Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-12-03T19:20:23.998Z Has data issue: false hasContentIssue false
  • English
  • Français

SOWING WINDOWS FOR A SPRING CROP INTRODUCED IN RICE CULTIVATION AREAS AFFECTED BY LOW TEMPERATURE AND RADIATION

Published online by Cambridge University Press:  29 January 2015

LUU NGOC QUYEN ,
FRANÇOIS AFFHOLDER ,
JENNIFER MONTAGNE ,
DAMIEN JOURDAIN ,
AUDE RIPOCHE  and
ALAIN CAPILLON
LUU NGOC QUYEN*
Affiliation:
VAAS, NOMAFSI, Food Crop Department, Phu Ho Commune, Phu Tho Town of Phu Tho Province, Viet Nam CIRAD, UMR System, IRRI, Bat. 27, Supagro, 2 place Viala, F-34060 Montpellier, France CIRAD, UPR AIDA, F-34398 Montpellier, France
FRANÇOIS AFFHOLDER
Affiliation:
CIRAD, UMR System, IRRI, Bat. 27, Supagro, 2 place Viala, F-34060 Montpellier, France CIRAD, UPR AIDA, F-34398 Montpellier, France
JENNIFER MONTAGNE
Affiliation:
CIRAD, UMR System, IRRI, Bat. 27, Supagro, 2 place Viala, F-34060 Montpellier, France
DAMIEN JOURDAIN
Affiliation:
CIRAD, UMR System, IRRI, Bat. 27, Supagro, 2 place Viala, F-34060 Montpellier, France UMR G-Eau, IRRI, 361 rue J.F. Breton, BP 5095, F-34196 Montpellier Cedex 5, France Int Rice Res Inst, DAPO Box 7777, Metro Manila, Philippines
AUDE RIPOCHE
Affiliation:
CIRAD, UPR AIDA, F-34398 Montpellier, France
ALAIN CAPILLON
Affiliation:
Supagro, UMR System, F-34060 Montpellier, France
*
§§Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

In mountainous areas of Continental South East Asia, double cropping in the irrigable valleys and terraces is often promoted as a way to increase farmers’ income while alleviating the pressure of agriculture on fragile slopes. However, cold temperature and low global radiation may constrain this strategy. Lethally cold events may occur, and increases in crop cycle length may jeopardize the correct timing of the main rice crop, taking place in summer. The model PYE (potential yield estimator) simulating the impact of temperature and radiation on the development and yield of annual crops was adapted to account for the range of temperature occurring in the area under study. It was calibrated against experimental data for the three crops that are most often considered as spring crops in the irrigable land of the northern mountains of Vietnam: rice, soybean and maize. Then a virtual experiment was designed in order to simulate various scenarios combining crop species and sowing date with climatic data accounting for variability of climate across years, location and elevation. Completed with a sensitivity analysis, it allowed to define favourable ‘sowing windows’ for non-water limited environments, based on the three following criteria: high average yield, low incidence over years of lethally cold events and low incidence over years of delays in the maturity of the spring crop. The length of this sowing window varied greatly across the scenarios tested. The widest was obtained for the case of soybean whatever the location and elevation, which makes it the less risky of the tested options. The approach followed proved effective to identify favourable and unfavourable environments in order to help better targeting the policy in support to the introduction of a spring crop in the mountains of Vietnam.

