Effects of GroMore^® Program on Rice Yield and GHG Emissions in a Korean Paddy Rice

Abstract

The agronomic benefits of pesticides combined with amino acid application to increase rice production have been recognized, but they are still not well-known for greenhouse gas (GHG) emissions and mitigation in irrigated paddy fields. Thus, this study was conducted to investigate the combined effects of pesticide and amino acid application on rice yield and methane (CH₄) emissions in a Korean rice paddy. A field experiment was conducted with five levels: none (no pesticide application, T1), different conventional practices (combined application of insecticides and fungicide, T2 and T3), and GroMore^® programs (combined application of insecticides, fungicides, and amino acids, T4 and T5). Rice grain yield and yield components were obtained using agronomic measurements. To determine the greenhouse gas intensity (GHGI) of each treatment, CH₄ emissions were measured throughout the rice growing period. Results showed that the chemical applications in combination with amino acids in T4 obtained a higher grain yield and number of panicles per plant compared to T1, T2, and T3, while T4 and T5 showed no difference on filled spikelets except for T2. T3 and T5 showed lower respective cumulative CH₄ emissions by 30% and 32% during the entire rice growing season, compared to no chemical application (T1). Meanwhile, N₂O emissions were negligible in all treatments because the paddy field was flooded most of the growing season. The results of the impact of GroMore^® programs on relatively higher grain yield and lower GHG emissions are presented. In conclusion, the application of pesticides combined with amino acids obtained lower GHGI values.

1. Introduction

In agricultural fields, rice cultivation practices, such as the application of chemical fertilizers, pesticides, tillage, amendment of organic material, flooding paddy fields, etc., contribute approximately 10% of global man-made methane (CH₄) and nitrous oxide (N₂O), a potent GHG [1,2,3,4]. Meanwhile, sustaining rice productivity is most important in meeting the increasing demand for food security since increasing greenhouse gas (GHG) emissions worldwide have been attributed to global warming and climate change, which has affected drought, flood, and extreme temperatures that devastate crops. Recent agricultural practices face different challenges, such as sustaining crop productivity and increasing pathogen and pest attacks in relation to fluctuating climatic factors [5,6]. Crop pests especially influence super threats to global agricultural production [7].

Large amounts of agrochemicals such as herbicides, insecticides, fungicides, and plant growth regulators in terms of pesticides are used to control weeds, pests, and pathogens in agricultural fields. In Korea, the total use of agricultural pesticides amounted to 19,882 tons in 2022 [8]. Frequently, the application of pesticides leads to chemical residue accumulation in intensive agriculture, causing contamination of water and soil and killing off useful or harmful organisms, and throwing off the ecological balance of the agroecosystem [9,10,11,12,13]. There are benefits of pesticide usage on agricultural productivity and possible negative effects on health and the environment. Tremendous benefits such as improving crop productivity, protection of crop losses (yield reduction), and disease control have been derived from the use of pesticides in agriculture [14,15,16]. There are potential benefits of pesticides: controlling diseases and weeds and vectors of crop disease and organisms (human and livestock) disease and preventing harmful organisms that influence human activities [17]. Particularly, pests reduce agricultural income in most developing countries since farm and postharvest losses contribute to hunger and malnutrition. According to the United Nations Children’s Fund (UNICEF), malnutrition is ‘‘largely a silent and invisible emergency, exacting a terrible toll on children and their families’’ [18]. Although, the credits of pesticides include enhanced economic benefits such as increased production of food and fiber, and amelioration of vector-borne diseases, their negative effects have resulted in critical health implications to man and his environment such as pesticide contamination and degradation of soil, water, and other vegetation in addition to possible negative effects on organisms (birds, fish, beneficial insects, non-target plants, etc.) [19].

The use of agrochemicals can effectively suppress the growth of weeds and the threat of insects, and thus improve crop growth, yet influence GHG emissions directly or indirectly [1,20,21]. Much research on the influence of agrochemicals used in croplands is focused on the mode of action, efficacy, resistance of plants, nitrogen-use efficiency, and therefore higher crop production [10,19,22,23,24,25,26]. Research attempted on foliar spray plant growth regulators to increase rice yield reported that amino acids absorbed from the leaves increase the mineral nutrients content of the grain and improve its quality [27]. Foliar spray of amino acids (with the recommended dose of fertilizers for plant growth) on rice leaves rapidly absorbs and assimilates them, increasing the number of leaves, leaf area index (LAI), crop growth rate (CGR), total chlorophyll content, and yield [28,29]. When the nitrogen content of rice leaves increases, a great deal of N is invested in Rubisco protein, the primary CO₂ fixation enzyme [30], and the CO₂ conductivity of mesophyll cells is improved [31], which increases photosynthesis.

