Title: Simulating the impacts of climate change on cotton production in India
Journal Name: Climate Change
K.B.Hebbar1*, M.V.Venugopalan1, A.H.Prakash1, P.K.Aggarwal2
1Central Institute for Cotton Research, P.B.No.2, Shankar Nagar, Nagpur, 440 010, Maharashtra, India
* Present address & Corresponding author: Central Plantation Crops Research Institute, Kasaragod Kerala, India
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Telephone: 914994 232894; Fax: 914994 232322
M.V.Venugopalan: Email:
A.H.Prakash: Email:
2Indian Agricultural Research Institute, New Delhi, 110 012, India.
Present address: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), International Water Management Institute, New Delhi Office; New Delhi-110012, India
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2.1.1 Model description
The Infocrop model is written in FORTRAN SIMULATION TRANSLATOR (FST) language (Van Kraalingen 1995). The time step of the model is one day. The general structure and details of the Infocrop series of models are described by Aggarwal et al. (2004; 2006). Cotton is also a part of a wider group of field crops simulated by this generic model, and the reader is referred to (Hebbar et al. 2008) for a fuller description of the approach. The Infocrop cotton module simulates crop development, growth, yield and nitrogen accumulation in response to temperature, photoperiod, soil water and N supply. The model was calibrated and validated to simulate the growth and production of cotton using field experiment data collected during 2000-2005 from a network project ‘ Technology Mission on Cotton’ funded by Government of India (Hebbar et al. 2008; Venugopalan et al.2007). Here we present some of the parameters and relationships needed to build the functions in the infocrop cotton model.
2.1.2 Phenology
The Infocrop cotton simulates the complete life cycle of cotton in three developmental phases viz. sowing to emergence, emergence to flowering and flowering to maturity. The duration of these growth stages is found to be dependent on genotype and environment. Broadly the varieties and hybrids are classified according to their duration for maturity as short (125 to 145 days), medium (145 to 165) and long (170 to 190 days) (Kairon and Singh 1996). The corresponding duration required for flowering is 55 to 60, 60 to 65 and 65 to 73 days respectively. Like in other crops, in cotton too, the development rate is mainly driven by temperature (Oosterhuis, 1992). The amount of heat required for each stage is measured in heat units using the daily average and a base temperature of 15oC (Reddy et al. 1997). Emergence has an optimum temperature requirement of 28-30o C.
The vegetative stage, i.e., from emergence to anthesis has been divided into early vegetative stage i.e. from emergence to the appearance of 1st square (35 to 50 days) and juvenile phase i.e. from squaring to flowering (20 to 22 days). Most of the commercially grown cotton cultivars are not photosensitive but highly thermo sensitive (Bhat 1996). Cotton has an optimum temperature of 28oC for flowering. At low temperature flowering is delayed and below 15oC there is complete cessation of flowering. At this stage, the development rate is linearly related to the daily mean temperature above base temperature. Above optimum the rate decreases until the maximum temperature is reached (Reddy et al. 1997). If temperature goes below the base or above the maximum the rate of development becomes zero. Water stress in cotton increase leaf temperatures as high as 3.4°C above ambient (Pallas et al. 1967). This accelerates flowering and hence, depending upon the severity of stress the rate of development is controlled by increasing canopy temperature (Turner et al. 1986).
The duration of last phase from flowering to maturity in cotton has been divided into 2 stages viz. flowering to cutout and cutout to maturity. Since, cotton is an indeterminate crop there is continuous production of flowers. The number of bolls retained and developed is solely a function of variety specific thermal time which is modified by water and nitrogen stress. The developing bolls utilize all the carbohydrates, leading to cessation of growth known as cutout (Guinn 1984; 1985). Cut out dictates the end of the growing season (that is the end of production of new blooms and bolls that will contribute to harvest) which is relatively early in Bt cotton hybrids compared to Non-Bt hybrids due to faster utilization of assimilates as a result of more synchronized boll development (Hebbar et al 2007b). Bt cotton hybrids mature 10 to 20 days early compared to non-Bt hybrids (Singh et al. 2006).
