Effects of Temperature and CO2 on Growth and Yield of Corn (Zea mays L.) under Climate Change in An Giang Province Vietnam

At the present time, climate change causing increasing temperature, dryness and CO2 has exposed negative impacts on crops. In this study, four independent chambers were built to establish the expectation of different temperatures between the chambers. The experiment was carried out from January to March 2021 at An Giang University experimental area. Corn variety “Gold 58” was grown in 42 pots (34x28x28cm) in a chamber, 2 plants/pot. Temperature and CO2 were hourly recorded. Plant height, leaf number, stover biomass were measured every 10 days period. The results showed that days to maturity in 4 chambers ranged from 62 to 67 days and accumulated temperature from transplanting or sowing to maturity (Tsum) varied from 1976 to 2077 0C d. The average of CO2 concentration of 10 days period in the chambers varied from 527.5 to 558.3 ppm at daytime and 626.1 to 744.4 ppm at night-time (highest in chamber 1). Plant height at harvest in chamber 1 was 306.7 ± 11.5 cm, while it was decreased by 6.1%; 11.7% in chambers 3 and 4. Total biomass above the ground in chamber 2, 3, 4 also significantly declined by 25.2%; 31.6% and 36.4% at harvest, respectively. Fruit yield also reduced by 14.3%, 34.9% and 34.1% respectively compared to chamber 1. Observed versus simulated comparison by our crop-model (based on R language programing) resulted in RRMSE value less than 8.2%. NSE index (Nash Sutcliffe Efficiency) of the models greater than 0.75 show that the models have high reliability.


Introduction
In the general situation of climate change in the world, Vietnam is one of the countries most affected by climate change in the world [7].In recent decades, average temperature tends to increase in most observational stations over Viet Nam and temperatures grew by 0.62 0 C in the period 1958-2014 in average for the whole Vietnam [18].For instance, it increased 0.42 0 C in period 1985-2014 [15].The observation data of 1961-2014 recorded that maximum and minimum temperature over Viet Nam tended to increase considerably [24].The number of hot days that maximum temperature is greater than 35 0 C, increased almost in all over Viet Nam [33].
Corn can use solar energy more efficiently and sustain relatively high temperatures up to a crucial threshold due to the C4 plant.Heat stress is defined as temperatures above a certain threshold that cause irreversible crop growth and development [10] which is hampered by both hot and low temperatures [32].High temperatures can cause a variety of morphological, anatomical, physiological and biochemical changes to corn.[5].However, at elevated CO2 conditions, maize showed an increase in CO2 assimilation during periods with less rain [21].These increases are based on the high intracellular concentration of CO2 at low stomatal conductance and decreased transpiration [40].
Crop modeling are significant systems for simulating crop development and advancement for agronomy understanding, too for environment influence [11].As of recently, various yield models have been created for significant crops like wheat [39], maize [4] and, rice [19].
Climate change is going to continue to influence corn production and the knowledge these effects will help determine future production areas [12][13][14] and can apply methods to adapt to new conditions to facilitate farming.Our research model is an effective tool to estimate and predict climate change impacts, in which the simple crop model has strong point without requiring larger number of parameters, can predict in the conditions of climate change, changes of space and time of planning, can help local and senior managers.

Experiment design
The experiment was conducted in the experimental area of An Giang University to assess the effects of temperature and CO2 concentration on the development and yield of Gold 58 corn variety, after that, predicting the yield base on the parameters of cultivation management, soil, and weather.The experiment was randomly designed with 3 times replication.Corn was planned in pots with 34x28x28 cm size (loamy sand soil), putting in 4 chambers greenhouse designed with different temperature.An automatedly record system of temperature, CO2 concentration, solar radiation with ventilation, misting, drop irrigation systems stored data.
To observe the effects of climate changes such as temperature and CO2 increase, plant heigh, biomass/pot, leaf number were collected every 10 days.Final yield, fresh biomass, dry stalk biomass, dry grain was recorded at harvest.Besides, the experiment was conducted with the aim to collect the other parameters to build corn crop model to estimate the final yield in different temperature and CO2 concentration.Input varieties needed to run corn crop model [35,39] were weather varieties: average temperature, minimum, maximum ( 0 C), Tsum, I50A (cumulative temperature necessity for leaf area development to intercept 50% of radiation ( 0 C d), I50B (cumulative temperature till maturity to reach 50% radiation interception due to leaf senescence ( 0 C d); crop management: sowing date, harvest date, irrigation (mm); soil characteristics: AWC (available water capacity), RCN (Runoff curve number), DDC (Deep drainage coefficient), RZD (Active main root zone depth) [39]; initial varieties: initial biomass (kg), initial cumulative temperature, initial fraction of solar radiation interception [39].

