SciELO - Scientific Electronic Library Online

 
vol.21 número1Determinación de índices reales de consumo de combustible en el laboreo de un fluvisol en la Empresa de Cultivos Varios “Paquito Rosales Benítez”Contenido de elementos metálicos en suelos característicos del municipio San José de las Lajas índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Artigo

Indicadores

  • Não possue artigos citadosCitado por SciELO

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Revista Ciencias Técnicas Agropecuarias

versão On-line ISSN 2071-0054

Rev Cie Téc Agr vol.21 no.1 San José de las Lajas jan.-mar. 2012

 


ARTÍCULO ORIGINAL

 

Estimation of the papaya crop coefficients for improving irrigation water management in south of Havana

 

La estimación de los coeficientes de la cosecha de papaya por mejorar la dirección de agua de irrigación en el sur de La Habana

 

 

M.Sc. Yoima Chaterlán,I  M.Sc. Geisy Herández,I M.Sc. Paula Paredes,II Dr. C. Roberto Martínez,I Dr. C. Teresa López,I Dr. Luis Santos Pereira,II

I Instituto de Investigaciones de Ingeniería Agrícola (IAgric), La Habana, Cuba.
II CEER-Biosystems Engineering, Institute of Agronomy, Technical Univ. of Lisbon, Portugal.

 

 


ABSTRACT

The papaya (Carica papaya L.) is a main irrigated fruit crop in Cuba and in the tropical and subtropical regions. For environmental and irrigation management purposes, it is important to accurately estimate its crop evapotranspiration and irrigation requirements. The objective of the present study is to determine the crop coefficients (K c) and the depletion fraction for no stress (p) of the papaya, variety Maradol, as cultivated in southern Havana. Experiments took place during the period March–November, 1997 in an experimental area where soils are compacted red iron soils. The ISAREG irrigation simulation model was applied to those observed data. The calibration of the model consisted in searching the crop coefficients and the depletion fraction for no stress that minimize the differences between observed and simulated available soil water. Several statistical indicators were used to assess the goodness of fit. Results show a good adjustment between observations and model predictions, with the regression coefficient forced to the origin close to 1 (b=1,01) and a high R2=0,86. The root mean square error (RMSE) and the average absolute error (AAE ) are small, respectively RMSE=6,5 mm and AAE=4,9 mm. After calibration, the model was used to assess the current irrigation scheduling; results show that irrigation dates were anticipated relative to the required and irrigation depths were excessive, thus a large percolation occurred. The ISAREG model will be further used to generate and evaluate alternative irrigation schedules aimed at improved water productivity.

Key words: soil water balance, modelling, irrigation management.


RESUMEN

La papaya (la papaya de Carica L.) es uno de los cultivos principales irridados en Cuba y en las regiones tropicales y subtropicales. Para el medio ambiente y la irrigación, es importante estimar la evapotranspiración de la cosecha y los requisitos de la irrigación con precisión. El objetivo del presente estudio fue determinar los coeficientes de la cosecha (Kc) y el vaciamiento fraccional para ninguna tensión (r) de la papaya, variedad Maradol, cultivada al sur de La Habana. Los experimentos tuvieron lugar durante el periodo marzo-noviembre de 1997 en una área experimental dónde se encuentran suelos Ferralítico rojo compactado. El modelo de simulación de irrigación ISAREG se aplicó a esos datos observados. La calibración del modelo consistió en la investigación de los coeficientes de la cosecha y el vaciamiento fraccional para ninguna tensión que minimiza las diferencias observadas y el agua simulada de la tierra disponible. Se usaron varios indicadores estadísticos para evaluar la bondad de ataque. Los resultados muestran un buen ajuste entre las observaciones y predicciones del modelo, con el coeficiente de la regresión forzado al origen cerca de 1 (el b=1,01) y un R2=0,86 alto. el error de la raíz cuadrada (RMSE) y el error medio absoluto (AAE) son pequeños respectivamente RMSE=6,5 mm AAE=4,9 mm. Después de la calibración, el modelo fue acostumbrado a evaluar la planificación de la irrigación actual; muestra de los resultados que se anticiparon las fechas de la irrigación relativo a los requerimos y profundidades de la irrigación sea excesiva, así una coladura grande ocurrió. El modelo de ISAREG será acostumbrado a generar más allá y para evaluar horarios de la irrigación alternativos apuntados a la productividad de agua mejorada.