2.1.3 Leaf area growth
Leaf area development is described using functions for the appearance, expansion and senescence of leaves. Leaf appearance can occur from emergence until maturity depending upon the supply of assimilates available for growth. Leaf lamina area (LAI) changes proportionally with leaf area growth rate; its value is obtained by multiplying the increment in leaf weight by the specific leaf area (SLA). Under field condition SLA ranges from 0.0020 to 0.0022 dm2 mg-1 (Hebbar et al. 2008). SLA is high at initial stages and gradually decreases with the crop age. This is simulated by adjusting SLA as a function of the development stage. In cotton, bracts and capsules contribute 15 to 20% of green leaf area for photosynthetic area (Bhatt 1996; Wullschleger and Oosterhuis 1991). In the model, non- lamina area is calculated as a crop specific function of the maximum leaf lamina area index and it is assumed that the photosynthetic character of their non- lamina green area are same as those of leaves.
Simulation of senescence is based on several empirical constants relating to shading, ageing, nitrogen mobilization, temperature, water stress and death due to pests and diseases. Shading in dense stands (LAI > 4.0) accelerates senescence linearly to a maximum of 3% per day of leaf area index. Higher (>36oC) or lower (< 15oC) temperatures and water stress accelerate rate of senescence depending upon its severity. Net effective leaf area for photosynthesis and transpiration (EFFLAI) is thus the sum of leaf area and non-lamina area after subtracting all losses due to senescence.
2.1.4 Dry matter production
In cotton at emergence nearly 35 to 40 % of seed weight is partitioned to leaf and rest to roots. For simulating further increase in dry matter, the crop is treated as an intact unit. The dry matter production in Infocrop-cotton is calculated by the approach of the radiation use efficiency (RUE). Pre-determined values of the RUE are input in the model as a function of crop/cultivar (RUEMAX). RUE in cotton ranges between 1.5 to 1.7 g MJ-1 under favorable condition and 1.2 to 1.4 g MJ-1 under unfavorable condition (Sadras 1996). It is further modified by the development stage (RCFDS), abiotic (RUEABI) and biotic (RUEBIO) factors. RUE peaks at early boll development and subsequently it declines (Milroy and Bange 2003). Radiation interception by the crop is calculated as a function of total LAI, incident solar radiation, radiation captured by the pests and weeds and a crop / cultivar specific extinction coefficient (KDF). Under favorable growing condition KDF has values from 0.8 to 1.14 while, under unfavorable condition it ranges from 0.6 to 0.9 (Sadras 1996). The growth rate of the crop (GCROP) is then calculated as a function of RUE and radiation intercepted by the crop.
RUE = RUEMAX*AFGEN(RCFDS,DS)*RUEABI*RUEBIO
RUEABI = AFGEN(RCFTP,TPAD)*AFGEN(RCFLN,NSTRES)*...
AFGEN(RCFCO2,CO2)*LIMIT(0.,1.,WSTRES)
RUEBIO=AMAX1(0.,1.-AMAX1(BLIGHT,RUST,… AFGEN(SEVRPT,MILDEW), AFGEN(EARCUT,DAS)*.3/100.))
GTOTAL = RUE*PARINT*10.
Photosynthesis of cotton hybrids ranges from 28 to 34 umole m-2s-1 under field condition (Hebbar et al 2007a). Bt cotton hybrids showed higher photosynthesis compared to non-Bt hybrids at boll development stage (Hebbar et al. 2007a). The preferred temperature for optimum photosynthesis is 25oC (Downtown and Slatyer 1972). The effect of temperature mimics a crop specific decrease in photosynthesis RCFTP due to adverse mean daytime temperature (TPAD). Function RCFLN, dependent on N levels has an exponential relation with a maximum of 32 umol CO2 m-2 s-1 (Milroy and Bange 2003), further reduces RUE. Since, cotton is a C3 plant, more C is fixed in high [CO2] grown plants at all levels of water and nutrient deficient conditions and across a wide range of temperatures (Reddy et al. 1997). This is simulated by a crop specific input (RCFCO2) that increases RUE as a function of ambient [CO2].