Crop model description
Our crop model is a simple general model that simulates plant growth using few parameters and data requirements without crop-specific processes for simple application to many crops [39].From this model, it is possible to develop a few more specific parameters of nutrition and pests depending on the growing area.
The model simulates the process of crop growth, development and yield using daily step time [22].The factors soil, water, crop, and climate are considered in the model that express through via 11 equations.Crop yields can be determined by the amount of biomass accumulated over time throughout the plant growth time and adjusted with the harvest coefficient (the proportion of biomass yielding economic value).This accumulated biomass is mainly influenced by variables such as solar radiation, temperature, humidity, irrigation, CO2 concentration, physicochemical properties of soil, crop species [36].
Based on the established equations combined with the relevant parameter sets, a program to simulate cumulative biomass and crop yield prediction is established using the R programming language.Equations and related parameters used in the simulation program are presented in detail in the following section.
-fSolar: the fraction-of solar radiation intercepted by a plant canopy [12].The fSolar is constructed on Beer-Lambert's law of light reduction and solar radiation interception.-RUE: Radiation Using Efficiency.
From ( 1) and ( 2), calculate the mature yield (final yield) as a product of the biomass and harvest index (3) [21].
Yield = Biomass_cummaturity * HI (3) where: -Biomass_cummaturity : Biomass of mature plants -HI: Harvest index [22] fSolar for leaf growth senescence period is calculated as follows [12]: where: -I50A: the cumulative temperature necessary for leaf area development to intercept 50% solar radiation during canopy closure [12].-I50B: the cumulative temperature necessary from maturity to 50% of radiation interception during canopy senescence [12].-fSolar-max: the maximum fraction of radiation interception.The cumulative temperature is calculated as follows: TT and Tsum are calculated like this: TT i+1 =TT i +∆TT (6) Where: -TT i: average temperature accumulated to day i -∆TT: average temperature added per day -T: daily average temperature -Tbase: the base temperature for phenological development and growth ( 0 C).
The influence of temperature on biomass growth rate [23] is determined as follows: [12] where: -T is the daily mean temperature.
-Tbase and Topt are the base and optimal temperatures for biomass growth for a given crop species.
The impact of heat stress on biomass growth rate [24] is calculated: T extreme -T heat , T heat <T max ≤T extreme 0, T max >T extreme (8) [12] where: -T max: daily maximum temperature -T heat: threshold temperature when biomass growth rate begins to be decreased by heat stress -T extreme: extreme temperature threshold when the biomass growth rate reaches 0 due to heat stress.RUE rises linearly until CO2 is 700 ppm [25].When CO2 concentration is higher than 700 ppm, RUE is kept constant due to the likely saturation of RUE to elevated CO2 [25].The impact of CO2 on RUE in the model is determined as follows: [12] Where: SCO2: the crop-specific sensitivity of RUE to elevated CO2 * Drought stress impact on RUE and radiation interception [12].
A water budget routine is used for water balance simulation and to determine drought stress f(water)=1-S water .ARID (10) [12] Here: -ARID: the ARID index after [26] ranges from 0 (no water shortage) to 1 (extreme water lack and associated drought stress).(10) [12] Inside: -ET0: evapotranspiration -PAW: plant-available water content in the soil [12].The experiments create the observed data and are simulated by R (R language programming) to simulate the final corn yield.

