Estimation of transpiration in oil palm (Elaeis guineensis Jacq.) with the heat ratio method Received for publication: 9 February, 2016. Accepted for publication: 30 June, 2016. Doi: 10.15446/agron.colomb.v34n2.55649 1 Oil Palm Biology and Breeding Research Program, Colombian Oil Palm Research Center (Cenipalma). Bogota (Colombia). 2 Department of Biology, Faculty of Sciences, Universidad Nacional de Colombia. Bogota (Colombia). hmromeroa@unal.edu.co Agronomía Colombiana 34(2), 172-178, 2016 Estimation of transpiration in oil palm (Elaeis guineensis Jacq.) with the heat ratio method Estimación de la transpiración en palma de aceite (Elaeis guineensis Jacq.) por el método del radio de calor Cristihian Jarri Bayona-Rodríguez1 and Hernán Mauricio Romero1, 2 ABSTRACT RESUMEN Sap f low sensors were installed on the leaf petioles of 5-year-old oil palms (Elaeis guineensis Jacq.) to measure the xylem water f low for 12 days based on the heat ratio method (HRM). It was found that young leaves have higher sap f low rates, reaching values of over 250 cm3 h-1, and that sap f low f luctuations are directly related to weather conditions, particularly the vapor pressure deficit (VPD) component. It was observed that the sap f low rates remained constant and very close to 0 cm3 h-1 between 18:00 and 6:00 h and that the upward and downward movement of sap was faster during the day, with peak levels between 9:00 and 16:00 h. Under the evaluation conditions, the oil palm crop transpiration was estimated to be 1.15 mm H2O/ha-day. The HRM is a highly repeatable method and an useful tool to quantify the total oil palm transpiration. It could potentially be applied to irrigation. En palma de aceite (Elaeis guineensis Jacq.) de 5 años de edad se colocaron en la base peciolar de las hojas sensores de f lujo de savia, basados en el método del radio de calor (HRM), para cuantificar durante 12 días el movimiento de agua xilemática en la palma. Se encontró que las hojas jóvenes tienen un mayor f lujo de savia con valores superiores a los 250 cm3 h-1, se deter- minó que las f luctuaciones del f lujo de savia están directamente relacionadas con las condiciones climáticas siendo el déficit de presión de vapor (VPD) el componente de mejor explicación para dicha variación. Se observó que el f lujo de savia es cons- tante y muy cercano a 0 cm3 h-1 desde las 18:00 horas hasta las 6:00 horas, y en el día su ascenso y descenso son rápidos y mantiene sus valores máximos entre las 9:00 y 16:00 h. Se estimó que bajo las condiciones de la evaluación el cultivo de palma de aceite presentó una transpiración de 1,15 mm H2O/ ha-día. El HRM resultó un método con alta repetibilidad entre las palmas siendo una buena herramienta para cuantificar la transpiración total de la palma de aceite y podría ser utilizada potencialmente para la aplicación de riego. Key words: transpiration, sap f low, vapor pressure deficit. Palabras clave: transpiración, f lujo de savia, déficit de presión de vapor. the water demand of oil palms under different controlled conditions; however, the water requirements of oil palm in the field are not well known. Therefore, it is necessary to take direct measurements to determine water use under field conditions over time. Different measurement methods have been used to quan- tify the transpiration of plants, including the estimation of water use based on water balance and measurements of precipitation, drainage and changes in the water reserve available to plants (Ruiz-Peñalver et al., 2014), along with the lysimeter method, which, for perennials, requires a large infrastructure, such