2.1.5 Dry mass partitioning among plant organs
The net dry matter available each day for crop growth is partitioned into roots, leaves, stems and seed cotton as a function of development stage is simulated in the model through empirical interpolation functions developed from field experiments (Hebbar unpublished data). Allocation is first made to roots (0.35), which are increased in case the crop experiences water, or nitrogen stress. The remaining dry matter is allocated to the above ground shoot from which a fraction is allocated to leaves and stems. Approximately 70% biomass is accumulated in leaves at early seedling stage and later it gradually decreased. At squaring, almost equal amount of biomass was partitioned between leaves and stem. After flowering biomass allocation increases towards bolls and nearing cutout negligible amount was partitioned to leaves and stem.
2.1.6 Source-sink balance
The net growth during boll development period and a crop specific factor relating bolls per growth are utilized to calculate increase in the number of bolls every day. In India, under well managed condition cotton could yield as high as 5 ton ha-1 with a maximum boll load of 1 to 1.1 million bolls having a potential boll weight of 5 g (Data from All India Cotton Improvement Projects). Cotton crops produce many more floral buds than mature bolls (Heitholt 1995); abscission of fruiting forms (squares and bolls) is a major determinant of the number of bolls harvested. Apart from the entomological factors the environmental conditions, which influence the fruiting in cotton are temperature, light, water and nutrients (Ehlig and LeMert 1973; Patterson et al. 1978). Temperature has a curvilinear response to potential growth of developing squares. Growth rate increased to 220 C but did not grow more rapidly at higher temperatures. Boll growth is much more rapid, had a distinct optimum temperature at about 280C and declined rapidly at higher temperature (Reddy et al. 1997). In the model, a predetermined maximum boll number limits the final boll number.
Bolls retained in the plant are filled up with a rate depending upon temperature dependent potential filling rate and the level of dry matter available for growth. The boll growth is terminated when their weight reaches potential weight, no dry matter is available or when the thermal time dependent stage has reached. In Bt hybrids, the boll growth is terminated early due to greater competition for assimilates as a result of more synchronized boll development (Hebbar et al. 2007b).
2.1.7 Abiotic stresses
Water stress is determined as the ratio of actual water uptake (ATRANS) and potential transpiration. Though, cottons are xerophytes, water stress at flowering and boll development significantly reduced the yield (Potkile et al. 1988). Similarly, drastic reduction in leaf area expansion and growth was observed when field grown cotton was stressed at 75, 95 and 115 days after emergence (Kumar et al. 1987). Photosynthetic rates of cotton plants were reduced about 50% as the midday leaf water potential reduced from -1.4 MPa to -3.5 MPa (Reddy et al. 1998). Similarly, Lower productivity under N deficit was caused by reduced photosynthesis, leaf area and radiation use efficiency (Milroy and Bange 2003). Leaf growth declined to nearly zero when the leaf N was 1.5 g m-2, the minimum N concentration in cotton leaves.
Soil is considered waterlogged on a day in case available water fraction in the surface layer exceeds 20% of the field capacity or if there is free-standing water on soil surface. Cotton response to waterlogging depends on the cultivar, growth stages and the prevailing weather conditions. It suddenly wilts if waterlogged under bright sunlight at flowering and boll development stages (Hebbar 2004; 2010), whereas under cloudy weather leaves starts senescing and thus leaf area and photosynthesis declines (Hebbar 2003a). Photosynthesis decreased by 30% in waterlogged plants relative to non-waterlogged plants (Tongbai et al, 2001).
2.1.8 Soil water and nitrogen balance
The Infocrop cotton model simulates water and nitrogen balance in three layers. If rainfall exceeds the infiltration rate and storage capacity of soil, runoff occurs. Above field capacity, any additional water entering the soil surface percolates beyond the lower boundary of the rooting zone. Waterlogging may occur if the rate of precipitation or irrigation exceeds the hydraulic conductivity of any soil layer.
2.1.9 Model input requirements
Environmental inputs to run Infocrop are daily solar radiation, maximum and minimum air temperature, rainfall, vapor pressure and wind speed. Additional necessary inputs are sowing dates, seed rate, and latitude of the site, N fertility and the physical and hydraulic properties of the soil. Crop development and growth processes required are phenology, dry matter development and its partitioning, leaf area growth, source-sink balance, nitrogen uptake and distribution, transpiration, abiotic stresses, biotic stresses etc.
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