Effect of temperature
In chamber 1, the average temperature was lowest, ranked from 26.3 -30.3 0 C, with the peak was at 46.1 0 C, which was significantly lower than the other 3 chambers (Figure 1b), especially mean maximum temperature from the period of 20 -30 day after planting (DAP) and 60 -DAP to harvest time (Figure 1e).In chamber 4, the average temperature was higher than in chamber 1 from 0.7 -1.0 0 C and the maximum temperature was higher from 4.7 0 C, depending on the different stages (Figure 1e).In the other 2 chambers, the temperature was also higher than in chamber 1, in which chamber 4 was recorded the highest temperature in all maximums, average and peak levels.
Corn variety "Gold 58" ended its growth period in 4 chambers were respectively 67, 65, 64 and 62 days, with Tsum were 2077, 2068, 1990 and 1976 0 C day (Figure 1d).It is clearly that with the higher temperature, the corn growing period shorten from 2-5 days.
The experiment was conducted in the sunny season, with the rank of temperature from 21.4 -47.6 0 C in chamber 4 at harvest time (Figure 1a, 1b).The temperature was strongly increase as the effect of the climate change in the chamber 2, 3, 4 that peak temperature was normally higher than 45 0 C while the peak temperature in chamber 1 was significantly lower, at 45.7 -46.1 0 C (Figure 1e).In addition, the total number of hours with stress temperature in chamber 1 was still the lowest, lower than from 216% hours ≥ 34 0 C and 17-67% hours ≥ 45 0 C (Figure 1f).Reseach of Zhang and Yang [38] when build up the model of a nonlinear regression model between temperature and yield, the stress temperature threshold of corn was 36.06 0 C. Corn yield was correlated with the number of days under high temperature stress, corresponding to a 9.2% increase in temperature, the yield decreased by 27.3% [38].Growth decreases when temperatures exceed 35 0 C [20].

Effect of CO2 concentration (ppm)
CO2 concentration (ppm) in the chamber 1 was significantly higher than in the chamber 2, 3, 4 in both day and nighttime.CO2 concentration in daytime fluctuated from 527.5 ppm -558.at nighttime was higher and fluctuated from 613.9 -744.4 ppm (Figure 2).CO2 in chamber 1 was higher, from 4.5 -5.4% at daytime and higher the other chamber from 15.9 -17.6% at nighttime (Figure 2).The results of the hourly recording showed that the CO2 concentration at chamber 1, 2, 3 was the lowest from 9 am to 2 pm, from 460-470 ppm.However, in chamber 4, the CO2 concentration increased again during this time period (Figure 3a, 3b, 3c, 3d).This may be because corn plant did not use as much CO2 for photosynthesis at this time as other chamber.Corn biomas was lowest, the peak temperature appear longer and the yield was lowest in the chamber 4 (Figure 1e, Table 3).There was a combination between the highest CO2 concentration and the lowest temperature in the chamber 1 among 4 chambers, having highest final yield.

Plant heigh and leaves number
Plant height in chamber 1, 2 were significantly higher than in chamber 4 at level 5% (Table 1).At the harvest time, the heigh achieved in 4 chambers from 306.7, 305.9, 288.0, and 270.7 cm respectively (Table 1).
The temperature in chamber 1 was from 2-3 0 C higher than the temperature outside, the corn developed stalks, leaves and heigh properly.Maximum temperature increased in the chamber 2, 3, 4, especially in the chamber 4 reduced the development of the corns (Table 1).
The average members of leaves were significantly different among 4 chambers after 30 DAP to harvest that chamber 4 significantly lower than in the chamber 1, 2, 3 (Table 1

Biomass (above the ground surface) of corn variety Gold 58
Biomass above the ground of the corn variety Gold 58 (g/pot) was significantly different at 5% level from 20 DAP to harvest, in which the corn weight in the chamber 1 was significantly higher than the other chambers at 14.3%, 34.9% and 34.1% respectively (Table 2).A research on corn named "Bap Nu" from Nghiem, et al. [23] in the same season in the net house showed that the highest biomass of Bap Nu was at 1960 g/pot (2 plants/pot), which is 33.4% lower than in the chamber 1.The plant height in four chambers was from 2.7 -3.0 m while in farmer field normally from 2.2-2.4m.
Many experiments and model simulations research have almost showed similar when corn grown in the higher temperature condition until a specific temperature value, it would increase biomass of stalks and leaves [1,6,9,26,28,30].