as that used in the study conducted on date palm (Tripler et al., 2012). However, even though Introduction Oil palm cultivation in Colombia has grown significantly in recent years (Fedepalma, 2014), with a planted area of 450 thousand hectares distributed in different regions of the country. Oil palm requires large amounts of water for good production (Corley and Tinker, 2003; Paramananthan, 2003; Carr, 2011) assuming an average water requirement of 6 mm per day. However, the measurements used to determine the overall transpiration rate of oil palm have been based on allometric parameters (Kallarackal et al., 2004; Legros et al., 2009) or on gas exchange measurements (Suresh et al., 2010; Rivera et al., 2012; Suresh et al., 2012). All of these studies have allowed us to partly understand http://dx.doi.org/10.15446/agron.colomb.v34n2.55649 173Bayona-Rodríguez and Romero: Estimation of transpiration in oil palm (Elaeis guineensis Jacq.) with the heat ratio method this method has been improved, the size of the plant is still a major limitation. For smaller species, inexpensive lysimeters can be used, as reported by Ruiz-Peñalver et al. (2014). Another method used is the Granier method (Granier, 1987) and its modifications (Burgess et al., 2001), a technique that measures sap flow rates and the volumetric f low of water in xylem tissue with a short heat pulse as an indicator. This is performed by measuring the ratio of the amount of heat transported to two symmetrically arranged temperature sensors to calculate the quantity and direction of the water f low (Smith and Allen, 1996; Bleby et al., 2004). Research with sap f low meters has been corroborated by other techniques, such as the lysimeter and water balance, with a high correlation between the different techniques. These results show the usefulness of this technique (Trcala and Čermák, 2012; Langensiepen et al., 2014). The aim of most of the studies that used the heat pulse method was to determine the water balance and f low of assimilates, such as the study by Haijun et al. (2015) under mesh-house conditions, in which the total transpiration of banana plants was determined. Based on information pro- vided by the device, they were able to determine the water demand of the plants and, therefore, the optimum irriga- tion schedule to prevent water stress. The same has been done with cacao (López-López et al. 2013) and eucalyptus (Bleby et al., 2012); various studies were able to determine and quantify the sap f low rate with a high degree of ac- curacy using the heat pulse method. The aim of this study was to measure the total transpiration of a commercial oil palm plantation under field conditions. We examined climate variables in order to understand which of them play significant roles in transpiration f luc- tuations. Furthermore, we studied the inf luences of leaf age on whole plant transpiration. The results have a potential to be used as a decision making tool in water management and supply under a precision agriculture scheme. Materials and methods Location of the study area This study was conducted in the Palmar de la Vizcaína Experiment Field Station, Santander, Colombia (6º58’ N; 73º42’ W), at an altitude of 140 m, with 75% relative humidi- ty and 32ºC of average daily temperature. Five years-old oil palms (Elaeis guineensis ) arranged in a 9 m wide triangle were selected for evaluation in a 10-ha lot planted in 2011. During the months of the study, the average rainfall was 280 mm. Sap flow measurement The heat ratio method (Bleby et al., 2012; Hölttä et al., 2015) was used to measure the sap f low with