SOME RESULTS ON WATER AND NUTRIENT CONSUMPTION OF A GREENHOUSE TOMATO CROP GROWN IN ROCKWOOL

SOME RESULTS ON WATER AND NUTRIENT CONSUMPTION OF A GREENHOUSE TOMATO CROP GROWN IN ROCKWOOL JEMAA R BOULARD T., BAILLE A. I.N.R.A., Unité de Bioclimatologie d'avignon 84914 Avignon Cedex 9 FRANCE. Abstract Transpiration (TR) and nutrient consumption (N) of a greenhouse tomato crop grown in rockwool were monitored during spring and summer periods. Transpiration measurements were obtained by two ways: (i) hourly values given by an electronic balance supporting four plants; (ii) daily values estimated by the difference between supply and drainage rates of a complete row (108 plants). Nutrient (N03, K, Ca, Mg and P) concentration in the solutions (supply and drainage) were determined each week from chemical analysis of samples of both solutions. Data on crop transpiration obtained with the two methods agree fairly well at daily scale. They were used to test and validate two models of canopy transpiration (TR): i) a model based on the Penman-Monteith approach, where stomatal resistance to water vapour transfer is expressed as a function of global radiation (G) and vapour pressure deficit (D); (ii) a simplified formula derived from the previous model: TR = A*G + B*D, where A and B are two parameters that were identified by fitting the calculated and measured transpiration all along the crop development (April to July). Comparison between predicted and measured values showed that the two models simulate quite closely crop transpiration. The data on mineral absorption of the system (crop + substrate) indicated that the absorption rates of the various nutrients (N) followed quite closely the transpiration rate. The ratio N/TR remained rather stable for all components, with some slight fluctuations for N03 and K. Key words: greenhouse, irrigation, model, nutrient uptake, transpiration, tomato. 1. Introduction In protected cultivation, maximum return on investment implies rational irrigation practices and correct evalution of water requirements: water shortage induces plant stress that reduces growth and yield. Alternatively, excess watering wastes water and nutrients and increases environmental pollution load. To avoid such risks and to improve the efficiency of water and fertilizers, accurate estimates of greenhouse crop transpiration and mineral absorption are valuable information for the growers. As already stated by different authors (Fuchs, 1990; Boulard and Bailie, 1993), greenhouse crop évapotranspiration depends strongly on the greenhouse characteristics (cladding material) and climate equipment (shading screen, fog system, type of heating and ventilation). Therefore, reliable estimation of plant requirements must be based on the knowledge of interaction between greenhouse climate and crop response. In the 70's, simplified models were proposed (De Villèle, 1974) to evaluate the transpiration from the only measure of the outside global radiation using specific coefficients (cladding and crop coefficient). Very simple and commonly used under greenhouse, the precision of these methods lies on the estimation of crop coefficients that depend on crop, climate and greenhouse conditions. Then, if the type of climate, greenhouse and crop change, the model parameters can no longer be valid. Acta Horticulturae 408, 1995 Soilless Cultivation Technology for Protected Crops 137