Currently, only a few studies on the impact of agrochemical application on GHG emissions in agriculture have been reported. Gianessi (2013) [32] reported that herbicide application to manage weeds reduced GHG emissions by saving the fuel consumption of traditional farming machinery. Jiang et al., (2015) [33] reported that the application of herbicides reduced N₂O emissions in winter wheat fields and CH₄ and N₂O fluxes in irrigated rice paddy fields. While another study reported that the combination of two herbicides (Bensulfuron-methyl and Pretilachlor) increased the emissions of N₂O and CH₄ [34]. The use of pesticides plays an important role in increasing crop production, but its impact on GHG emissions and mitigation in irrigated paddy fields is not well-known. Additionally, there have been no research reports on the effect of synthetic agrochemical and amino acid applications on rice production and GHG emissions.

Agriculture is directly impacted by climate change and extreme weather, which alters the dynamics of pest occurrence, the length of the rainy season, the amount of rainfall, the timing and course of typhoons, and the amount of sunlight. These changes have an impact on agricultural production both directly and indirectly. In terms of pest management and prevention, granular insecticides have a 30- to 60-day pest control efficacy, whereas Syngenta Korea’s GroMore^® program, which combines insecticides, fungicides, and amino acids, has a 100-day pest control efficacy. The fungicides, insecticides, and amino acids in the drenching speed up the early growth of rice, prolonging the tillering period, increasing the number of panicles, and further increasing rice yield. This enables the number of foliar sprays to be reduced from two times to one during the heading stage. Since its introduction in the Korean market in 2016, the GroMore^® program has been implemented all over the country, covering an area of almost 20,000 hectares as of 2024. It has been acknowledged for its effectiveness and is recommended as a local government subsidy program. Therefore, the purpose of this study was to look into how the use of GroMore^® programs affected rice yield and greenhouse gas emissions.

2. Materials and Methods

2.1. Field Experiment

A field experiment was conducted at a local rice paddy field in Pyeongtaek-si, Gyeonggi province, Korea (26°58′ N, 127°10′ E) from May to October 2023. The climatic condition is characterized by an annual average air temperature of 13.2 °C, radiation of 13.1 MJ m⁻², and cumulative precipitation of 1356.5 mm (Figure 1), where the average air temperature in the area ranges from around 10 to 16 °C of the average annual temperature in Korea. The experiment field belongs to a relatively humid region, having a significantly similar amount of precipitation to the average in Korea. Precipitation is mostly concentrated in the summer season. During the rice growing season, the average air temperature, radiation, and cumulative precipitation were 22.4 °C, 16.2 MJ m⁻², and 1094 mm, respectively.

Soil type for the experiment is classified as Alisols [35]. Soils are used mainly for paddy rice. The soil physico-chemical properties are shown in

Table 1. Soil chemical properties of the rice paddy field.

Soil Texture	pH	O.M 1	Av. P2O5	Av. SiO2	K+	Ca2+	Mg2+
	(1:5)	(g kg−1)	(mg kg−1)	(mg kg−1)	(cmolc kg−1)
Loam	6.5	13.3	23	173.7	0.5	4.4	1.5

¹ organic matter.

. It is loam, 0 to 1% slopes, drained, and permeable. Based on the local field and climate conditions in the region, the experiment was set up in a completely randomized block design, consisting of five plots with three replications. The treatments for each plot (300 m², $6\times 50 \mathrm{m}$) is shown in

Table 2. Specific chemical sources, purpose, and the recommended rate in the treatments.

