigation and reclaimed water," Agricultural Water Management, Elsevier, vol. 276(C).
    3. Fan Ding & Changchun Li & Weiguang Zhai & Shuaipeng Fei & Qian Cheng & Zhen Chen, 2022. "Estimation of Nitrogen Content in Winter Wheat Based on Multi-Source Data Fusion and Machine Learning," Agriculture, MDPI, vol. 12(11), pages 1-16, October.
    4. Bhatti, Sandeep & Heeren, Derek M. & Evett, Steven R. & O’Shaughnessy, Susan A. & Rudnick, Daran R. & Franz, Trenton E. & Ge, Yufeng & Neale, Christopher M.U., 2022. "Crop response to thermal stress without yield loss in irrigated maize and soybean in Nebraska," Agricultural Water Management, Elsevier, vol. 274(C).
    5. Thomas M. Koutsos & Georgios C. Menexes & Andreas P. Mamolos, 2021. "The Use of Crop Yield Autocorrelation Data as a Sustainable Approach to Adjust Agronomic Inputs," Sustainability, MDPI, vol. 13(4), pages 1-17, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Xianbo & Yang, Hui & Shukla, Manoj K. & Du, Taisheng, 2023. "Proposing a crop-water-salt production function based on plant response to stem water potential," Agricultural Water Management, Elsevier, vol. 278(C).
    2. Levin, Alexander D., 2019. "Re-evaluating pressure chamber methods of water status determination in field-grown grapevine (Vitis spp.)," Agricultural Water Management, Elsevier, vol. 221(C), pages 422-429.
    3. Li, Hao & Hou, Xuemin & Bertin, Nadia & Ding, Risheng & Du, Taisheng, 2023. "Quantitative responses of tomato yield, fruit quality and water use efficiency to soil salinity under different water regimes in Northwest China," Agricultural Water Management, Elsevier, vol. 277(C).
    4. Wu, Zhuqing & Fan, Yaqiong & Qiu, Yuan & Hao, Xinmei & Li, Sien & Kang, Shaozhong, 2022. "Response of yield and quality of greenhouse tomatoes to water and salt stresses and biochar addition in Northwest China," Agricultural Water Management, Elsevier, vol. 270(C).
    5. Syeda Fasiha Amjad & Nida Mansoora & Samia Yaseen & Afifa Kamal & Beenish Butt & Humera Matloob & Saad A. M. Alamri & Sulaiman A. Alrumman & Ebrahem M. Eid & Muhammad Shahbaz, 2021. "Combined Use of Endophytic Bacteria and Pre-Sowing Treatment of Thiamine Mitigates the Adverse Effects of Drought Stress in Wheat ( Triticum aestivum L.) Cultivars," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
    6. Jorge F. S. Ferreira & Devinder Sandhu & Xuan Liu & Jonathan J. Halvorson, 2018. "Spinach ( Spinacea oleracea L.) Response to Salinity: Nutritional Value, Physiological Parameters, Antioxidant Capacity, and Gene Expression," Agriculture, MDPI, vol. 8(10), pages 1-16, October.
    7. Tianyu Wang & Zhenghe Xu & Guibin Pang, 2019. "Effects of Irrigating with Brackish Water on Soil Moisture, Soil Salinity, and the Agronomic Response of Winter Wheat in the Yellow River Delta," Sustainability, MDPI, vol. 11(20), pages 1-16, October.
    8. Kumar, Navsal & Adeloye, Adebayo J. & Shankar, Vijay & Rustum, Rabee, 2020. "Neural computing modelling of the crop water stress index," Agricultural Water Management, Elsevier, vol. 239(C).
    9. Ezenne, G.I. & Jupp, Louise & Mantel, S.K. & Tanner, J.L., 2019. "Current and potential capabilities of UAS for crop water productivity in precision agriculture," Agricultural Water Management, Elsevier, vol. 218(C), pages 158-164.