More recently, explicative models were developed for greenhouse crops (Stanghellini, 1987; Yang et al 1990; Boulard et al 1991; Jolliet and Bailey, 1992). They are based on Penman-Monteith (P.M.) formula which expresses the transpiration as function of two climatic parameters: global radiation (G) and water vapour deficit (D) and of physiological parameters such as the aerodynamic (r a ) and stomatal (r s ) resistances and the leaf area index (LAI). In this paper, our purpose is: 1 to analyse the predictions of a transpiration model based on the P.M. equation, including the effects of stomatal regulation; 2 to derive a simplified model for irrigation control objectives; 3 to identify the simplified model parameters. Furthermore, we have taken advantage of the soilless cultivation technology (the crop is grown on rockwool) to measure the mineral absorption of the system constituted by the rockwool slabs and the crop. The long term balance between transpiration and nutrient (NO3, P, K, Ca and Mg) is presented and discussed. 2. Theory Greenhouse tomato crop transpiration TH (W.rtr 2 ) can be estimated by the P.M. formula (for the meaning of symbols, see attached list in annex): TR = A. ( ra / 2 ) Ga + P' C P LAI D (1) A.( ra / 2)+y.rt A.( ra / 2)+y.rt (1) In this equation, the transpiration rate (TR) is divided in two components: a radiative one, proportional to the radiation absorbed by the crop (Ga), and an advective one, proportional to the vapour pressure deficit (D). These two components of transpiration include rt, the total canopy resistance which is the sum of the aerodynamic (r a ) and stomatic (r s ) resistance, the latter one being dependent - among others - on climatic parameters. Previous works (Stanghellini, 1987 and Boulard et al., 1991) showed that r s can be expressed as a function of G, D and T: r s = rsmin * f 1 (G) * f2(d) * f 3 (T) (2) where r sm in is the minimum stomatal resistance of the crop, and fi the response functions to climatic parameters. Due to the large number of parameters involved, this approach is somewhat difficult to apply in irrigation control. Simplification of eqs. (1) and (2) leads to the the following formula: R=A*Ga+B*D (3) where the values of the key parameters A and B can be identified in-situ by using the calculated and measured values of transpiration and climatic parameters. 3. Material and methods 3.1. Greenhouse and experimental set up. The study was carried out in a climate controlled greenhouse equipped with both heating (soil and air) and cooling (fog system, aeration) devices. Tomato plants, cv. Rondello, were planted in double rows (January 1991) and grown on rockwool slabs placed on a 138

white plastic mulch. Inside and outside climate parameters (dry and wet bulb temperatures, global radiation) were monitored at hourly time step. 3.2. Transpiration measurements. Crop transpiration was obtained by two methods: (i) a weighting lysimeter which included a frame supporting four plant and an independent system of irrigation and drainage, as shown on fig (la). The decrease in weight (accuracy ± 1 g) was monitored and recorded at hourly time step. (ii) recording the water budget of a complete tomato row (108 plants) by measuring input and output, i.e. water supply (1) and drainage rate (Dr) (figlb). Neglecting the storage term on long time step (day) allows to calculate TR from: TR = I - Dr (4) 3.3. Determination of nutrient uptake. The concentration of nutrients (NO3, P, K, Ca and Mg) in supply and drainage was determined each week from chemical analyses of samples of the supplied and drained solutions. From these measurements (expressed in mg per litre) and the measurements of the volume (expressed in mm per week) of the supplied (I) and drained (Dr) solutions, the nutrient absorption N (j) for an element (j) (expressed on Kg per hectare and per week) can be estimated from: N(j) = Ci*I - Cr*Dr (5) where Ci (mg/1) and Cr (mg/1) are, respectively, the concentrations of the nutrient (j) in the supply drainage solutions. 4. Results and discussion 4.1. Validation of the transpiration model Daily courses of measured (lysimeter and water budget) and calculated transpiration (formula 1) are plotted in fig (2a) together with average and maximum daily values of temperature and saturation deficit (fig 2b). Agreement between measured and calculated values can be observed when the plants were young and when the climate conditions were near-optimal (from 7 April to 12 May). Later (end of May to end of June), with older plants and increase of greenhouse air temperature and saturation deficit, we note an overestimation of the model during periods when the fog system was not used. Comparison of TR during warm periods with (28/5 to 22/6) and without (12/5 to 28/5) fog system shows clearly that the use of the fog system can limit the stress intensity. The Penman-Monteith formula allows to estimate the respective contributions of the radiative and advective parts of the transpiration (fig 3). The advective part of transpiration represents 43 % of the total transpiration and should not be neglected. For the period from 7 to 18 l h of April, the accuracy of the calculated transpiration is good when compared to lysimeter measurements (fig 4). These results indicate that, when stress conditions are not too strong, an explicative model based on Penman-Monteith formulation (eq. 1) completed by the description of the stomatic regulation (eq. 2) allows a precise estimation of greenhouse tomato crop transpiration. Nevertheless, this model is not well-adapted to irrigation control because it involves the estimation of numerous crop parameters (LAI, r S) r a ) that are not easily available in production greenhouse. Therefore, a more simple model (eq. 3) was derived and tested in operational procedures. 139