Treatment	Chemicals	Purpose	Recommended Rate
			(g, mL ha−1)
T1	-	-	-
T2	Fipronil	Insecticide	10,000
	Orysastrobin	Fungicide	10,000
T3	Clothianidin	Insecticide	10,000
	Thifluzamide	Fungicide	10,000
	Tiadinil		10,000
T4	Cyantraniliprole	Insecticide	800
	Pymetrozine		800
	Clothianidin		2000
	Orysastrobin	Fungicide	2000
	Amino acid (water soluble)	Nutrition	1500
T5	Cyantraniliprole	Insecticide	400
	Thiamethoxam		400
	Clothianidin		2000
	Orysastrobin	Fungicide	2000
	Amino acid (water soluble)	Nutrition	1500

T1: none, T2 and T3: conventional practices, but different chemicals of insecticide and fungicide, T4 and T5: GroMore^® programs (T4 = GroMore_Star, T5 = GroMore_Duo).

. To prevent mixing chemicals from water between the treatment areas, polyvinyl chloride (PVC) with 200 mm in height was installed in between plots.

Figure 1. The mean of the average air temperature and radiation and amount of rainfall observed at the regional climate station of Pyeongtaek-si (climate datasets available from National Institute of Agricultural Sciences for agricultural climatic information [36].

Figure 1. The mean of the average air temperature and radiation and amount of rainfall observed at the regional climate station of Pyeongtaek-si (climate datasets available from National Institute of Agricultural Sciences for agricultural climatic information [36].

2.2. Management of the Chemicals and Fertilizer Application, Water Irrigation, and Rice Cultivation

For chemical application, recommended treatment amounts of T4–T5 in Table 2 were diluted based on 80 L ha⁻¹ of water to make a diluted solution. The granular type of pesticide for T2 and T3 was sprayed to the plots directly on transplanting day, while 400 mL of stock solution per seedling box for T4 and T5 was applied to the seeding box using a 10 L PVC water drench can (Jinsan Inc., Jeonnam, Republic of Korea) at 1 day before transplanting. This cultivar (Kosihikari, Oryza sativa L.) is a broad rice variety in Gyeonggi-do, Korea, and it has a medium–late maturity (150 d). Three to four seedlings per hill were established with a density of 30 cm $\times$ 15 cm.

For each treatment, urea, superphosphate, and potassium chloride were used as sources of N-P₂O₅-K₂O for rice cultivation. The amounts of N-P₂O₅-K₂O were 90-45-57 kg ha⁻¹ following the recommended amount of fertilizer for paddy rice in Korea [37]. Urea was applied three times on −1 (30%), 40 (40%), and 70 (30%) days after transplanting (DAT). The entire amount of superphosphate (45 kg P ha⁻¹) was basally applied. Potassium chloride was split into two applications and applied on −1 (60%) and 70 (40%) DAT.

Water management practice was continuously flooded from −20 DAT to 30 DAT at the beginning of the rice growing season. When the rice plant reached the tillering stage on 30 DAT, mid-season drainage was applied for three weeks (late June to mid-July) to suppress the non-productive tiller, and then irrigation was applied until the physiological maturity stage. During the flooded period, the water level was continuously maintained at a depth of approximately 5 cm from the soil surface. The rice was harvested at 145 DAT.

2.3. Agronomic Measurements

The rice was harvested at 145 DAT. Grain yield (GY) and other yield components (thousand-grain weight, number of panicles per plant, total spikelets per panicle, and % filled spikelets) of rice were obtained after harvest. GY was measured after oven drying at 70 °C for 3 days.

2.4. Measurement of CH₄ and N₂O

The closed chamber method was used to examine the plot’s gas flux [38]. For collecting gas samples, a 60 × 60 × 120 cm acrylic chamber with a fan and thermometer within the lid was employed in each plot.

CH₄ and N₂O were sampled in the morning (10:00 to 12:00) one to two times per week using a 50 mL plastic syringe at 0, 30, and 60 min after closing the chamber. The collected gas samples were analyzed with a gas chromatography (Agilent, California, USA) equipped with FID and ECD detectors to determine the concentrations of CH₄ and N₂O, respectively. Except for the period of gas sampling, the chambers were kept open during the rice growing season to prevent the greenhouse effect on rice growth. The CH₄ and N₂O emissions were calculated using the following equation [39]:

$$F=\rho \times {\displaystyle \frac{V}{A}}\times {\displaystyle \frac{\Delta c}{\Delta t}}\times {\displaystyle \frac{273}{\left(273+T\right)}}\times {\displaystyle \frac{P_a}{760}}\times 60\times 24$$

