{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T11:00:53Z","timestamp":1773831653845,"version":"3.50.1"},"reference-count":76,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,24]],"date-time":"2021-08-24T00:00:00Z","timestamp":1629763200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key-Area Research and Development program of Guangdong Province","award":["(2019B020214003)"],"award-info":[{"award-number":["(2019B020214003)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Drought and water scarcity due to global warming, climate change, and social development have been the most death-defying threat to global agriculture production for the optimization of water and food security. Reflectance indices obtained by an Analytical Spectral Device (ASD) Spec 4 hyperspectral spectrometer from tomato growth in two soil texture types exposed to four water stress levels (70\u2013100% FC, 60\u201370% FC, 50\u201360% FC, and 40\u201350% FC) was deployed to schedule irrigation and management of crops\u2019 water stress. The treatments were replicated four times in a randomized complete block design (RCBD) in a 2 \u00d7 4 factorial experiment. Water stress treatments were monitored with Time Domain Reflectometer (TDR) every 12 h before and after irrigation to maintain soil water content at the desired (FC%). Soil electrical conductivity (Ec) was measured daily throughout the growth cycle of tomatoes in both soil types. Ec was revealing a strong correlation with water stress at R2 above 0.95 p &lt; 0.001. Yield was measured at the end of the end of the growing season. The results revealed that yield had a high correlation with water stress at R2 = 0.9758 and 0.9816 p &lt; 0.01 for sandy loam and silty loam soils, respectively. Leaf temperature (LT \u00b0C), relative leaf water content (RLWC), leaf chlorophyll content (LCC), Leaf area index (LAI), were measured at each growth stage at the same time spectral reflectance data were measured throughout the growth period. Spectral reflectance indices used were grouped into three: (1) greenness vegetative indices; (2) water overtone vegetation indices; (3) Photochemical Reflectance Index centered at 570 nm (PRI570), and normalized PRI (PRInorm). These reflectance indices were strongly correlated with all four water stress indicators and yield. The results revealed that NDVI, RDVI, WI, NDWI, NDWI1640, PRI570, and PRInorm were the most sensitive indices for estimating crop water stress at each growth stage in both sandy loam and silty loam soils at R2 above 0.35. This study recounts the depth of 858 to 1640 nm band absorption to water stress estimation, comparing it to other band depths to give an insight into the usefulness of ground-based hyperspectral reflectance indices for assessing crop water stress at different growth stages in different soil types.<\/jats:p>","DOI":"10.3390\/s21175705","type":"journal-article","created":{"date-parts":[[2021,8,24]],"date-time":"2021-08-24T22:09:39Z","timestamp":1629842979000},"page":"5705","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Ground-Based Hyperspectral Remote Sensing for Estimating Water Stress in Tomato Growth in Sandy Loam and Silty Loam Soils"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6699-8972","authenticated-orcid":false,"given":"Kelvin Edom","family":"Alordzinu","sequence":"first","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, Guangzhou 510070, China"}]},{"given":"Jiuhao","family":"Li","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, Guangzhou 510070, China"}]},{"given":"Yubin","family":"Lan","sequence":"additional","affiliation":[{"name":"National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology (NPAAC), College of Electronic Engineering, South China Agriculture University, Guangzhou 510070, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7099-7489","authenticated-orcid":false,"given":"Sadick Amoakohene","family":"Appiah","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, Guangzhou 510070, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7463-6592","authenticated-orcid":false,"given":"Alaa","family":"AL Aasmi","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, Guangzhou 510070, China"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, Guangzhou 510070, China"}]},{"given":"Juan","family":"Liao","sequence":"additional","affiliation":[{"name":"College of Engineering, South China Agriculture University, Guangzhou 510070, China"}]},{"given":"Livingstone Kobina","family":"Sam-Amoah","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, School of Agriculture, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast 03321, Ghana"}]},{"given":"Songyang","family":"Qiao","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, Guangzhou 510070, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.biosystemseng.2012.08.009","article-title":"Twenty-five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps","volume":"114","author":"Mulla","year":"2013","journal-title":"Biosyst. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Espinoza, C.Z., Khot, L.R., Sankaran, S., and Jacoby, P.W. (2017). High resolution multispectral and thermal remote sensing-based water stress assessment in subsurface irrigated grapevines. Remote Sens., 9.","DOI":"10.3390\/rs9090961"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"106404","DOI":"10.1016\/j.agwat.2020.106404","article-title":"New technologies and practical approaches to improve irrigation management of open field vegetable crops","volume":"242","author":"Zinkernagel","year":"2020","journal-title":"Agric. Water Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"104860","DOI":"10.1016\/j.compag.2019.104860","article-title":"Sensitivity of spectral vegetation indices for monitoring water stress in tomato plants","volume":"163","author":"Ihuoma","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"ref_5","first-page":"230","article-title":"Remotely sensed estimates of crop water demand","volume":"5544","author":"Ustin","year":"2004","journal-title":"Int. Soc. Opt. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.compag.2015.09.006","article-title":"Automatic irrigation scheduling of apple tress using therietical crop water stress index with and innovative dynamic threshold","volume":"118","author":"Osroosh","year":"2015","journal-title":"Comp. Electron. Agric."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.biosystemseng.2016.10.003","article-title":"Crop reflectance monitoring as a tool for water stress detection in greenhouses: A review","volume":"151","author":"Katsoulas","year":"2016","journal-title":"Biosyst. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhang, C., Filella, I., Liu, D., Ogaya, R., Llusi\u00e0, J., Asensio, D., and Pe\u00f1uelas, J. (2017). Photochemical Reflectance Index (PRI) for Detecting Responses of Diurnal and Seasonal Photosynthetic Activity to Experimental Drought and Warming in a Mediterranean Shrubland. Remote Sens., 9.","DOI":"10.3390\/rs9111189"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(92)90059-S","article-title":"A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency","volume":"41","author":"Gamon","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_11","first-page":"3","article-title":"Impact of alternative wetting and soil drying and soil clay content on the morphological and physiological traits of rice roots and their relationships to yield and nutrient use-efficiency","volume":"233","author":"Hamouda","year":"2019","journal-title":"Agric. Water Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111828","DOI":"10.1016\/j.rse.2020.111828","article-title":"Accuracy and limitations for spectroscopic prediction of leaf traits in seasonally dry tropical environments","volume":"244","author":"Streher","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.agwat.2016.07.022","article-title":"Effects of water stress on processing tomatoes yield, quality and water use efficiency with plastic mulched drip irrigation in sandy soil of the Hetao irrigation district","volume":"179","author":"Zhang","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Nemesk\u00e9ri, E., Nem\u00e9nyi, A., Bocs, A., P\u00e9k, Z., and Helyes, L. (2019). Physiological factors and their relationship with the productivity of processing tomato under different water supplies. Water, 11.","DOI":"10.3390\/w11030586"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/s12898-019-0233-0","article-title":"Estimation of vegetation water content Indices:using hyperspectral vegetation Indicators, a comparison of crop water Treatments, in response to water stress Maize, for summer","volume":"19","author":"Zhang","year":"2019","journal-title":"BMC Ecol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhou, J.J., Zhang, Y.H., Han, Z.M., Liu, X.Y., Jian, Y.F., Hu, C.G., and Dian, Y.Y. (2021). Hyperspectral sensing of photosynthesis, stomatal conductance, and transpiration for citrus tree under drought condition. BioRxiv.","DOI":"10.1101\/2021.02.26.433135"},{"key":"ref_17","first-page":"342","article-title":"Modeling canopy water content for carbon estimates from MODIS data at land EOS validation sites","volume":"1","author":"Ustin","year":"2001","journal-title":"Int. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1080\/00387010.2014.909495","article-title":"Determining the canopy water stress for spring wheat using Canopy Hyperspectral Reflectance Data in Loess Plateau Semiarid Regions","volume":"48","author":"Wang","year":"2015","journal-title":"Lett. Spectrosc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1002\/jsfa.2546","article-title":"Antioxidant content and ascorbate metabolism in cherry tomato exocarp in relation to temperature and solar radiation","volume":"86","author":"Rosales","year":"2006","journal-title":"J. Sci. Food Agric."