4.2. Test of the simplified model and parameters identification The use of the simplified model (eq. 3) for operational procedure calls for the identification of parameters A and B. This was performed by means of the following system of two equations derived from eq. 1: TR=A*Ga+B*D (3) A/B = (A.ra)/(2.p.Cp.LAI) (6) In the following, Ga was estimated from measurements of the incident global radiation on the crop. The aerodynamic resistance r a, was considered as constant (ra = 250 s.nr') under greenhouse conditions (Stanghellini, 1987). It is then possible to identify A and B for each time step. As seen on figs 5 and 6, identified and calculated values of A and B changed periodically between a maximum (diurnal) and a minimum (nocturnal) value, that represent the effect of crop stomatal regulation. The A value (diurnal and nocturnal) remains constant (0.2 and 0.6 respectively) all along the period, whereas B value (diurnal and nocturnal) increases with LAI. 4.3. Nutrient absorption The weekly absorption rate N (Kg.ha-l.week'l) by the system {crop + substrate) for the various nutrients (K, Ca, Mg, NO3 and P) is plotted in figure 7. As it can be seen, the N values for Ca, Mg, and P are rather stable all along the growth period between 7 t ' 1 April and 22 n d June (week 15 to 25), but with a significant increase of NO3 and K absorption during the week 20 and 21. This increase can be related to climate conditions that were marked by an important increase of G and D during these two weeks (fig 8). We find generally, a good correlation between the NO3 and K absorption rates and the climate parameters G and D (that govern the transpiration rate): N(NC>3)= 1.245*G-4 07 (r 2 = 0.69) N(K) = 0.512*G-4.16 (r 2 = 0.54) N(NC>3) = 8.543*D+54.6 (r 2 = 0 67) N(K) = 4.095*D+16.16 (r 2 = 0.71) N(NC>3) = 0.871*G+4.6*D (r 2 = 0.80) N(K) = 0.251*G+3.014*D (r 2 = 0.75) These results lead us to examine the interdependence between climate, transpiration and absorption of the nutrients (K, Ca, Mg, and P). We observe that the ratio (N/TR) remained rather stable for all components all along the crop duration (fig 9) and analysis of data in fig. 7 showed that the uptake rates for water and nutrients were highly correlated with both radiation and saturation deficit. 5. Discussions and conclusion Transpiration rate of a soilless greenhouse tomato crop was measured from April to August 1991 by means of two methods: - a weighting lysimeter supporting 4 plants (hourly time step). - an input/output method that gives the transpiration rate for a complete row of plants (daily time step). These measurements were compared to a detailed model of transpiration including the effect of stomatal regulation. The positive accuracy between the prediction and the measurements (as long as no strong climatic stress occurs) leads us to adapt and simplify the model for irrigation control purpose. A simple linear model TR = A*Ga-t-B*D, was derived from the analytical model and tested. It was shown that A and B values oscillate between day and night according to the 140

oscillations of the stomatal resistance. Nevertheless, the low values of tomato transpiration during night time allow to consider only a single couple of A and B value for irrigation control. During the periods under study, the determination of the absorption rates (N) for various nutrients (K, Ca, Mg, NO3 and P) together with transpiration rate showed that the ratio N/TR remained rather stable for all the components with some slight fluctuations for NO3- and K +. It suggests that the uptake rates for water and nutrients are closely dependent on the same climatic parameters: radiation and air humidity. References Baille M., Laury J.C., Morel P. and Bailie A. (1990). Mesure et estimation de l'évapotranspiration sous serre des plantes ornamentales en pot. Cahier C.N.I.H. 15: 33-37. Boulard, T., Baille, A. (1993). A simple greenhouse climate control model incorporing effects of ventilation and evaporative cooling. Agric. and Forest Meteor. 65: 145-157. Boulard, T., Baille, A, Mermier, M. and Vilette, F. (1991). Mesures et modélisation des effets de la résistance stomatique foliare et de la transpiration d'un couvert de tomates de serre. Agronomie 11: 259-274. De Villèle, O. (1974). Besoins en eau des cultures sous serre, essai de conduite des arrosages en fonction de l'ensoleillement. Acta. Hort. 35: 123-129. Fuchs, M. (1990). Effect of transpiration on greenhouse cooling. International symposium on greenhouse technology. Israël 26/03-02/04/90. Inst of Agr. and Engineering. A.R.0.155-181 Jolliet, O. and Bailey B.J. (1992). The effect of climate on tomato transpiration in greenhouse. Agric. and Forest Meteor 58: 43-62. Stanghellini, C. (1987). Transpiration of greenhouse crops, an aid to climate management Ph.D. thesis. Agricultural University, Wageningen,150 p. Yang, X., Short, T.M., Fox, R.D. and Bauerle, W.L. (1990 Transpiration, leaf temperature and stomatal resistance of a greenhouse cucumber crop. Agri. and Forest Meteor 51: 197-209. 141

