Background and motivation
We wish our Bio-pesticide project could be applied in the real crop field one day. And for this vision, we want to know the possible efficiency and cost of our Bio-pesticide to optimize our project and make it closer to the application.
Different fields vary in acreage and weeds amount, based on these variates, we predicted proper dsRNA dosage in certain area fields and the cost of it.
Methodology
We use a formula to describe relationship between area and dsRNA dosage: \[ W_{dsRNA} = S_{field}\frac{V_{plant}}{V_{field}} \times P \times \vartheta \]
- Where
- \( W_{dsRNA} = \) total mass of dsRNA should be used
- \( S_{field} = \) area of land
- \( V_{plant} = \) water consumption of per plant
- \( P = \) the amount of weeds in unit area
- \( \vartheta = \) the minimum dosage of dsRNA to kill weed
Thanks to our human practice work, we got many useful data, like the plant water consumption and the total number of weeds per mu (0.0667 hectares)
By the assumption that 133pg/L dsRNA can effectively suppress the expression of target gene confidence interval [2].
Meanwhile, water absorption of each plant can be represented by this formula: \[ V_{plant} = ET_c + C_w \]
- Where
- \( ET_c = \) Crop transpiration rate
- \( C_w = \) Plant water consumption
What known is plant water consumption \( C_w \) is much less than RCE, so we simplify the formula to: \[ V_{plant} = ET_c \] Based on the Penman computing method and the data from China Meteorological Observatory (CMO), we use equation set to compute the \( ET_c \) in China.
Plant transpiration, ETc, can be determined by transpiration of reference plant, ET0 and transpiration coefficient, Kc. The method of calculating ETc is following: \[ ET_c = ET_0 \times K_c \] We use Penman-Monteith formula to calculate transpiration of reference plant. \[ ET_0 = \frac{0.408\Delta (R_n-G)+\gamma \frac{37}{T_{day}}u_2(e_s-e_a)}{\Delta + \gamma(1+0.34u_2)} \]
- Where
- \( ET_0 = \) Transpiration of reference plant in one day
- \( R_n = \) Average net radiation in one day
- \( G = \) Soil heat flux
- \( T_{day} = \) Average temperature in one day
- \( u_2 = \) Average wind speed at the height of meters
- \( E_s = \) Saturated vapor pressure
- \( e_a = \) Actual vapor pressure
- \( \Delta = \) Slope of saturation vapour pressure curve at air temperature
- \( \gamma = \) Psychrometric constant
In formula, \( T \) and \( u_2 \) can be determined by mesure, \( (e_s-e_a), \gamma, \Delta, G \) can be calculated by parameter. \( G \) , in general, is considered to be 0.5 times \( R_n \) in the evening, 0.1 times \( R_n \) in the day.
\( \gamma \) is related to atmospheric pressure. We can get it by following equation: \[ \gamma = 0.665 \times 10^{-3} \times 101.3(\frac{293-0.0065z}{293})^{5.26} \] where \( z \) is Altitude.
Saturated vapor pressure, \( e_s \), can be get by the following equatiin: \[ e_s = e^0(T_{day})=0.6108exp[\frac{17.27T_{day}}{T_{day}+237.3}] \]
Actual vapor pressure, \( e_a \), can be get by the following equation: \[ e_a=e^0(T_{day})\frac{RH_{mean}}{100} \] Where \( H_{mean} \) is average air humidity in one day
Slope of saturation vapour pressure curve at air temperature, \( \Delta \), can be get bu the following equation: \[ \Delta=\frac{4098[0.6108exp(\frac{17.27T_{day}}{T_{day}+237.3})]}{(T_{day}+237.3)^2} \]
Average net radiation in one day, Rn, is the difference between the incoming net shortwave radiation (\(R_{ns}\)) and the outgoing net longwave radiation (\(R_{nl}\)): \[ R_n=R_{ns}-R_{nl} \]
Net shortwave radiation, \(R_{ns}\) and net longwave radiation, \(R_{nl}\), can be calculated by the following equation: \[ R_{ns}=(1-\alpha)R_s \] \[ R_{nl}=\sigma[\frac{T_{day}^4}{2}](0.34-0.14\sqrt{e_a})(1.35\frac{R_s}{(0.75+2\times 10^{-5})R_a} - 0.35) \] \[ R_a=\frac{12(60)}{\pi}G_{sc}d_r[(\omega_2-\omega_1)sin(\varphi)sin(\delta)+cos(\varphi)cons(\delta)(sin(\omega_2)-sin(\omega_1))] \]
- Where
- \(R_a = \) Extraterrestrial radiation
- \( G_{sc} = \) Solar constant
- \( d_r = \) Inverse relative distance Earth-Sun
- \( d = \) Solar declination [rad]
- \( j = \) Latitude [rad]
- \( \omega_1 = \) Solar time angle at beginning of period [rad]
- \( \omega_2 = \) Solar time angle at end of period [rad]
Results
Through modelling, we got the application amount of dsRNA in different areas of China.
So farmers could use this data to decide the water need, and the real dosage of certain plant rely on crop kinds.
Discussion
It could be clearly seen the usage of dsRNA in major grain producing areas of China (North China Plain, Northeast China Plain and Yangtze Plain, Middle and Lower) are maximum about 10.16-15.77mg/mu. This result has a guiding significance to our experiments and improved our application design.
Reference
- [1] S Tabor, CC Richardson. T7 DNA polymerase 1990
- [2] Joga et al. - 2016 - RNAi Efficiency , Systemic Properties , and Novel Delivery Methods for Pest Insect Control What We Know So Far
- [3] H huang et al -1957-2012- The reference crop evapotranspiration quantity of space analysis