Type
Research Article
Information
Experimental Agriculture , Volume 51 , Issue 4 , October 2015 , pp. 540 - 566
Check for updates
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Affholder, F., Poyedebat, C., Corbeels, M., Scopel, E. and Tittonell, P. (2013). The yield gap of major food crops in family agriculture in the tropics: assessment and analysis through field surveys and modelling. Field Crops Research 143, 106–118.Google Scholar
Affholder, F., Tittonell, P., Corbeels, M., Roux, S., Motisi, N., Tixier, P. and Wery, J. (2012). Ad Hoc modeling in agronomy: what have we learned in the last 15 years? Agronomy Journal 104 (3): 735–748.CrossRefGoogle Scholar
Alocilja, E. C. and Ritchie, J. T. (1991). A model for the phenology of rice. In Predicting Crop Phenology, 181–189 (Ed Hodges, T.). Boca Raton, Florida: CRC Press.Google Scholar
Andaya, V. C. and Mackill, D. J. (2003). Mapping of QTLs associated with cold tolerance during the vegetative stage in rice. Journal of Experimental Botany 54 (392):2579–2585.CrossRefGoogle ScholarPubMed
Baker, F. S. (1944). Mountain Climates of the Western United States. Ecological Monographs 14 (2): 223–254.Google Scholar
Birch, C. J., Hammer, G. L. and Rickert, K. G. (1998). Temperature and photoperiod sensitivity of development in five cultivars of maize (Zea mays L.) from emergence to tassel initiation. Field Crops Research 55 (1–2):93–107.Google Scholar
Bouman, B. A. M., Kropff, M. J., Tuong, T. P., Wopereis, M. C. S., ten Berge, H. F. M. and van Laar, H. H. (2001). ORYZA2000 : modeling lowland rice. International Rice Research Institute, Los Baños, Philippines and Wageningen University and Research Centre, Wageningen, The Netherlands.Google Scholar
Bouman, B. A. M., Peng, S., Castaneda, A. R. and Visperas, R. M. (2005). Yield and water use of irrigated tropical aerobic rice, systems. Agricultural Water Management 74 (2):87–105.CrossRefGoogle Scholar
Bouman, B. A. M., Yang, X. G., Wang, H. Q., Wang, Z. M., Zhao, J. F. and Chen, B. (2006). Performance of aerobic rice varieties under irrigated conditions in North China. Field Crops Research 97 (1):53–65.CrossRefGoogle Scholar
Brisson, N., Bona, S. and Bouniols, A. (1989). A soybean crop simulation model-validation and adaptation to varieties cultivated in Southern Europe. Agronomie 9 (1):27–36.Google Scholar
Brisson, N., Gary, C., Justes, E., Roche, R., Mary, B., Ripoche, D., Zimmer, D., Sierra, J., Bertuzzi, P., Burger, P., Bussiere, F., Cabidoche, Y. M., Cellier, P., Debaeke, P., Gaudillere, J. P., Henault, C., Maraux, F., Seguin, B. and Sinoquet, H. (2003). An overview of the crop model STICS. European Journal of Agronomy 18 (3–4):309–332.CrossRefGoogle Scholar
Brisson, N., Mary, B., Ripoche, D., Jeuffroy, M. H., Ruget, F., Nicoullaud, B., Gate, P., Devienne-Barret, F., Antonioletti, R., Durr, C., Richard, G., Beaudoin, N., Recous, S., Tayot, X., Plenet, D., Cellier, P., Machet, J. M., Meynard, J. M. and Delecolle, R. (1998). STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agronomie 18 (5–6):311–346.Google Scholar
Confalonieri, R., Acutis, M., Bellocchi, G. and Donatelli, M. (2009). Multi-metric evaluation of the models WARM, CropSyst, and WOFOST for rice. Ecological Modelling 220 (11):1395–1410.Google Scholar
Dat Van, T. (1997). World rice production: main issues and technical possibilities. Cahiers Options Méditerranéennes 24 (2):57–69.Google Scholar
Dingkuhn, M. (1995). Climatic determinants of irrigated rice performance in the Sahel. 3. Characterizing environments by simulating crop phenology. Agricultural Systems 48 (4):435–456.CrossRefGoogle Scholar
Feng, D. Y. and Fu, L. Q. (1989). Main meteorological problems of rice production and protective mesures in China. International Journal of Biometeorology 33 (1):1–6.Google Scholar
Fukai, S. (1999). Phenology in rainfed lowland rice. Field Crops Research 64 (1–2):51–60.Google Scholar
Gao, L., Jin, Z., Huang, Y. and Zhang, L. (1992). Rice clock model–a computer model to simulate rice development. Agricultural and Forest Meteorology 60 (1–2):1–16.Google Scholar
Horie, T. and Sakuratani, T. (1985). Studies on crop-weather relationship model in rice. (1) relation between absorbed solar radiation by the crop and the dry matter production. Journal of Agricultural Meteorology 40 (4):331–342.Google Scholar
Hungria, M., Chueire, L. M. D., Coca, R. G. and Megias, M. (2001). Preliminary characterization of fast growing rhizobial strains isolated from soyabean nodules in Brazil. Soil Biology and Biochemistry 33 (10):1349–1361.CrossRefGoogle Scholar
Idinoba, M. E., Idinoba, P. A. and Gbadegesin, A. S. (2002). Radiation interception and its efficiency for dry matter production in three crop species in the transitional humid zone of Nigeria. Agronomie 22 (3):273–281.CrossRefGoogle Scholar
