Effect of Temperatures on Plant Growth

Chapter 5

IMPLEMENTATION

The plant growth module computes the crop growth and development based on daily values of maximum and minimum temperatures, radiation and daily value of soil stress factors. The values are added together to give an estimate of the amount of seasonal growth your plants have achieved. Plant growth prediction model depends on the plant parameters like,

• Temperature
• Relative humidity
• Rainfall
• Solar radiation.

5.1 Effect of Temperature:

Temperature factors that figure into plant growth potentials include the following:

• Maximum daily temperature
• Minimum daily temperature
• Difference between day and night temperature
• Average daytime temperature
• Average nighttime temperature

Along with these there are other considerations such as:

5.1.1 Microclimates

The microclimate of a garden plays a primary role in actual garden temperature. In mountain communities, changes in elevation, air drainage, exposure and thermal heat mass (surrounding rocks) will make gardens significantly warmer or cooler than the temperatures recorded for the are.

In mountain communities, it is important to know where the local weather station is located so gardeners can factor in the difference in their specific locations to forecast temperatures more accurately.

5.1.2 Thermal heat mass (surrounding rocks)

In many Colorado communities, the surrounding rock formations can form heat sinks creating wonderful gardening spots for local gardeners. Nestled in among the mountains some gardeners have growing seasons several weeks longer than neighbors only a half a mile away. In cooler locations, rock mulch may give some frost protection and increase temperatures for enhanced crop growth. In warmer locations rock mulch can significantly increase summer temperatures and water requirements of landscape plants.

5.1.3 Influence of heat on Crop Growth

Temperature affects the growth and productivity of plants, depending on whether the plant is a warm season or cool season crop.

Photosynthesis: within limits, rates of photosynthesis and respiration both rise with increasing temperatures. As temperatures reach the upper growing limits for the crop, the rate of food used by respiration may exceed the rate at which food is manufactured by photosynthesis. For tomatoes, growth peaks at 96F.

Temperature influence on growth:seeds of cool season crops germinate at 40 to 80.Warm season crop seeds germinate at 50F to 90F.In the spring, cool soil temperatures may prohibit seed germination.

Examples of temperature influence on flowering

• Tomatoes

1. Pollen does not develop if night temperatures are below 55F
2. Blossoms drop if daytime temperatures rise above 95F before 10 am
3. Tomatoes grown in cool climates will have softer fruit with bland flavors.

• Spinach (a cool season, short day crop) flowers in warm weather with long days.
• Christmas cacti and poinsettias flower in response to cool temperatures and short days.

Examples of temperature influence on crop quality

• High temperatures increase respiration rates, reducing sugar content of produce. Fruits and vegetables grown in heat will be less sweet.
• In heat, crop yields reduce while water demand goes up.
• In hot weather, flowers colors fade and flowers have a shorter life.

The Table 5.1 llustrates temperature differences in warm season and cool season Crops

5.1.4 Influence of cold temperatures

The temperature variation over karnataka for the years 2008,2009,2010.2011 is shown in the figure 6.2. this also shows a clear annual cycle in the temp rise in feb-may and then falls during monsoon and winter.

fig 6.2 TEMPERATURE VARIATION OVER KARNATAKA FROM YEAR 2008-2011

5.2 Effect of Relative humidity

Relative humidityis the ratio of the partial pressure of water vapor in an air-water mixture to the saturated vapor pressure of water at a prescribed temperature. The relative humidity of air depends not only on temperature but also on the pressure of the system of interest.

5.2.1 Measurement

The humidity of an air-water vapour mixture is determined through the use of psychometric charts if both thedry bulb temperature(T) and thewet bulb temperature(T_w) of the mixture are known. These quantities are readily estimated by using a slingpsychometer.

There are several empirical correlations that can be used to estimate the saturated vapour pressure of water vapour as a function of temperature. TheAntoine equationis among the least complex of these formulas, having only three parameters (A, B, and C). Other correlations, such as those presented byGoff-GratchandMagnus Tetens approximation, are more complicated but yield better accuracy. The correlation presented byBuckis commonly encountered in the literature and provides a reasonable balance between complexity and accuracy^.

whereis the dry bulb temperature expressed in degrees Celsius (°C),is the absolute pressure expressed in hectopascals (hPa), andis the saturated vapour pressure expressed in hectopascals (hPa).

Buck has reported that the maximum relative error is less than 0.20% between -20°C and +50°C when this particular form of the generalized formula is used to estimate the saturated vapour pressure of water.