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"604","DOI":"10.3934\/environsci.2016.4.604","article-title":"Remote sensing of agricultural drought monitoring: A state of art review","volume":"3","author":"Hazaymeh","year":"2016","journal-title":"AIMS Environ. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5006","DOI":"10.3390\/rs5105006","article-title":"Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture","volume":"5","author":"Honkavaara","year":"2013","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1023\/B:GROW.0000017489.21970.d4","article-title":"Effects of flooding and drought on stomatal activity, transpiration, photosynthesis, water potential and water channel activity in strawberry stolons and leaves","volume":"42","author":"Blanke","year":"2004","journal-title":"Plant Growth Regul."},{"key":"ref_23","first-page":"188","article-title":"Indirect method for measurement of leaf area and leaf area index of soilless cucumber crop","volume":"8","author":"Singh","year":"2019","journal-title":"Adv. Plants Agric. Res."},{"key":"ref_24","unstructured":"Danner, M., Locherer, M., Hank, T., and Richter, K. (2015). Spectral Sampling with the ASD FieldSpec 4\u2014Theory, Measurement, Problems, Interpretation, EnMAP. EnMAP Field Guides Technical Report."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.jhydrol.2013.12.047","article-title":"Combining SMOS with visible and near\/shortwave\/thermal infrared satellite data for high resolution soil moisture estimates","volume":"516","author":"Piles","year":"2014","journal-title":"J. Hidrol."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Gerhards, M., Schlerf, M., Mallick, K., and Udelhoven, T. (2019). Challenges and Future Perspectives of Multi- Hyperspectral Thermal Infrared Remote Sensing for Crop Water-Stress Detection: A Review. Remote Sens., 11.","DOI":"10.3390\/rs11101240"},{"key":"ref_27","unstructured":"Hatfield, J., Baker, J., and Arkebauer, T.J. (2005). Leaf radiative properties and the leaf energy budget. Micrometeorology in Agricultural Systems, Crop Science Society of America, and Soil Science Society of America. Agronomy Monograph, American Society of Agronomy."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/0034-4257(94)00114-3","article-title":"Estimating PAR absorbed by vegetation from bidirectional reflectance measurements","volume":"51","author":"Roujean","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gitelson, A.A., Vi\u00f1a, A., Ciganda, V., Rundquist, D.C., and Arkebauer, T.J. (2005). Remote estimation of canopy chlorophyll content in crops. Geophys. Res Lett.","DOI":"10.1029\/2005GL022688"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.rse.2012.12.017","article-title":"MODIS-based corn grain yield estimation model incorporating crop phenology information","volume":"131","author":"Sakamoto","year":"2013","journal-title":"Remote Sens. Env."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1080\/01431169308954010","article-title":"The reflectance at the 950\u2013970 nm region as an indicator of plant water status","volume":"14","author":"Filella","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.rse.2005.07.008","article-title":"Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands","volume":"98","author":"Chen","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_33","first-page":"460","article-title":"Tomato yield and water use efficiency\u2014coupling effects between growth stage specific soil water deficits","volume":"65","author":"Chen","year":"2015","journal-title":"Soil Plant Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Liu, J., Hu, T., Feng, P., Wang, L., and Yang, S. (2019). Tomato yield and water use efficiency change with various soil moisture and potassium levels during different growth stages. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0213643"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Mzid, N., Cantore, V., De-Mastro, G., Albrizio, R., Sellami, M., and Todorovic, M. (2020). The Application of Ground Based and Satellite Remote Sensing for Estimation of Bio-Physiological Parameters of Wheat Grown Under Different Water Regimes. Water, 12.","DOI":"10.3390\/w12082095"},{"key":"ref_36","first-page":"309","article-title":"Monitoring vegetation systems in the Great Plains with ERTSThird ERTS Symposium","volume":"351 I","author":"Rouse","year":"1973","journal-title":"NASA SP"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/s10658-015-0821-6","article-title":"One-step reverse transcription loop-mediated isothermal amplification assay for rapid detection of melon yellow spot virus","volume":"145","author":"Zeng","year":"2016","journal-title":"Eur. J. Plant Pathol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhang, H., Niu, Y., and Han, W. (2019). Mapping Maize Water Stress Based on UAV Multispectral Remote Sensing. Remote Sens., 11.","DOI":"10.3390\/rs11060605"},{"key":"ref_39","first-page":"121","article-title":"Climate Change Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change","volume":"3","author":"Fischlin","year":"2007","journal-title":"Ecosyst. Their Prop. Goods Serv."