where F is the flux (mg CH₄ m⁻² d⁻¹ or mg N₂O m⁻² d⁻¹), $\rho$ is the gas density ($\rho$ = 0.714 g m⁻³ for CH₄ and $\rho$ = 1.964 kg m⁻³ for N₂O at 273 K and 101.325 kPa (760 mmHg)), V is the volume of the chamber (m³), A is the cross-sectional area of the chamber (m²), $\Delta$c/$\Delta$t is the change in gas concentration inside the chamber as a function of time t (10⁻⁶ m³ m⁻³ min⁻¹), T is the air temperature inside the chamber (°C), 273 is a correction factor between °C and K, and Pa is the air pressure (kPa). The value of Pa was assumed to be 760 mmHg (101.325 kPa) in our calculation.

To estimate the daily data of gas emissions, linear interpolation between the observed values of gas concentrations was used [2], and summed up to estimate its GWP in CO₂ terms through multiplying by 25 or 300 for CH₄ or N₂O, respectively [40]. The standard curve was calibrated at 0.00, 0.10, 0.50, and 1.00 mg L⁻¹ of N₂O and 0, 3, 5, and 10 mg L⁻¹ of CH₄ every week before gas analysis [41].

2.5. Greenhouse Gas Intensity (GHGI) Estimated with Aggregate Emission of CH₄ and N₂O

The cumulative amounts of CH₄ and N₂O emissions in the CO₂ equivalent for the 100-year horizon of each treatment were calculated, projecting the global warming potential (GWP) of CH₄ and N₂O as 25 and 300, respectively [40]. The GHGI (kg CO₂-eq. t⁻¹ per grain yield) was interpreted as yield-scaled aggregate emission of CH₄ and N₂O in the CO₂ equivalent at the 100-year horizon and calculated using the below equation:

GHGI = aggregate emission in the 100-year CO₂ equivalent per grain yield.

2.6. Statistical Analysis

ANOVA (analysis of variance) was conducted using the XLSTAT V.2023 software while the differences between the treatments were analyzed using Duncan’s multiple range test (DMRT) at p < 0.05 of probability. Principal component analysis (PCA) was applied using the XLSTAT software to clarify the effect of each treatment on rice productivity and GWP.

3. Results and Discussions

3.1. Rice Yield Characteristics

The chemical applications in combination with amino acids in T4 obtained higher grain yield and number of panicles per plant compared to T1, T2, and T3, although there were no different total spikelets per panicle, filled spikelet (%), and thousand-grain weight (g) among them (Figure 2). In the results, the effect of pesticides combined with amino acids as biostimulants was remarkable. Although T5 was not statistically significant with T1, T2, and T3, the higher grain yields due to amino acids including phenylalanine, tryptophan, and tyrosine improved the number of panicles per plant and seed-setting rate [42,43,44].

Foliar application of amino acids supports rice growth by improving photosynthesis and biosynthesis within the plant. Also, water-soluble amino acids improve the accumulation of the amino acid content in plants. Garcia et al., (2011) [45] reported that the application of single or complex forms of different amino acids supplied essential nutrients for plant growth. Amino acids accelerate the absorption of micronutrients such as metal ions that are chelated with different amino acids in the plant [46]. As a source of nitrogen (N), amino acids can enhance nutrient N availability in the soil by promoting the activity of beneficial soil microorganisms involved in nutrient cycling. When applied to paddy soil, amino acids serve as organic substrates for soil microorganisms. Soil microorganisms, such as bacteria, fungi, and archaea, play crucial roles in the decomposition of organic matter. Upon deposition in the soil, amino acids are metabolized by microbial communities as a source of carbon (C), nitrogen (N), and energy. During microbial metabolism, amino acids undergo a process called mineralization, where the organic nitrogen (N) within the amino acids is converted into inorganic forms, such as ammonium (NH₄⁺). This process releases mineralized N into the soil solution, making it available for rice uptake in flooded paddy soils [47].