Palabras clave: balance de agua-tierra, modelado, dirección de la irrigación.


 

 

INTRODUCTION

The papaya (Carica papaya L.) is one of the main fruit trees in the tropical and sub-tropical countries. This relates to the high nutritional value of the fruit, its excellent flavor, and utility for food industry (Alonso et al., 2008). Environmental factors such as temperature (Campostrini and Glenn, 2007), wind speed, water stress (Marler and Clemente, 2006) and soils chemical and physical characteristics affect papaya productivity and physiology (Campostrini and Glenn, 2007).

Papaya irrigation management relates both with excess and deficit soil moisture. A water deficit restricts the plant growth and favors the production of male flowers (Terra de Almeida et al., 2003; Niklas and Marler, 2007; dos Santos et al., 2008), reducing the production of fruits (Aiyelaagbe et al., 1986; Masri et al., 1990; Kruger and Mostert, 1999). Studies have shown that the crop stages more sensitive to water stress are the mid vegetative stage, flowering and fruit enlargement (Aiyelaagbe et al., 1986). Excess irrigation affects the absorption of nutrients,favours their lixiviation, decreases oxygen availability in the root zone, and increases plant propensity to diseases (Campostrini and Yamanishi, 2001; Campostrini and Glenn, 2007). Several studies indicate that papaya should be cropped in soils with good structure and internal drainage, thus avoiding waterlogging that may cause severe damages to the plant, even its death (dos Santos et al., 2008). Hence, good irrigation management practices are needed when papaya has to attain high levels of production. However, there are few publications dealing with water requirements of papaya.

Papaya is a main crop fruit in Cuba, with approximately 5000 ha harvested (Alonso et al., 2008). The establishment of papaya in the South of Havana is being promoted because favorable climatic and soil conditions exist there. It is therefore important to develop appropriate irrigation schedules to improve papaya irrigation management and water productivity.

Mathematical models for simulating the soil water balance are useful tools for irrigation management (Pereira et al., 2003) but require proper calibration before being used for different crops and environments. This is the case of the ISAREG irrigation scheduling simulation model, which performs the soil water balance at field level and simulates alternative irrigation schedules (Teixeira and Pereira, 1992; Pereira et al., 2003) including assessing the impacts of those irrigation schedules on crop yields. This model has been used world-wide for a variety of crops and environments (e.g., Liu et al., 1998, 2006; Popova et al., 2006; Cholpankulov et al., 2008), including for Cuban conditions (Chaterlán et al., 2008, 2009).

The objective of this study is to determine the crop coefficients (Kc), and the depletion fraction for no stress (p) for papaya, which are not available in literature. Calibrating the model for its further use in irrigation management in Cuba is another objective of the study.

 

METHODS

Experimental site characterization

Field data were collected at the IIRD Experimental Station, located in the municipality of Alquizar; province of La Habana, Cuba (latitude 22º 46' N; Longitude 82º 37' W; altitude 6 m) during the period March to November of 1997. A climatic characterization of the experimental site for that year (1997) is presented in Figure 1. The reference evapotranspiration (ETo) was computed using the FAO-PM method (Allen et al., 1998). According to the methodology locally developed by Pacheco et al. (1995), 1997 is considered a wet year, with annual precipitation of 2 118 mm, ranging 34 to 421 mm month-1 . For this year, precipitation largely exceeded ETo except for the dry season.

Soils are red iron compacted soils, Rhodic Ferralsol according to the classification of FAO/UNESCO (Institute of soil, 1996a, b), also called clayey (Cid, 1995). Main characteristics of these soils are presented in Table 1. The total available soil water (TAW) averages 119 mm when the rooting depth is 0,70 m. Observations of soil water potential were performed with tensiometers at 0,20, 0,40 and 0,60 m with 3 measurements at each depth (Hernández et al., 2003). Soil water content data were obtained through the Van Genuchten model (López, 1996).