5.2.2 Pressure Dependence

The relative humidity of an air-water system is dependent not only on the temperature but also on the absolute pressure of the system of interest. This dependence is demonstrated by considering the air-water system shown below. The system is closed (i.e., no matter enters or leaves the system). The relative humidity over Karnatakafor the years 2008,2009,2010.2011 is shown in the figure 6.4

Fig 6.4 RELATIVE HU MIDITY OVER KARNATAKA 2008-2011

5.3 Effect of Rainfall

Fig 6.5 RAIN ANOMALY (top panel) Vs COFFEE AND Rice production over Karnataka

5.4 Effect of Solar Radiation

Sunlight is a portionof the electromagnetic radiation given off by the Sun, particularly infrared, visible, and ultraviolet light. On Earth, sunlight is filtered through the Earth’s atmosphere, and is obvious as daylight when the Sun is above the horizon. When the direct solar radiation is not blocked by clouds, it is experienced as sunshine, a combination of bright light and radiant heat. When it is blocked by the clouds or reflects off other objects, it is experienced as diffused light. The World Meteorological Organization uses the term “sunshine duration” to mean the cumulative time during which an area receives direct irradiance from the Sun of at least 120 watts per square meter.

Sunlight may be recorded using a sunshine recorder, pyranometer or pyrheliometer. Sunlight takes about 8.3 minutes to reach the Earth. On average, it takes energy between 10,000 and 170,000 years to leave the sun’s interior and then be emitted from the surface as light.

Direct sunlight has a luminous efficacy of about 93 lumens per watt of radiant flux. Bright sunlight provides illuminance of approximately 100,000 luxors lumens per square meter at the Earth’s surface. The total amount of energy received at ground level from the sun at the zenith is 1004 watts per square meter, which is composed of 527 watts of infrared radiation, 445 watts of visible light, and 32 watts of ultraviolet radiation. At the top of the atmosphere sunlight is about 30% more intense, with more than three times the fraction of ultraviolet (UV), with most of the extra UV consisting of biologically-damaging shortwave ultraviolet.

Sunlight is a key factor in photosynthesis, the process used by plants and other autotrophic organisms to convert light energy, normally from the sun, into chemical energy that can be used to fuel the organisms’ act

The solar radiation over karnataka for the years 2008,2009,2010.2011 is shown in the figure 6.7, which shows maximum radiation in summer and it decreases in winter.

2008 2009

2010 2011

Fig 6.6 SOLAR RADIATION OVER KODAGU FROM 2008-2011

MODULES OF THE PLANT GROWTH MODEL

The plant growth module computes crop growth and development based on daily values of maximum and minimum temperatures radiation and the daily value of two soil water stress factors, SWFAC1 and SWFAC2. This module also simulates leaf area index (LAI), which is used in the soil water module to compute evapotranspiration.

7.1 Initialization

Input variables, as listed in table 1, are read from file PLANT.INP. File PLANT.OUT is opened and a header is written to this output file.

Table 7.1 input data read for plant module

7.2 Rate calculations

The plant module calls three subroutines: PTS to calculate the effect of temperature on daily plant growth rate and rate of leaf number increase; PGS to calculate daily plant weight increase (g/plant) and LAIS to calculate in leaf area index.

In subroutine PTS the growth rate reduction factor (PT) is calculated every day using the following equation:

PT=1-0.0025((0.25TMIN + 0.75 TMAX)-26)²

Where TMIN and TMAX are the minimum and maximum daily temperatures.

Subroutines PGS calculate PG, the potential daily total dry matter increase (g/plant) :where SRAD is the daily solar radiation and PD is the plant density.

SRAD:

Y1 is obtained by

Y1 =1.5 -0.768. ((ROWASPC .0.01)² .PD)^0.1

Where ROWSPC is the row spacing in cm. The potential plant growth rate is limited by soil water stress through SWFAC and temperature through PT.

The plant cycle is divided in vegetative and reproductive phrases. The vegetative phase continues until the plant reaches a genetically determined maximum leaf number. During the vegetative phase, leaf number increase is calculated based on maximum rate and a temperature based limiting factor.

During reproductive phase, the difference between daily mean temperature and a base temperature is used to calculate the rate of plant development. Total rate of development towards maturity is accumulated as int.

Subroutine LAIS is called for phases to compute the change in leaf area index. During vegetative period, LAI increases as a function of the rate of leaf number increase. The potential rate is limited by soil water stress, through SWFAC and temperature through PT. Its value is given by:

dLAI=SWFAC. PT.PD.EMP1. Dn.a/1+a

where PD is the plant density , EMP1 is the maximum leaf area expansion per leaf, and a is given by :

a= e^EMP2.(N-nb)

Where EMP2 and nb are coefficients in the expolinear equation and N is the development age of the plant.

After plant has reached the maximum number of leaves, LAI starts to decrease as a function of the daily thermal integral, di. The rate of decrease is given by

dLAI= -PD.di.p1.SLA

Where P1 is the dry matter of leaves removed per plant per unit development after maximum number of leaves is reached and SLA is the specific leaf area.

7.3 Integration

Changes to leaf area index, plant weights and leaf number are integrated into the appropriate state variables at the beginning of the integration section.

7.4 Output

Daily output is written in PLANT.OUT file.

7.5 Close

The PLANT.OUT output file is closed.

Fig 7.1 Planning the Concept Of Dynamical Agriculture Model