On the other hand, there are various types and dosages of fungicides and insecticides used in the experiment. Most of the pesticides such as fipronil, clothianidin, and cyantraniliprole for insecticides and orysastrobin, thifluzamide, and tiadinil for fungicides in T2 and T3 are commonly used domestically in Korean paddy fields, and the recommended amount was 10 kg ha⁻¹ for T2 and T3 (Table 2). T4 and T5 consist of these pesticides (cyantraniliprole, clothianidin, and orysastrobin) and thiamethoxam (THMX) and pymetrozine (PYME), the recommended amount is 3.6 L ha⁻¹. THMX is a small molecule (molecular weight 291) with a balanced lipophilicity/hydrophilicity (log Pow is −0.13) and an optimal water solubility (4100 mg L⁻¹ at 20 °C). It has a high availability in soils, rapid uptake by roots, and good distribution in plants. THMX uptake was compared with imidacloprid and clothianidin under normal humid soil conditions. Due to its optimal physicochemical properties, THMX is taken up and distributed more evenly in the plant as demonstrated by the greater amount. In addition, THMX’s optimal water solubility provides good uptake and translocation properties even under dry conditions. In seed care, THMX benefits from its lipophilicity (as measured by the log P or log Kow value), where it binds to organic matter in the soil. If the log P is greater than zero, the compound is attracted to organic matter. If the log P is less than zero, the compound is more soluble in water and is less attracted to organic matter. Mobility of the active compound is required in order to maintain a sufficient concentration in the root hair zone. Seed coatings with restricted mobility will form only a small zone around the seed, and uptake of the compound from this reservoir will cease over time as the roots and root hairs grow away from the concentrated zone. In contrast to those compounds, THMX is soluble enough to be translocated with and within the growing root [48]. PYME is a modulator in the TRPV channels of the chordotonal organs, which is systemically active through xylem transportation, allowing movement of PYME from the point of application to the outer edges or growing points of the plant leaf. Leaf uptake is moderate in comparison with other insecticides. There is no or little phloem movement, so downward movement in the plant or translocation to new leaves is not possible. However, redistribution of PYME can occur after a rain event, as demonstrated in the control of brown planthoppers in rice after PYME applications made to the upper parts of the plant are redistributed by rainfall. PYME is a small molecule (molecular weight 217.23) with hydrophilicity (log Pow is −0.19) and is slightly soluble in water (270 mg L⁻¹ at 20 °C) [48]. Although pesticides have various purposes and modes of action (Table S1), grain yield and number of particles per hill⁻¹, and filled spikelet were higher in T4 and T5. Meanwhile, a few studies suggest that the combined application of amino acids and pesticides can have synergistic effects on rice growth. Amino acids can act as biostimulants, promoting root development, nutrient uptake, and stress tolerance in plants. When applied in conjunction with pesticides, amino acids may enhance the efficacy of the pesticides by improving their absorption and translocation within the plant, thereby increasing pest control while supporting plant growth [49,50,51].

3.2. Effect of the Chemical Applications With/Without Amino Acids on CH₄ Emissions and GHGI

The CH₄ emissions over the rice growing periods are presented in Figure 3. The flux and its trend of CH₄ emissions were related to rice growing development and the water regime associated with air temperature. From transplanting to tillering stages (7 June to 7 August), CH₄ emissions had increased in all treatments and showed the highest peaks on 7 August. Increasing rice growth and air temperature can lead to increased CH₄ emissions during the rice growing stages. This is because more vigorous rice plants produce more root exudates and organic matter, which provide substrates for methanogenic archaea in the soil [52,53]. These microorganisms use the exudates and decaying plant material to produce CH₄ under anaerobic conditions typical of flooded rice paddies. Additionally, larger and more developed root systems enhance the transport of CH₄ from the soil to the atmosphere via the aerenchyma (air spaces) in the plant tissues. This accounts for about 90% of CH₄ emissions under submerged soil conditions. Although mid-season drainage on July 19 was implemented, the CH₄ emission still increased due to rainfall events and temperature. Additionally, Conant et al., (2008) [54] reported that concern in increasing air temperature accelerates the decomposition of organic substances in soils, thus stimulating methanogenic activities. The trend of CH₄ flux was attributed to soil water and temperature affected by the amount of rainfall and air temperature (Figure 3). On the other hand, the tendencies of T3 and T5 showed lower CH₄ emissions than the others. The application of the chemicals (T3 and T5) reduced cumulative CH₄ emissions during the entire rice-growing season, as compared to no chemical application (T1). Among the chemical treatments, T2 and T4 showed a similar amount of CH₄ emissions to T1 (Figure 4). Meanwhile, N₂O emissions were negligible in all treatments because the paddy field was flooded most of the growing season and it has high water solubility.