 

 

Field experiments were carried out with the papaya tree (Carica papaya L.) variety Maradol, with a plant density of 1 851 plants ha-1; Experiments were performed in the period 20 March to November 6, 1997. The dates for the papaya crop growth stages are given in Table 2.

 

 

Micro-irrigation was used. Irrigation uniformity tests were carried out (Pizarro, 1990); the uniformity coefficient was UC = 90% and the application efficiency was 85%. Table 3 shows the irrigation schedule used in the experiments; the total irrigation applied was 157 mm, with irrigation depths ranging 6,10–28,14 mm.

qFC and qWP represent the soil water content at field capacity and wilting point

 

The ISAREG model

The ISAREG model (Pereira et al., 2003) was selected to simulate and assess alternative irrigation schedules for papaya after proper calibration. Experimental data collected at the Irrigation Station of Alquízar were used to calibrate the model. The procedure applied is described in former applications to horticultural crops in the same location (Chaterlan et al., 2008, 2009). The actual crop evapotranspiration (ETa) is lower than ETc when the soil water depletion exceeds the depletion fraction for no stress (p). ETa is estimated through the soil water balance as a function of the available soil water in the root zone as described by Teixeira and Pereira (1992). Depletion is limited to the management allowed depletion (MAD). When water stress is not admitted, then MAD p is adopted; when deficit irrigation is applied then MAD p .

The model computes the water balance for a multilayered soil and is able to consider the impacts of salinity (Pereira et al., 2007) and to estimate the groundwater contribution (GC) through a parametric function (Liu et al., 2006). The impact of the water stress on crop yields is evaluated with the Stewart model (Stewart et al., 1977).

 

Goodness of ISAREG model simulations

In order to assess the goodness of model predictions, qualitative and statistical strategies were used. The qualitative strategy consisted of representing graphically comparisons between soil water content values observed in the field and those simulated by the model. This strategy provides a good perception of the trends and/or biases in modeling and when they occur. The second assessment strategy used linear regression forced through the origin between observed and predicted soil water content data. When the regression coefficient (b) is close to 1 then the covariance is close to the variance of the observed values which means that the predicted and observed values are statistically close; if the determination coefficient (R2) is also close to 1,0, then most of the total variance of the observed values is explained by the model. Additionally, two indicators of residual estimation errors were used. The selected indicators are based upon former applications (Liu et al., 1998; Cholpankulov et al., 2008; Chaterlan et al., 2009).

The indicators are defined bellow:

1) the Regression and determination coefficients relating observed and simulated data, b and R2 :

 

 

 

 

2) the root mean square error, RMSE, which characterizes the variance of the estimation errors:

 

 

3) the average absolute error, AAE, which expresses the size of estimation errors in alternative to RMSE , is

where Oi and Pi (i = 1, 2, …, n) are the pairs of observed and model predicted values of a given variable, and Ō and Ρ are the respective mean values:

 

RESULTS AND DISCUSSION

The calibration procedure consisted on adjusting the crop parameters Kc and p considering the range of values they can assume, in order to minimize the difference between observed and simulated available soil water. The calibrated values are presented in Table 4. The results from comparing the simulated and the observed available soil water (mm) are presented in Figure 2. The soil water in excess is also represented in Figure 2 between field capacity (FC) and soil saturation (dashed line above TAW); it corresponds to drainable water due to rainfall or to excess irrigation. To note that 3 observations were performed after irrigation and precipitation occurred and therefore they lay above FC. Results show that the field observed values cover a large range of soil water content values and that the model simulates well.

  The computed goodness of fitting indicators are as follows: b=1,01, thus indicating that predicted values are close to the observed ones;R2=0,86, hence expressing that most of the variance is explained by the model; and the estimation of errors RMSE=6.5 mm and AAE=4,9 mm, representing less than 5% of TAW, thus indicating that estimation errors are small and that there is a good agreement between simulated and observed available soil water. Summarizing, results indicate that the model performs well the simulation of the soil water balance of the micro-irrigated papaya.

The irrigation schedule used in the calibration experiment was evaluated. Results (Table 5) show that deep percolation attained very high values (40% of the total used water, i.e., the sum of irrigation and precipitation). Irrigation depths were high (up to 28 mm), also favoring deep percolation and poor use of precipitation. Thus, the current irrigation schedule is not appropriate to cope with water scarcity conditions. A more efficient use of the irrigation water is required. This implies that irrigation dates should be better adjusted and irrigation depths controlled to decrease deep percolation.