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.rse.2015.11.013","article-title":"Response of high frequency Photochemical Reflectance Index (PRI) measurements to environmental conditions in wheat","volume":"173","author":"Magney","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.rse.2010.08.023","article-title":"The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies. A review and meta-analysis","volume":"115","author":"Garbulsky","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1111\/nph.13159","article-title":"Three causes of variation in the photochemical reflectance index (PRI) in evergreen conifers","volume":"206","author":"Wong","year":"2015","journal-title":"New Phytol."},{"key":"ref_43","first-page":"37","article-title":"Improvement in estimation of soil water deficit by integrating airborne imagery data into a soil water balance model","volume":"10","author":"Zhang","year":"2017","journal-title":"Int. J. Agric. Biol. Eng."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"13087","DOI":"10.1073\/pnas.1606162113","article-title":"A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers","volume":"113","author":"Gamon","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1093\/aob\/mcm222","article-title":"Stomatal regulation of photosynthesis in apple leaves: Evidence for different water-use strategies between two cultivars Catherine","volume":"100","author":"Massonnet","year":"2007","journal-title":"Ann. Bot."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/S0176-1617(00)80023-1","article-title":"Phenotypic plasticity and acclimation to water deficits in velvet-grass: A long-term greenhouse experiment. Changes in leaf morphology, photosynthesis and stress induced metabolites","volume":"157","author":"Pedrol","year":"2000","journal-title":"J. Plant Physiol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.13031\/trans.12083","article-title":"Leaf thickness and electrical capacitance as measures of plant water status","volume":"60","author":"Afzal","year":"2017","journal-title":"Trans. ASABE"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/S1658-3655(12)60019-3","article-title":"Effect of water stress on growth and water use efficiency (WUE) of some wheat cultivars (Triticum durum) grown in Saudi Arabia","volume":"3","author":"Tahar","year":"2010","journal-title":"J. Taibah Univ. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3619","DOI":"10.3390\/rs4113619","article-title":"Infrared Thermometry to Estimate Crop Water Stress Index and Water Use of Irrigated Maize in Northeastern Colorado","volume":"4","author":"Taghvaeian","year":"2012","journal-title":"Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Abdullah, N.H., Kuan, N., Ibrahim, A., Ismail, B., Majid, M.R., Ramli, R., and Mansor, N. (2018, January 5\u20136). Determination of soil water content using time domain reflectometer (TDR) for clayey soil. Proceedings of the Advances in Civil Engineering and Science Technology, Penang, Malaysia.","DOI":"10.1063\/1.5062642"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.ecolind.2015.02.027","article-title":"Best hyperspectral indices for tracing leaf water status as determined from leaf dehydration experiments","volume":"54","author":"Cao","year":"2015","journal-title":"Ecol. Indic."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1111\/pbi.12032","article-title":"Down-regulation of CBP80 gene expression as a strategy to engineer a drought-toletant potato","volume":"11","author":"Pieczynski","year":"2013","journal-title":"Plant Biotechnol. J."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1111\/jac.12259","article-title":"Aerial canopy temperature differences between fast- and slow-wilting soya bean genotypes","volume":"204","author":"Bai","year":"2018","journal-title":"J. Agron. Crop Sci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1117\/12.561223","article-title":"Estimating corn nitrogen status using ground\u2014Based and satellite multispectral data","volume":"5544","author":"Bausch","year":"2004","journal-title":"Remote Sens. Model. Ecosyst. Sustain."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1590\/S0102-05362003000400019","article-title":"A new method for estimating the leaf area index of cucumber and tomato plants","volume":"21","author":"Blanco","year":"2003","journal-title":"Hortic. Bras."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/TGRS.2008.2010457","article-title":"Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle","volume":"47","author":"Berni","year":"2009","journal-title":"Geosci. Remote Sens. IEEE Trans."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"06015011","DOI":"10.1061\/(ASCE)GT.1943-5606.0001372","article-title":"Improved TDR Method for Quality Control of Soil-Nailing Works","volume":"142","author":"Chung","year":"2016","journal-title":"J. Geotech. Geoenviron. Eng."