SFM1 sensors from ICT International (Australia). These sensors consisted of three needles. One of the needles generates a heat pulse, and the other two are each fitted with two thermocouples (Fig. 1). Three sensors were installed in each palm, in lea- ves 9, 17 and 25, just before the rudimentary leaf lets. The information was recorded every 10 min. throughout the day for cycles of 12 d, which is the time that it takes for the leaf to change positions in the phyllotaxy of the palm. The heat pulse used was 35 J, a value found in previous settings (data not shown). Additionally, tissue samples were collected from the petiole base to determine the leaf tissue thermal diffusivity constant by measuring the wet weight, dry weight and volume of fresh tissue. The heat ratio method (HRM) measures the ratio of the increase in temperature, following the release of a pulse of heat, at points equidistant downstream and upstream from a line heater. Heat pulse velocity is calculated as: Vh = k 1n (v1/v2)3600 (1)x Where k is thermal diffusivity of green (fresh) wood, x is distance (cm) between the heater and either temperature probe, and v1 and v2 are increases in temperature (from initial temperatures) at equidistant points downstream and upstream, respectively, x cm from the heater. The probe positions relative to the heater used with the HRM are -0.5 and 0.5 cm, hence x = 0.5 cm. FIgURE 1. Diagram of the heat ratio method used in the sap flow meters. Modified from the Heat Ratio Method (HRM) Installation & Operation Manual, ICT International Pty Ltd., Australia. 174 Agron. Colomb. 34(2) 2016 PPFD (µmol m-2 s-1) 0 400 800 1200 1600 2000 16 :0 0: 00 11 :0 0: 00 06 :0 0: 00 01 :0 0: 00 20 :0 0: 00 15 :0 0: 00 10 :0 0: 00 05 :0 0: 00 00 :0 0: 00 19 :0 0: 00 14 :0 0: 00 09 :0 0: 00 21 :0 0: 00 1110987654321 12 Vapor pressure deficit (KPa) 1.5 1.0 0.5 0.0 2.0 2.5 3.0 3.5 4.0 04 :3 0: 00 23 :4 0: 00 18 :5 0: 00 14 :0 0: 00 09 :1 0: 00 04 :2 0: 00 23 :3 0: 00 18 :4 0: 00 13 :5 0: 00 09 :0 0: 00 09 :2 0: 00 19 :1 0: 00 14 :2 0: 00 09 :3 0: 00 04 :4 0: 00 23 :5 0: 00 19 :0 0: 00 14 :1 0: 00 00 :0 0: 00 15 :0 0: 00 10 :1 0: 00 05 :2 0: 00 00 :3 0: 00 19 :4 0: 00 14 :5 0: 00 10 :0 0: 00 05 :1 0: 00 00 :2 0: 00 19 :3 0: 00 14 :4 0: 00 09 :5 0: 00 05 :0 0: 00 00 :1 0: 00 19 :2 0: 00 14 :3 0: 00 09 :4 0: 00 04 :5 0: 00 19 :5 0: 00 20 :0 0: 00 15 :1 0: 00 10 :2 0: 00 05 :3 0: 00 00 :4 0: 00 00 :5 0: 00 01 :0 0: 00 20 :1 0: 00 15 :2 0: 00 10 :3 0: 00 05 :4 0: 00 00 :5 0: 00 06 :0 0: 00 01 :1 0: 00 20 :2 0: 00 15 :3 0: 00 10 :4 0: 00 10 :5 0: 00 20 :3 0: 00 15 :4 0: 00 1110987654321 12 Atmosphere temperature (°C) 28 26 24 22 20 30 32 36 38 40 04 :3 0: 00 23 :4 0: 00 18 :5 0: 00 14 :0 0: 00 09 :1 0: 00 04 :2 0: 00 23 :3 0: 00 18 :4 0: 00 13 :5 0: 00 09 :0 0: 00 09 :2 0: 00 19 :1 0: 00 14 :2 0: 00 09 :3 0: 00 04 :4 0: 00 23 :5 0: 00 19 :0 0: 00 14 :1 0: 00 00 :0 0: 00 15 :0 0: 00 10 :1 0: 00 05 :2 0: 00 00 :3 0: 00 19 :4 0: 00 14 :5 0: 00 10 :0 0: 00 05 :1 0: 00 00 :2 0: 00 19 :3 0: 00 14 :4 0: 00 09 :5 0: 00 05 :0 0: 00 00 :1 0: 00 19 :2 0: 00 14 :3 0: 00 09 :4 0: 00 04 :5 0: 00 19 :5 0: 00 20 :0 0: 00 15 :1 0: 00 10 :2 0: 00 05 :3 0: 00 00 :4 0: 00 00 :5 0: 00 01 :0 0: 00 20 :1 0: 00 15 :2 0: 00 10 :3 0: 00 05 :4 0: 00 00 :5 0: 00 06 :0 0: 00 01 :1 0: 00 20 :2 0: 00 15 :3 0: 00 10 :4 0: 00 10 :5 0: 00 20 :3 0: 00 15 :4 0: 00 1110987654321 12 Relative humidity (%) 0 20 40 60 80 100 04 :3 0: 00 23 :4 0: 00 18 :5 0: 00 14 :0 0: 00 09 :1 0: 00 04 :2 0: 00 23 :3 0: 00 18 :4 0: 00 13 :5 0: 00 09 :0 0: 00 09 :2 0: 00 19 :1 0: 00 14 :2 0: 00 09 :3 0: 00 04 :4 0: 00 23 :5 0: 00 19 :0 0: 00 14 :1 