An improved irrigation schedule using MAD=p with a fixed irrigation depth of 8 mm was also simulated. Results are presented in Table 5 showing that a decrease in season irrigation may be adopted without promoting any stress but decreasing deep percolation.

 

CONCLUSIONS

The ISAREG model was successfully calibrated using past observation data of micro-irrigated papaya, including the available soil water. Results show that the regression coefficient relating simulated and observed data was close to 1.0 and a high determination coefficient (0,86) was obtained. The estimation errors RMSE, AAE are small respectively 6,5 and 4,9 mm, representing less than 5% of soil TAW. Therefore, it can be concluded that the study produced good estimates of the crop coefficient and depletion fraction for no stress. Furthermore, the analysis of the current irrigation schedule showed high non-beneficial water use as deep percolation, and an inadequate use of the precipitation. Further developments may be attained when using the model to design improved irrigation strategies aiming higher water productivity and saving.

 

REFERENCES

  1. AIYELAAGBE, I.O.O., FAWUSI, M.O.A. BABALOLA, O.: Growth development, yield of pawpaw (Carica persica L.) Homestead selection' in response to soil moisture stress, Plant and Soil, 93: 427-435, 1986.

  2. ALLEN, R.G., PEREIRA, L.S., RAES, D., SMITH, M.: Crop Evapotranspiration, 300pp., Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56, FAO, Rome, Italy, 1998.

  3. ALONSO, M., TOMET, Y., RAMOS, R., FARRÉS, E., CASTRO, J. & RODRÍGUEZ, M.C.: Evaluación de tres cultivares de papaya del grupo solo basada en caracteres de crecimiento y productividad. Cultivos Tropicales, 29(2): 59-64, 2008.

  4. CAMPOSTRINI, E. & YAMANISHI O.K.: Estimation of papaya leaf area using the central vein length, Scientia Agricola, 58(1):39-42, 2001.

  5. CAMPOSTRINI, E. & GLENN, D.M.: Ecophysiology of papaya: a review, Braz. J. Plant Physiol., 19(4):413-424, 2007.

  6. CHATERLÁN, Y., DUARTE, C., LEÓN, M., PEREIRA, L.S., TEODORO, P.R. GARCIA, R.R.: Coeficientes de cultivo de la cebolla y su determinación con el modelo ISAREG, pp. 23-25 + CD-ROM paper 1.4. In: E. Ruz and L.S. Pereira (eds.) Modernización de Riegos y Uso de Tecnologías de Información. CYTED, PROCISUR/IICA, Montevideo, 2008 .

  7. CHATERLÁN, Y., LEÓN, M., DUARTE, C., LÓPEZ, T., PAREDES, P. & PEREIRA, L.S.: Determination of crop coefficients for Horticultural crops in Cuba through field experiments and water balance simulation. In: VI International Symposium on Irrigation of Horticultural Crops . November 2-6, Villa del Mar, Chile, 2009.

  8. ?HOLPANKULOV, E.D., INCHENKOVA, O.P., PAREDES, P., PEREIRA, L.S.: Cotton irrigation scheduling in Central Asia: Model calibration and validation with consideration of groundwater contribution, Irrig and Drain , 57: 516-532, 2008.

  9. CID, G.: Introducción de métodos y metodologías para la caracterización de las propiedades hidrofísicas, así como las variaciones espacio temporales, 45pp., Informe del contrato 004-17 Instituto Investigaciones Riego Drenaje-Ministerio Tecnología Ciencia Medio Ambiente, La Habana, 1995.

  10. DOS SANTOS, F.S.S., VIANA, T.V.A., DE AZEVEDO, B.M., OLIVEIRA, C.W. & SOUSA, A.E.C.: “ Efeito de diferentes laminas de irrigação na cultura do mamão”, Eng. Agric Jaboticabal, 28(4): 673-680, 2008.

  11. HERNÁNDEZ, G., MARTÍNEZ R., PUIG O., LÓPEZ T. & SOTOMAYOR G.: “Elementos agronómicos para el riego localizado en el cultivo del papayo” Revista Ciencias Técnicas Agropecuarias, 12(2): 55-60, 2003.