    10. Krista C. Shellie & Bradley A. King, 2020. "Application of a Daily Crop Water Stress Index to Deficit Irrigate Malbec Grapevine under Semi-Arid Conditions," Agriculture, MDPI, vol. 10(11), pages 1-17, October.
    11. Pappalardo, S. & Consoli, S. & Longo-Minnolo, G. & Vanella, D. & Longo, D. & Guarrera, S. & D’Emilio, A. & Ramírez-Cuesta, J.M., 2023. "Performance evaluation of a low-cost thermal camera for citrus water status estimation," Agricultural Water Management, Elsevier, vol. 288(C).
    12. Yang, Hui & Du, Taisheng & Mao, Xiaomin & Ding, Risheng & Shukla, Manoj K., 2019. "A comprehensive method of evaluating the impact of drought and salt stress on tomato growth and fruit quality based on EPIC growth model," Agricultural Water Management, Elsevier, vol. 213(C), pages 116-127.
    13. Gulom Bekmirzaev & Baghdad Ouddane & Jose Beltrao & Mukhamadkhon Khamidov & Yoshiharu Fujii & Akifumi Sugiyama, 2021. "Effects of Salinity on the Macro- and Micronutrient Contents of a Halophytic Plant Species ( Portulaca oleracea L.)," Land, MDPI, vol. 10(5), pages 1-13, May.
    14. Okuhle Mndi & Avela Sogoni & Muhali Olaide Jimoh & Carolyn Margaret Wilmot & Fanie Rautenbach & Charles Petrus Laubscher, 2023. "Interactive Effects of Salinity Stress and Irrigation Intervals on Plant Growth, Nutritional Value, and Phytochemical Content in Mesembryanthemum crystallinum L," Agriculture, MDPI, vol. 13(5), pages 1-21, May.
    15. Santesteban, L.G. & Di Gennaro, S.F. & Herrero-Langreo, A. & Miranda, C. & Royo, J.B. & Matese, A., 2017. "High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard," Agricultural Water Management, Elsevier, vol. 183(C), pages 49-59.
    16. Syed Abu Bakr Haider Bukhari & Irfana Lalarukh & Syeda Fasiha Amjad & Nida Mansoora & Maliha Naz & Muhammad Naeem & Syeda Aqsa Bukhari & Muhammad Shahbaz & Saleha Ahmad Ali & Theodore Danso Marfo & Su, 2021. "Drought Stress Alleviation by Potassium-Nitrate-Containing Chitosan/Montmorillonite Microparticles Confers Changes in Spinacia oleracea L," Sustainability, MDPI, vol. 13(17), pages 1-15, September.
    17. Marcella Michela Giuliani & Eugenio Nardella & Anna Gagliardi & Giuseppe Gatta, 2017. "Deficit Irrigation and Partial Root-Zone Drying Techniques in Processing Tomato Cultivated under Mediterranean Climate Conditions," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    18. Qiu, Yuan & Fan, Yaqiong & Chen, Yang & Hao, Xinmei & Li, Sien & Kang, Shaozhong, 2021. "Response of dry matter and water use efficiency of alfalfa to water and salinity stress in arid and semiarid regions of Northwest China," Agricultural Water Management, Elsevier, vol. 254(C).
    19. King, B.A. & Shellie, K.C., 2016. "Evaluation of neural network modeling to predict non-water-stressed leaf temperature in wine grape for calculation of crop water stress index," Agricultural Water Management, Elsevier, vol. 167(C), pages 38-52.
    20. Ramírez-Cuesta, J.M. & Ortuño, M.F. & Gonzalez-Dugo, V. & Zarco-Tejada, P.J. & Parra, M. & Rubio-Asensio, J.S. & Intrigliolo, D.S., 2022. "Assessment of peach trees water status and leaf gas exchange using on-the-ground versus airborne-based thermal imagery," Agricultural Water Management, Elsevier, vol. 267(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:9:y:2017:i:9:p:1548-:d:110271. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.