0: 00 00 :0 0: 00 15 :0 0: 00 10 :1 0: 00 05 :2 0: 00 00 :3 0: 00 19 :4 0: 00 14 :5 0: 00 10 :0 0: 00 05 :1 0: 00 00 :2 0: 00 19 :3 0: 00 14 :4 0: 00 09 :5 0: 00 05 :0 0: 00 00 :1 0: 00 19 :2 0: 00 14 :3 0: 00 09 :4 0: 00 04 :5 0: 00 19 :5 0: 00 20 :0 0: 00 15 :1 0: 00 10 :2 0: 00 05 :3 0: 00 00 :4 0: 00 00 :5 0: 00 01 :0 0: 00 20 :1 0: 00 15 :2 0: 00 10 :3 0: 00 05 :4 0: 00 00 :5 0: 00 06 :0 0: 00 01 :1 0: 00 20 :2 0: 00 15 :3 0: 00 10 :4 0: 00 10 :5 0: 00 20 :3 0: 00 15 :4 0: 00 1110987654321 12 Sap flow (cm3 h-1) 0 50 150 100 200 250 300 04 :3 0: 00 23 :4 0: 00 18 :5 0: 00 14 :0 0: 00 09 :1 0: 00 04 :2 0: 00 23 :3 0: 00 18 :4 0: 00 13 :5 0: 00 09 :0 0: 00 09 :2 0: 00 19 :1 0: 00 14 :2 0: 00 09 :3 0: 00 04 :4 0: 00 23 :5 0: 00 19 :0 0: 00 14 :1 0: 00 00 :0 0: 00 15 :0 0: 00 10 :1 0: 00 05 :2 0: 00 00 :3 0: 00 19 :4 0: 00 14 :5 0: 00 10 :0 0: 00 05 :1 0: 00 00 :2 0: 00 19 :3 0: 00 14 :4 0: 00 09 :5 0: 00 05 :0 0: 00 00 :1 0: 00 19 :2 0: 00 14 :3 0: 00 09 :4 0: 00 04 :5 0: 00 19 :5 0: 00 20 :0 0: 00 15 :1 0: 00 10 :2 0: 00 05 :3 0: 00 00 :4 0: 00 00 :5 0: 00 01 :0 0: 00 20 :1 0: 00 15 :2 0: 00 10 :3 0: 00 05 :4 0: 00 00 :5 0: 00 06 :0 0: 00 01 :1 0: 00 20 :2 0: 00 15 :3 0: 00 10 :4 0: 00 10 :5 0: 00 20 :3 0: 00 15 :4 0: 00 1110987654321 12 Leaf 9 Leaf 25Leaf 17 17 :0 0: 00 12 :0 0: 00 07 :0 0: 00 02 :0 0: 00 22 :0 0: 00 18 :0 0: 00 13 :0 0: 00 08 :0 0: 00 03 :0 0: 00 23 :0 0: 00 19 :0 0: 00 14 :0 0: 00 09 :0 0: 00 04 :0 0: 00 00 :0 0: 00 20 :0 0: 00 15 :0 0: 00 10 :0 0: 00 05 :0 0: 00 01 :0 0: 00 21 :0 0: 00 16 :0 0: 00 11 :0 0: 00 06 :0 0: 00 02 :0 0: 00 22 :0 0: 00 17 :0 0: 00 12 :0 0: 00 07 :0 0: 00 03 :0 0: 00 23 :0 0: 00 18 :0 0: 00 13 :0 0: 00 08 :0 0: 00 04 :0 0: 00 00 :0 0: 00 19 :0 0: 00 14 :0 0: 00 09 :0 0: 00 05 :0 0: 00 20 :0 0: 00 15 :0 0: 00 10 :0 0: 00 FIgURE 2. Daily sap flow rate in 3 leaves of oil palm during a 12-day sampling period by the heat ratio method (n=4). PPFD, photosynthetic photon flux density; RH, relative humidity; AT, ambient temperature; VPD, vapor pressure deficit. Environmental variables throughout the sampling period. 175Bayona-Rodríguez and Romero: Estimation of transpiration in oil palm (Elaeis guineensis Jacq.) with the heat ratio method C um ul at iv e vo lu m e (L ) 0 5 10 15 20 25 16 :4 0: 00 09 :0 0: 00 00 :2 0: 00 21 :0 0: 00 1110987654321 12 Leaf 9 Leaf 25Leaf 17 15 :4 0: 00 08 :0 0: 00 23 :2 0: 00 14 :4 0: 00 07 :0 0: 00 22 :2 0: 00 13 :4 0: 00 06 :0 0: 00 21 :2 0: 00 12 :4 0: 00 05 :0 0: 00 20 :2 0: 00 11 :4 0: 00 04 :0 0: 00 19 :2 0: 00 10 :4 0: 00 03 :0 0: 00 18 :2 0: 00 09 :4 0: 00 02 :0 0: 00 17 :2 0: 00 08 :4 0: 00 01 :0 0: 00 16 :2 0: 00 07 :4 0: 00 00 :0 0: 00 15 :2 0: 00 06 :4 0: 00 23 :0 0: 00 14 :2 0: 00 05 :4 0: 00 22 :0 0: 00 13 :2 0: 00 FIgURE 3. Accumulated volume of water transported by 3 leaves of oil palm during a 12-day sampling period by the heat ratio method (n = 4). Climate data Air temperature, relative humidity, photosynthetically active radiation, soil moisture, soil temperature, rainfall and net radiation data were recorded with a Biomet weather station (Sutron Corp - Sterling, VA) anchored to the Eddy Covariance system installed in the study area. The VPD was calculated using software free to Autogrow (http://www. autogrow.com) with temperature data, relative humidity and radiation. Data analysis The sap f low data were analyzed with SapFlowTool 1.4.1 software from ICT-International / Phyto - IT (Australia). The daily f low and water consumption accumulation over time were calculated to estimate the total transpiration. The data were statistically analyzed with SAS software, the statistical