},{"key":"ref_58","first-page":"108","article-title":"Using TDR in the agricultural water management","volume":"2","author":"Tanriverdi","year":"2005","journal-title":"KSUJ Sci. Eng."},{"key":"ref_59","first-page":"152","article-title":"A comparison of the gravimetric and TDR methods in terms of determining the soil water content of the corn plant","volume":"59","author":"Degirmenci","year":"2016","journal-title":"Ser. A Agron."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1029\/WR016i003p00574","article-title":"Electromagnetic determination of soil water content: Measurements in coaxial transmission lines","volume":"16","author":"Topp","year":"1980","journal-title":"Water Rersour. Res."},{"key":"ref_61","unstructured":"Matema, L.E. (2019). Adding solid fertilizers to soil in pot experiments. Protocols.io, 1\u201316."},{"key":"ref_62","unstructured":"Sun, Z.J., and Young, G.D. (2001, January 5\u20137). Saline clayey soil moisture measurement using time domain reflectometry. Proceedings of the TDR 2001 Symposium, Evanston, IL, USA."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1409","DOI":"10.1109\/TIM.2018.2792878","article-title":"Measurement of Dielectric Constant and Cross-Sectional Variations of a Wire","volume":"67","author":"Pommerenke","year":"2018","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.measurement.2016.10.044","article-title":"TDR-based monitoring of rising damp through the embedding of wire-like sensing elements in building structures","volume":"98","author":"Cataldo","year":"2017","journal-title":"Measurement"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1007\/s11738-015-1776-0","article-title":"Relationships between stomatal behaviour, spectral traits and water use and productivity of green peas (Pisum sativum L.) in dry seasons","volume":"37","author":"Nagy","year":"2015","journal-title":"Acta Physiol. Plant."},{"key":"ref_66","first-page":"137","article-title":"The Effect of Silicon on Minimizing the Implications of Water Stress on Tomato Plants","volume":"4","author":"Mohamed","year":"2020","journal-title":"Environ. Biodivers. Soil Secur."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s00271-018-0571-2","article-title":"Effect of water supply on the water use-related physiological traits and yield of snap beans in dry seasons","volume":"36","author":"Helyes","year":"2018","journal-title":"Irrig. Sci."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.scienta.2011.04.030","article-title":"Effects of deficit irrigation on biomass, yield, water productivity and fruit quality of processing tomato under semi-arid Mediterranean climate conditions","volume":"129","author":"Tringali","year":"2011","journal-title":"Sci. Hortic."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"383","DOI":"10.2478\/s11535-013-0279-5","article-title":"Effect of irrigation on yield parameters and antioxidant profiles of processing cherry tomato","volume":"9","author":"Szuvandzsiev","year":"2014","journal-title":"Open Life Sci."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"119","DOI":"10.17660\/ActaHortic.2013.971.13","article-title":"Different water supply and stomatal conductance correlates with yield quantity and quality parameters","volume":"971","author":"Helyes","year":"2013","journal-title":"Acta Hortic."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Tak\u00e1cs, S., P\u00e9k, Z., Cs\u00e1nyi, D., Daood, H.G., Szuvandzsiev, P., Palot\u00e1s, G., and Helyes, L. (2020). Influence of Water Stress Levels on the Yield and Lycopene Content of Tomato. Water, 12.","DOI":"10.3390\/w12082165"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.agwat.2019.06.008","article-title":"Yield, fruit quality and water use efficiency of tomato for processing under regulated deficit irrigation: A meta-analysis","volume":"222","author":"Lu","year":"2019","journal-title":"Agric. Water Manag."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1937","DOI":"10.3390\/rs70201937","article-title":"Regional equivalent water thickness modeling from remote sensing across a tree cover\/LAI gradient in Mediterranean forests of Northern Tunisia","volume":"7","author":"Chakroun","year":"2015","journal-title":"Remote Sens."},{"key":"ref_74","first-page":"367","article-title":"Remote-sensing-based biophysical models for estimating LAI of irrigated crops in Murry darling basin. Int. Arch. Photogramm","volume":"34","author":"Wittamperuma","year":"2012","journal-title":"Remote Sens. Spat. Inf. Sci."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1007\/s00704-009-0103-3","article-title":"Comparison of satellite and ground-based NDVI above different land-use types","volume":"98","author":"Tittebrand","year":"2009","journal-title":"Theor. Appl. Clim."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. 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