  12. KRUGER, J.A., MOSTERT, P.G.: Irrigation, pp. 50-59, In: Villiers, E.A. (eds) The cultivation of papaya. ARC, LNR , South Africa, 1999.

  13. LIU, Y., TEIXEIRA, J.L., ZHANG, H.J., PEREIRA, L.S.: “Model validation and crop coefficients for irrigation scheduling in the North China Plain, Agric Water Manage, 36: 233–246, 1998.

  14. LIU, Y., PEREIRA, L.S. & FERNANDO, R.M.: Fluxes through the bottom boundary of the root zone in silty soils: parametric approaches to estimate groundwater contribution and percolation, Agric Water Manage, 84: 27-40, 2006.

  15. LÓPEZ, T.: Dinámica del agua en un suelo ferralítico rojo compactado del sur de la provincia La Habana . Tesis (en opción al título de Máster en Ciencias Agrícolas, Especialidad en Riego y Drenaje ), Universidad Agraria de La Habana ( UNAH)-Instituto de Investigaciones de Riego y Drenaja (IIRD), La Habana, 1996.

  16. MARLER, T.E. & CLEMENTE, H.S.: Papaya seedling growth response to wind and water deficit is additive, HortScience, 41(1): 96-98, 2006.

  17. MASRI, M., RAZK, A., GHAZALLI, M.Z.: Response of papaya (Carica papaya L.) to limited soil moisture at reproductive stage, Mardi Research Journal, 18: 191-196, 1990.

  18. NIKLAS, K.J., MARLER, T.E.: Carica papaya (caricaceae): a case study into the effects of domestication on plant vegetative growth and reproduction”, Am J Botany , 94(6): 999-1002, 2007.

  19. PACHECO, J., ALONSO, N., PUJOL, P., CAMEJO, E.: Riego y Drenaje , 414pp., Editorial Pueblo y Educación. La Habana, Cuba, 1995.

  20. PEREIRA, L.S., TEODORO, P.R., RODRIGUES, P.N., TEIXEIRA, J.L.: Irrigation scheduling simulation: the model ISAREG. pp. 161-180, In: G. Rossi, A. Cancelliere, L.S. Pereira, T. Oweis, M. Shatanawi and A. Zairi (eds.) Tools for Drought Mitigation in Mediterranean Regions, Kluwer, Dordrecht, 2003.

  21. PEREIRA, L.S., J.M. GONÇALVES, B. DONG, Z. MAO & S.X. FANG.: Assessing basin irrigation and scheduling strategies for saving irrigation water and controlling salinity in the Upper Yellow River Basin, China, Agric. Water Manage, 93(3), 109–122, 2007.

  22. POPOVA, Z., ENEVA S., PEREIRA, L.S.: Model validation, crop coefficients and yield response factors for maize irrigation scheduling based on long-term experiments, Biosystems Eng., 95(1): 139–149, 2006.

  23. STEWART, J.L., HANKS, R.J., DANIELSON, R.E., JACKSON, E.B., PRUITT, W.O., FRANKLIN, W.T., RILEY, J.P., & HAGAN, R.M.: Optimizing crop production through control of water and salinity levels in the soil, Utah Water Res. Lab. Rep. PRWG151-1, Utah St. Univ., Logan, USA, 1977.

  24. TEIXEIRA, J.L. & PEREIRA, L.S.: ISAREG, an irrigation scheduling model, ICID Bulletin 41: 29-48. 1992.

  25. TERRA DE ALMEIDA, F., SALES MARINHO, C., DE SOUZA, E.F. & GRIPPA, S.: Expressão sexual do mamoeiro sob diferentes lâminas de irrigação na região norte fluminense, Rev. Bras. Frutic . 25(3): 383-385, 2003.

 

 

Recibido:17 de septiembre de 2010.
Aprobado:10 de diciembre de 2010.

 

 

Yoima Chaterlán. Researcher, Instituto de Investigaciones de Ingeniería Agrícola, La Habana, Cuba, Correo electrónico:yoima@iagric.cu  & ychaterlan@yahoo.es

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License