Annex : List of symbols A : radiative coefficient B : advective coefficient (w.m'^.mb" 1 ) Ci : concentration of nutrient in supply solution (mg.l-1) Cp : calorific capacity (joules.kg' 1. 0 «' 1 ) Cr : concentration of nutnent in drainage solution (mg.l-1) D : saturation deficit (mb) Dr : volume of water drained (mm.week' 1 ) G : global radiation (w.m" 2 ) Ga : radiation absorbed by the crop (w.m" 2 ) I : volume of water supplied (mm.week* 1 ) LAI : leaf area index (m 2 m' 2 ) N : nutrient absorption rate (Kg.ha" 1.week -1 ) r a : aerodynamic resistance (s.m' 1 ) r s : resistance to vapour transfer (s.m" 1 ) rt : total resistance to vapour transfer (s.m' 1 ) T : temperature ( C) TR : transpiration (w.m' 2 ) p : density of air (Kg.m'3) 7 : psychrometric constant : (mb. K' 1 ) A : slope of saturated water vapour pressure deficit (mb. K' 1 ) Fig 1 Schematic iilustation of the transpiration mesurement systems a) Lysimeter supporting 4 plants 1) Plant supporting system 2) Nutrient solution tank 3) Drainage tank 4) Balance 5) Rockwool substrate =3=J=r= b) Fertirrigation and drainage monitoring system for 108 plants 1) Water counter 2) PH and EC measurements in supply solution 3) Distribution 4) Crop rows 5) PH and EC in drainage solution 6) Dripping bucket rain gauge 142

Fig 2 a) Courses of mesured and calculated transpiration (7 April to 22 June 1991) 1) lysimeter measurements on 4 plants. 2) measurements by supply and drainage monitoring on one row of 108 plants 3) model (eq. 1 and 2) estimation b) Daily courses of average greenhouse climate parameters: G, T and D (7 April to 22 June 1991) 1) daily average temperature T 2) daily maximum temperature Tmax 3) daily maximum saturation deficit Dmax. Fig 3 Hourly courses of transpiration (total and advective part) estimated by the complete model (eq.1 and 2). Total tranapraoon - Ac^ecov«part 143

Fig 4 Correlation between measured (lysimeter) and complete model estimated transpiration (hourly basis, 07 to 19/04/91). 0 50 IOO ISO :OJ 250 300 TR Model (w/m2) - - A lidenofied> A model leg 1 & 2) Fig 6 Hour (from 07to19/04) Daily courses of identified (eq. 3 and 6) and calculated (eq. 1 and 2) values of the model's parameters: B and LAI evolution. 144

Fig 7 Weekly nutrient absorption for the system {substrate+plant} of various nutrient (K, Ca, Mg, NO3 and P) from 7 April to 22 June 1991. Week numcer - m Weekly courses of greenhouse climate parameters (G, D and T) from 7 April to 22 June 1991. 15 IS 17 18 19 20 21 22 23 24 25 Week number Fig 9 Weekly courses of the ratio (N/Tr) from 7 April (week 15) to 22 June (week 25) 1991. 145