Janowiak, F., Luck, E. and Dorffling, K. (2003). Chilling tolerance of maize seedlings in the field during cold periods in spring is related to chilling-induced increase in abscisic acid level. Journal of Agronomy and Crop Science 189 (3):156–161.CrossRefGoogle Scholar
Jourdain, D., Boere, E., van den Berg, M., Dang, Q. D., Cu, T. P., Affholder, F. and Pandey, S. (2014). Water for forests to restore environmental services and alleviate poverty in Vietnam: a farm modeling approach to analyze alternative PES programs. Land Use Policy 41:423–437.Google Scholar
Keating, B. A., Carberry, P. S., Hammer, G. L., Probert, M. E. E, Robertson, M. J., Holzworth, D., Huth, N. I., Hargreaves, J. N. G., Meinke, H., Hochman, Z., McLean, G., Verburg, K., Snow, V., Dimes, J. P., Silburn, M., Wang, E., Brown, S., Bristow, K. L., Asseng, S., Chapman, S. C., McCown, R. L., Freebairn, D. M. and Smith, C. J. (2003). An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy 18:267–288.Google Scholar
Kouressy, M., Dingkuhn, M., Vaksmann, M. and Heinemann, A. B. (2008). Adaptation to diverse semi-arid environments of sorghum genotypes having different plant type and sensitivity to photoperiod. Agricultural and Forest Meteorology 148 (3):357–371.CrossRefGoogle Scholar
Launay, M., Brisson, N., Satger, S., Hauggaard-Nielsen, H., Corre-Hellou, G., Kasynova, E., Ruske, R., Jensen, E. S. and Gooding, M. J. (2009) Exploring options for managing strategies for pea-barley intercropping using a modeling approach. European Journal of Agronomy 31 (2):85–98.Google Scholar
Le Quoc Doanh, L. N. Q. 2007. Nghiên cứu áp dụng các biện pháp kỹ thuật nâng cao hiệu quả sử dụng đất ruộng một vụ vùng miền núi phía bắc Việt Nam. Study on application of technical approaches to increasing efficiency of use of rice fields cropped once a year in the mountainous region of northern Viet Nam. Science and Technology Journal of Agriculture and Rural Development 7:79–82.Google Scholar
Linquist, B., Trosch, K., Pandey, S., Phouynyavong, K. and Guenat, D. (2007). Montane paddy rice: development and effects on food security and livelihood activities of highland lao farmers. Mountain Research and Development 27 (1):40–47.CrossRefGoogle Scholar
Lobell, D. B., Cassman, K. G. and Field, C. B. (2009). Crop yield gaps: Their importance, magnitudes, and causes. Annual Review of Environment and Resources 34:179–204.Google Scholar
Lou, Q. J., Chen, L., Sun, Z. X., Xing, Y. Z., Li, J., Xu, X. Y., Mei, H. W. and Luo, L. J. (2007). A major QTL associated with cold tolerance at seedling stage in rice (Oryza sativa L.). Euphytica 158 (1–2):87–94.CrossRefGoogle Scholar
Maton, L., Bergez, J.-E. and Leenhardt, D. (2007) Modelling the days which are agronomically suitable for sowing maize. European Journal of Agronomy 27:123–129.CrossRefGoogle Scholar
Rezaul, M. (1997). Impacts of air temperature variations on the boro rice phenology in Bangladesh: implications for irrigation requirements. Agricultural and Forest Meteorology 84 (3–4):233–247.Google Scholar
Schleppi, P., Soldati, A. and Keller, E. R. (1990). Photosynthate partitioning in flowering soybeans subjected to a cold stress. Journal of Plant Physiology 136 (5):556–563.Google Scholar
Setiyono, T. D., Weiss, A., Specht, J., Bastidas, A. M., Cassman, K. G. and Dobermann, A. (2007). Understanding and modeling the effect of temperature and daylength on soybean phenology under high-yield conditions. Field Crops Research 100 (2–3):257–271.CrossRefGoogle Scholar
Shimono, H., Hasegawa, T. and Iwama, K. (2002). Response of growth and grain yield in paddy rice to cool water at different growth stages. Field Crops Research 73 (2–3):67–79.Google Scholar
Shrestha, R. R., Dibike, Y. B. and Prowse, T. D. (2011). Modeling climate change impacts on hydrology and nutrient loading in the upper assiniboine catchment. Journal of the American Water Resources Association 48:74–89.Google Scholar
Sinclair, T. R. and Seligman, N. G. (1996). Crop modeling: from infancy to maturity. Agronomy Journal 88 (5):698–704.Google Scholar
Singer, J. W., Meek, D. W., Sauer, T. J., Prueger, J. H. and Hatfield, J. L. (2010). Variability of light interception and radiation use efficiency in maize and soybean. Field Crops Research 121 (1):147–152.Google Scholar
Sipaseuth, Basnayake, J., Fukai, S., Farrell, T. C., Senthonghae, M., Sengkeo, Phamixay, S., Linquist, B. and Chanphengsay, M. (2007). Opportunities to increasing dry season rice productivity in low temperature affected areas. Field Crops Research 102 (2):87–97.Google Scholar
Wang, Z., Reddy, V. R. and Quebedeaux, B. (1997). Growth and photosynthetic responses of soybean to short-term cold temperature. Environmental and Experimental Botany 37 (1):13–24.CrossRefGoogle Scholar