assumptions (homogeneity of variance, normal distribution and randomness) were tested. In order to determine the differences between the palms and leaves, Anova, Duncan's multiple range test, and multiple regressions associated with weather data were performed. Results During the sampling days, the soil water potential was constant in a range of -0.1 to -0.2 MPa, and the sap f low showed no significant difference in any of the evaluated palms. However, differences were found between leaf 9 and leaf 25, where leaf 17 had an intermediate value between them. A similar pattern was found in each of the sampled leaves (Fig. 2), where the sap f low rate ranged from 10 to 20 cm3 h-1 overnight - from 18:00 HR to approximately 6:00 HR - increasing 20-fold 2 h after the arrival of the first rays of light (Fig. 2A). The highest f low rates occurred between 9:00 and 16:00 HR (220 cm3 h-1), with f luctuations between 20 and 40 cm3 h-1. At 16:00 HR, the f low rate started to decrease, reaching the lowest values after 18:00 HR; this cycle repeated every day during the sampling period. Ad- ditionally, a reduction in the sap f low was observed after day 7 of the evaluation, associated with a decrease in vapor pressure deficit (VPD). The volume of water transported through the leaf petiole bases during the sampling period was calculated based on the recorded information (Fig. 3). Leaf 9 transported the largest volume of water (21.65 L), followed by leaf 17 (17.20 L) and leaf 25 (14.6 L) during the 12 d of sampling. This vari- able showed statistically significant differences over time from day 4. No statistically significant differences were found between palms, which indicated a good repeatability of sampling. Additionally, the volume of water transported increased during the day, as illustrated by valleys related to the lower volume of water transported during the night. Discussion The results are similar to those found in pindo palm (Madurapperuma et al., 2009), pine (Chang et al., 2014) and wheat (Langensiepen et al., 2014), among other species. Daily f luctuations are directly associated with soil water conditions and weather variations that inf luence gas ex- change in plants. For example, in jujube (Chen et al., 2014), a reduction in soil water potential and change of meteoro- logical factors caused a direct response in photosynthesis and transpiration rates, which was ref lected in reduced sap f low. We found that sap f low rates are closely related to weather variables (Fig. 4), where the vapor pressure deficit (VPD) was the most correlated factor. These results are similar to those reported for oil palm in Indonesia (Niu et al., 2015). A multiple regression was also performed, taking into account the main components (AT, PPFD and VPD) (Fig. 5), in which a high linearity was found. However, it is 176 Agron. Colomb. 34(2) 2016 0 50 150 100 200 250 9: 10 :0 0 8: 20 :0 0 7: 30 :0 0 6: 40 :0 0 5: 50 :0 0 5: 00 :0 0 4: 10 :0 0 3: 20 :0 0 2: 30 :0 0 1: 40 :0 0 0: 50 :0 0 0: 00 :0 0 10 :0 0: 00 20 :0 0: 00 19 :1 0: 00 18 :2 0: 00 17 :3 0: 00 16 :4 0: 00 15 :5 0: 00 15 :0 0: 00 14 :1 0: 00 13 :2 0: 00 12 :3 0: 00 11 :4 0: 00 10 :5 0: 00 20 :5 0: 00 21 :4 0: 00 23 :2 0: 00 22 :3 0: 00 S ap fl ow ( cm 3 h- 1 ) V P D ( K Pa ) 2.5 2 1.5 1 0.5 3 0 0 50 150 100 200 250 9: 10 :0 0 8: 20 :0 0 7: 30 :0 0 6: 40 :0 0 5: 50 :0 0 5: 00 :0 0 4: 10 :0 0 3: 20 :0 0 2: 30 :0 0 1: 40 :0 0 0: 50 :0 0 0: 00 :0 0 10 :0 0: 00 20 :0 0: 00 19 :1 0: 00 18 :2 0: 00 17 :3 0: 00 16 :4 0: 00 15 :5 0: 00 15 :0 0: 00 14 :1 0: 00 13 :2 0: 00 12 :3 0: 00 11 :4 0: 00 10 :5 0: 00 20 :5 0: 00 21 :4 0: 00 23 :2 0: 00 22 :3 0: 00 S ap fl ow ( cm 3 h- 1 ) A m bi en t t em pe ra tu re ( °C ) 34 32 30 28 26 24 22 36 20 0 100 50 150 200 250 9: 10 :0 0 8: 20 :0 0 7: 30 :0 0 6: 40 :0 0 5: 50 :0 0 5: 00 :0 0 4: 10 :0 0 3: 20 :0 0 2: 30 :0 0 1: 40 :0 0 0: 50 :0 0 0: 00 :0 0 10 :0 0: 00 20 :0 0: 00 19 :1 0: 00 18 :2 0: 00 17 :3 0: 00 16 :4 0: 00 15 :5 0: 00 15 :0 0: 00 14 :1 0: 00 13 :2 0: 00 12 :3 0: 00 11 :4 0: 00 10 :5 0: 00 20 :5 0: 00 21 :4 0: 00 23 :2 0: 00 22 :3 0: 00 S ap fl ow ( cm 3 h- 1 ) R H ( % ) 100 80 60 40 20 120 0 0 100 50 150 200 250 9: 10 :0 0 8: 20 :0 0 7: 30 :0 0 6: 40 :0 0 5: 50 :0 0 5: 00 :0 0 4: 10 :0 0 3: 20 :0 0 2: 30 :0 0 1: 40 :0 0 0: 50 :0 0 0: 00 :0 0 10 :0 0: 00 20 :0 0: 00 19 :1 0: 00 18 :2 0: 00 17 :3 0: 00 16 :4 0: 00 15 :5 0: 00 15 :0 0: 00 14 :1 0: 00 13 :2 0: 00 12 :3 0: 00 11 :4 0: 00 10 :5 0: 00 20 :5 0: 00 21 :4 0: 00 23 :2 0: 00 22 :3 0: 00 S ap fl ow ( cm 3 h- 1 ) P P FD ( µ m ol m -2 s -1 ) 1600 1400 1200 1000 800 600 400 200 1800 0 PPFD RH AT VDP FIgURE 4. Relationship of sap flow rates of 3 leaves of oil palm by the heat ratio method with climate variables. PAR, photosynthetically active radia- tion; RH, relative humidity; AT, ambient temperature; VPD, vapor pressure deficit (n = 4). Leaf 9, leaf 17 and leaf 25. 177Bayona-Rodríguez and Romero: Estimation of transpiration in oil palm (Elaeis guineensis Jacq.) with the heat ratio method necessary to include other variables to complete a predictive model for irrigation, as was done for jujube and banana (Lu et al., 2002; Haijun et al., 2015; Chen et al., 2014). Based on the water f low data, including 33 leaves, our estimates of whole-plant water use were calculated as the sum of the rates from individual leaves, which is necessary and useful to assess canopy variability. We found that wa- ter use per palm was substantially higher in young leaves than in older leaves. The estimated water consumption per palm was 80.5 L d-1, for a transpiration of 1.15 mm d-1, very similar to the value reported by Niu et al. (2015). In the literature (Mutert et al., 1999; Corley and Tinker, 2003), the estimated values based on evapotranspiration O bs er ve d va lu e (c m 3 h- 1 ) Leaf 9 0 50 100 150 200 250 0 50 100 150 200 250 R2=0.98109 O bs er ve d va lu e (c m 3 h- 1 ) Leaf 17 0 50 100 150 200 250 0 50 100 150 200 250 R2=0.98301 O bs er ve d va lu e (c m 3 h- 1 ) Predicted value (cm3 h-1) Leaf 25 0 50 100 150 200 250 0 50 100 150 200 250 R2=0.98167 FIgURE 5. Multiple regression for leaves 9, 17 and 25 of oil palm, taking VPD, PPFD and RH into account to develop predictive models (n=4). and allometric calculations are higher, possibly because those estimations do not directly measure plant water consumption. Conclusions The analysis of sap f low measurements showed that each leaf had a different water consumption rate, and young leaves had higher water consumption values. This moni- toring allowed us to determine that, for the measurement conditions, the transpiration of one hectare of oil palm was 1.15 mm d-1. The sap f low rates in the oil palm were closely related to weather variations, particularly vapor pressure deficit, VPD, which is the variable that best explains the f luctuations in water movement in oil palm. Additionally, measurements showed high repeatability using the heat ratio method (HRM) of ICT-International (Australia). However, it is necessary to assess the crop in different seasons to determine water requirements during the dry season and to integrate crop transpiration data with the evapotranspiration data of the ecosystem. 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