Biomass and yield
Biomass, dry fruit, dry grain, cob husk and yield in chamber 1 were significantly higher than in the other 3 chambers (the higher temperature and the lower CO2 concentration) (Table 3, Figure 1, 2).Table 3.Some parameters at harvest (g/pot).Corn yield in chamber 1 was highest, at 1050 g/pot, and chamber 3, 4 were lowest, at 691.75 g/pot, 683.25 g/pot, respectively.The yield in chamber 2 was higher than in chamber 3, 4 but biomass, dry stalk leaves, dry grain, dry cob husk were not significantly different.By the other way, the biomass was transferred to chamber 1 higher than in chamber 2, 3.

Chamber
At high temperature in the chamber 2, 3, 4 (Figure 1), the yield of the corn decreased.This could be because the temperature at the chamber 2, 3, 4 so high, causing the inhibition of the growing process of the plants such as sympathies, respiratory, metabolism in the plants.

Correlation between temperature, CO2 with biomass and yield
The analysis also showed that increasing the temperature both reduce the biomass and yield (Figure 4a, 4b).However, when the CO2 concentration increased, both increased (Figure 4c, 4d).c) d) Figure 4. Analysis of the negative correlation between temperature vs biomass-yield (Fig. 4a, 4b) Analysis of the positive correlation between CO2 concentration vs biomass-yield (Fig. 4c, 4d) Lindey and Thomson [20] demonstrated that temperature of 33.9 0 C or above gave 1% yield loss due to leaf rolling by computer simulation [13].When there is a lack of water, the corn leaves tend roll up more [13].Yield is reduced by 1% for every hour the leaves are rolled but during the week of silking it is reduced by 1% in just 4 hours [20].Besides that, Kucharik and Serbin [17] resulted that corn yields could possibly decrease by 13% and 16% for each 1 0 C. If total summer rainfall increases by 5-10%, the impact of increasing temperature on yield will be reduced [29].

Simulated models to predict yields comparing to the observed data
Data on corn yield was calculated into kg/ha to be modelized and compared to experiments (black colume, observed data) (Figure 5).The results of the simulated model were underestimate from 6.2% to 8.9% in comparison to observed parameter in this study.Corn yield was reduced when the extreme temperature occurs during the pollination period especially when combined with severe water shortage [16].During the grain filling stage, excessively high temperatures upper threshold will reduce yield [29].In this research, the model predicted the yield of the chamber 3 and 4 reducing at 33.9% and 34.6% respectively comparing to the chamber 1.Some crop models in the climate change analyses the sensitivity in the model by simulating the increase of CO2 concentration in plant growth environment, which caused increase of corn yield corn [1,6,8,9,25,26,28,30].In this paper, the author did not analyze prediction of separated CO2 concentration and temperature on the yield and biomass of the corn.However, there was empirical data to calibrate crop models again in the following growing season of our project.

Conclusion
Gold 58 corn variety grown in chambers greenhouse conditions to investigate the effects of climate change in temperature and CO2 resulted that chamber 1 demonstrated the lowest temperature and highest CO2 concentration (both day and night).The fruit yield and fresh biomass also reached the highest compared to the other chambers, resulting 1,050.0g/pot and 1900.2 g/pot, respectively.However, the growth duration was longer from 2-5 days.High temperature and lower CO2 in chamber 3, 4 reduced fruit yield 34.1 -34.9%.Observed versus simulated comparison by the model (based on R language programing) resulted RRMSE value less than 8.2%.This crop model can be used to estimate biomass and yield under changing temperature and CO2 conditions.

4 -
The models use cumulative temperature to determine phenological development, along with CERES-Wheat[23].

Figure 3 .
Carbon dioxide concentration (ppm) recorded in every hour in 4 chambers.

Figure 5 .
Figure 5. Summary map plot of final corn yields between observed and simulated variable.

Table 1 .
). Plant heigh (cm) and the number of leaves in 4 chambers every 10 DAP and harvest time.