{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T23:11:42Z","timestamp":1768518702936,"version":"3.49.0"},"reference-count":59,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,7,29]],"date-time":"2021-07-29T00:00:00Z","timestamp":1627516800000},"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>The goal of this research is to use a WORKSWELL WIRIS AGRO R INFRARED CAMERA (WWARIC) to assess the crop water stress index (CWSIW) on tomato growth in two soil types. This normalized index (CWSI) can map water stress to prevent drought, mapping yield, and irrigation scheduling. The canopy temperature, air temperature, and vapor pressure deficit were measured and used to calculate the empirical value of the CWSI based on the Idso approach (CWSIIdso). The vegetation water content (VWC) was also measured at each growth stage of tomato growth. The research was conducted as a 2 \u00d7 4 factorial experiment arranged in a Completely Randomized Block Design. The treatments imposed were two soil types: sandy loam and silt loam, with four water stress treatment levels at 70\u2013100% FC, 60\u201370% FC, 50\u201360% FC, and 40\u201350% FC on the growth of tomatoes to assess the water stress. The results revealed that CWSIIdso and CWSIW proved a strong correlation in estimating the crop water status at R2 above 0.60 at each growth stage in both soil types. The fruit expansion stage showed the highest correlation at R2 = 0.8363 in sandy loam and R2 = 0.7611 in silt loam. VWC and CWSIW showed a negative relationship with a strong correlation at all the growth stages with R2 values above 0.8 at p &lt; 0.05 in both soil types. Similarly, the CWSIW and yield also showed a negative relationship and a strong correlation with R2 values above 0.95, which indicated that increasing the CWSIW had a negative effect on the yield. However, the total marketable yield ranged from 2.02 to 6.8 kg plant\u22121 in sandy loam soil and 1.75 to 5.4 kg plant\u22121 in silty loam soil from a low to high CWSIW. The highest mean marketable yield was obtained in sandy loam soil at 70\u2013100% FC (0.0 &lt; CWSIW \u2264 0.25), while the least-marketable yield was obtained in silty loam soil 40\u201350% FC (0.75 &lt; CWSIW \u2264 1.0); hence, it is ideal for maintaining the crop water status between 0.0 &lt; CWSIW \u2264 0.25 for the optimum yield. These experimental results proved that the WWARIC effectively assesses the crop water stress index (CWSIW) in tomatoes for mapping the yield and irrigation scheduling.<\/jats:p>","DOI":"10.3390\/s21155142","type":"journal-article","created":{"date-parts":[[2021,7,29]],"date-time":"2021-07-29T21:21:21Z","timestamp":1627593681000},"page":"5142","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Rapid Estimation of Crop Water Stress Index on Tomato Growth"],"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, No. 483, Wushan Road, Tianhe District, Guangzhou 510642, China"}]},{"given":"Jiuhao","family":"Li","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, No. 483, Wushan Road, Tianhe District, Guangzhou 510642, China"}]},{"given":"Yubin","family":"Lan","sequence":"additional","affiliation":[{"name":"College of Engineering, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology (NPAAC), South China Agriculture University, No. 483, Wushan Road, Tianhe District, Guangzhou 510642, China"}]},{"given":"Sadick Amoakohene","family":"Appiah","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, No. 483, Wushan Road, Tianhe District, Guangzhou 510642, 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, No. 483, Wushan Road, Tianhe District, Guangzhou 510642, China"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Civil Engineering, South China Agriculture University, No. 483, Wushan Road, Tianhe District, Guangzhou 510642, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,29]]},"reference":[{"key":"ref_1","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_2","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_3","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_4","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_5","doi-asserted-by":"crossref","first-page":"367","DOI":"10.5194\/isprsarchives-XXXIX-B8-367-2012","article-title":"Remote-sensing-based biophysical models for estimating LAI of irrigated crops in Murry darling basin","volume":"34","author":"Wittamperuma","year":"2012","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_6","unstructured":"Sui, R., and Baggard, J. (2020). Development and evaluation of a variable rate irrigation method in Mississippi Delta. Trans. Am. Soc. Agric. Biol. Eng., 19."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.scienta.2015.12.051","article-title":"Effect of water deficit on the agronomical performance and quality of processing tomato","volume":"200","author":"Lahoz","year":"2016","journal-title":"Sci. Hortic."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.jhydrol.2014.12.051","article-title":"A soil water based index as a suitable agricultural drought indicator","volume":"522","author":"Gumuzzio","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_9","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":"Comput. Electron. Agric."},{"key":"ref_10","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_11","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_12","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_13","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_14","doi-asserted-by":"crossref","unstructured":"Jackson, R. (1982). Canopy Temperature and Crop Water Stress, Academic Press.","DOI":"10.1016\/B978-0-12-024301-3.50009-5"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/0002-1571(82)90020-6","article-title":"Non-water stressed baselines: A key to measuring and interpreting plant water stress","volume":"27","author":"Idso","year":"1982","journal-title":"Agric. Meteorol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/0002-1571(81)90032-7","article-title":"Normalizing the stress degree-day parameter for environmental variability","volume":"24","author":"Idso","year":"1981","journal-title":"Agric. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.agwat.2017.04.016","article-title":"A satellite based crop water stress index for irrigation scheduling in sugarcane fields","volume":"189","author":"Veysi","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/978-1-4939-3356-3_17","article-title":"Assessing drought responses using thermal infrared imaging","volume":"1398","author":"Prashar","year":"2016","journal-title":"Methods Mol. Biol."},{"key":"ref_19","first-page":"239","article-title":"Remote sensing of plant stresses and its use in irrigation management","volume":"1038","author":"Jones","year":"2012","journal-title":"VII Int. Symp. Irrig. Hortic. Crops"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Matese, A., Baraldi, R., Berton, A., Cesaraccio, C., Di-Gennaro, S., Duce, P., and Zaldei, A. (2018). Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods. Remote Sens., 10.","DOI":"10.3390\/rs10010114"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1016\/j.rse.2003.10.021","article-title":"Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans","volume":"92","author":"Jackson","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_22","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_23","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_24","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_25","first-page":"251","article-title":"Durum wheat breeding for abiotic stresses resistance: Defining physiological traits and criteria","volume":"40","year":"2000","journal-title":"Options Mediterr."},{"key":"ref_26","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_27","doi-asserted-by":"crossref","first-page":"4735","DOI":"10.1002\/ece3.3051","article-title":"Deriving a light use efciency estimation algorithm using in situ hyperspectral and eddy covariance measurements for a maize canopy in Northeast China","volume":"7","author":"Zhang","year":"2017","journal-title":"Ecol. Evol."},{"key":"ref_28","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_29","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_30","doi-asserted-by":"crossref","first-page":"1133","DOI":"10.1029\/WR017i004p01133","article-title":"Canopy temperature as a crop water stress indicator","volume":"17","author":"Jackson","year":"1981","journal-title":"Water Resour. Res."},{"key":"ref_31","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_32","first-page":"372","article-title":"Evaluation of Crop Water Stress Index (CWSI) for Eggplant under Varying Irrigation Regimes Using Surface and Subsurface Drip Systems","volume":"4","author":"Yazarb","year":"2015","journal-title":"Agric. Agric. Sci. Procedia"},{"key":"ref_33","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_34","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. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/S0034-4257(02)00036-6","article-title":"Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1. Theoretical approach","volume":"82","author":"Ceccato","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_36","unstructured":"Tanriverdi, C., Atilgan, A., Degirmenci, H., and Akyuz1, A. (2017). Comparasion of Crop Water Stress Index (CWSI) and Water Deficit Index (WDI) by using Remote Sensing (RS). Infrastruct. Ecol. Rural AREAS, 879\u2013894."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/0378-3774(94)90049-3","article-title":"Relationships between leaf water potential, CWSI, yield and fruit quality of sweet lime under drip irrigation","volume":"25","author":"Sepaskhah","year":"1994","journal-title":"Agric. Water Manag."},{"key":"ref_38","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_39","first-page":"10074","article-title":"Relationships among top-of-atmosphere radiation and atmospheric state variables in observations and CESM","volume":"120","author":"Trenberth","year":"2015","journal-title":"Adv. Earth Space Sci."},{"key":"ref_40","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_41","first-page":"189","article-title":"Analysis of crop water stress index (CWSI) for estimating stem water potential in grapevines: Comparison between natural reference and baseline approaches","volume":"1150","author":"Espinace","year":"2017","journal-title":"Acta Hortic."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.jappgeo.2018.01.022","article-title":"Comparison of performance of inclinometer casing and TDR technique","volume":"150","author":"Aghda","year":"2018","journal-title":"J. Appl. Geophys."},{"key":"ref_43","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_44","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_45","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_46","doi-asserted-by":"crossref","unstructured":"Menziani, M. (1996). Soil volumetric water content measurement using TDR. Ann. Geofis., 91\u201396.","DOI":"10.4401\/ag-3953"},{"key":"ref_47","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_48","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_49","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.agwat.2004.09.003","article-title":"Water requirement of drip irrigated tomatoes grown in greenhouse in tropical environment","volume":"71","author":"Harmanto","year":"2005","journal-title":"Agric. Water Manag."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.catena.2013.12.005","article-title":"Response of temporal variation of soil moisture to vegetation restoration in semi-arid Loess Plateau, China","volume":"115","author":"Yang","year":"2014","journal-title":"CATENA"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1002\/2014WR016398","article-title":"Irrigation with desalinated water: A step toward increasing water saving and crop yields","volume":"51","author":"Silber","year":"2015","journal-title":"Water Resour. Res."},{"key":"ref_52","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_53","doi-asserted-by":"crossref","first-page":"1837","DOI":"10.1016\/j.agwat.2009.08.004","article-title":"Poverty reduction with irrigation investment: An empirical case study from Tigray, Ethiopia","volume":"96","author":"Gebregziabher","year":"2009","journal-title":"Agric. Water Dev."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/ird.114","article-title":"Irrigation and poverty alleviation: Review of the empirical evidence","volume":"53","author":"Hussain","year":"2004","journal-title":"Irrig. Drain."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"923","DOI":"10.1016\/j.rse.2010.11.019","article-title":"Foliar nutrient and water content in subtropical tree islands: A new chemohydrodynamic link between satellite vegetation indices and foliar d15N values","volume":"3","author":"Wang","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_56","first-page":"1","article-title":"Water Stress in Plants: Causes, Effects and Responses","volume":"10","author":"Lisar","year":"2012","journal-title":"Water Stress"},{"key":"ref_57","first-page":"34","article-title":"The influence of water deficit on vegetative growth, physiology, fruit yield and quality in eggplants","volume":"27","author":"Kirnak","year":"2001","journal-title":"Bulg. J. Plant Physiol."},{"key":"ref_58","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_59","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."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/15\/5142\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:36:41Z","timestamp":1760164601000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/15\/5142"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,29]]},"references-count":59,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["s21155142"],"URL":"https:\/\/doi.org\/10.3390\/s21155142","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,29]]}}}