Among the chemicals used in our experiment, fipronil, clothianidin, cyantraniliprole, pymetrozine, and thiamethoxam seem to have no specific evidence for the reduction in methanogenesis in paddy soils since these control insects. Thifluzamide and tiadinil: T3, and ozysastrobin: T5, showed a reduction in CH₄ emissions in paddy rice since these are fungicides affecting the microbial communities in soils. We assumed that the reduction in CH₄ emissions from T3 and T5 was derived from the different application methods of the chemicals with/without amino acids. In the treatments, T4 and T5 as the GroMore^® program provide a rice seedling box drench application of a mixture of pesticides (insecticide, fungicide, and biostimulant) in water-soluble form 1 day before transplanting, while T2 and T3 are the conventional methods of farmers who evenly broadcast pesticides in granular form (mixture of fungicide and insecticide) on the seedling box 1 day before transplanting to prevent diseases and pests that occur from immediately after transplanting to before the heading stage of rice. The granule form of the chemicals (thifluzamide and tiadinil) in T3 may influence the reduction in CH₄ emissions because the chemicals may remain and affect methanogens in the soil. While T2, T4, and T5 treated with the same fungicide (ozysastrobin) showed different results in CH₄ emissions, the results seemed to be attributed to the amino acid. Amino acids including biostimulant components accelerate the early growth of rice, extending the tillering period, and increasing the number of panicles per plant [55]. When applied to paddy soil, amino acids serve as the organic substrates for soil microorganisms. We assumed that the release of organic compounds (root exudates) from the rice roots into the surrounding soil influences CH₄ emissions. These exudates provide substrates such as sugars, amino acids, and organic acids that are utilized by soil microbes, including methanogenic archaea. The presence of these substrates stimulates microbial activity, leading to increased production of intermediates like acetate and hydrogen, which are then converted to methane by methanogens under anaerobic conditions. The process significantly contributes to CH₄ emissions from paddy fields [56]. Meanwhile, T4 included with amino acids appeared to have an effect on increasing CH₄ emissions with the higher grain yield and number of panicles per plant because root exudates appeared to have decreased relatively as the carbon assimilation rate within the plant improved. However, T5 showed a reduction in CH₄ emissions in the experiment, although the same amount of chemicals was used with T4. Probably, further study is needed to clarify this difference.

To evaluate GHGI, this study considered the yield-scaled aggregate emission of CH₄ in the CO₂ equivalent. Our result showed that significantly lower GHGI values in T4 and T5 were observed because of higher grain yields and comparatively lower CH₄ emissions (Figure 5). Hughes et al., (2010) [57] reported that disease control reduced 15 to 20% of GHG emissions associated with higher crop yields.

3.3. PCA Analysis

PCA analysis was conducted to assess the effect of each treatment.

Table 3. Factor loading, eigenvalue, and cumulative proportion of PCA in each treatment.

Factor Loading	1st PC	2nd PC
Grain yield (kg ha−1)	0.937	0.011
Number of panicles per plant	0.797	0.159
Percentage filled spikelet (%)	0.999	0.001
Thousand-grain weight (g)	0.978	0.000
CH4 (kg ha−1)	0.251	0.743
Eigenvalue	3.96	1.0
Cumulative proportion	79.2	97.5

indicates eigenvalue, cumulative proportion, and 1st and 2nd PC for factor loading. For this analysis, grain yield, number of panicles per plant, percentage filled spikelet, thousand-grain weight, and CH₄ emissions were engaged, and the analysis result was significant because the eigenvalue was more than 1.0 for the 2nd PC, and 97.5% of information was explained with the 1st and 2nd PC. The 1st PC was interpreted as P since grain yield, number of panicles per plant, percentage filled spikelet, and thousand-grain weight were highly contributing factors. On the other hand, the 2nd PC was explained as GWP since CH₄ showed a high eigenvector. Figure 3 presents the scattered diagram of the PC scores, with P on the x-axis and GWP on the y-axis. The T5 is in the 4th quadrant, indicating a high contribution of both P and GWP, in contrast with T1 and T2. The T4 is in the 1st quadrant, indicating relatively high P and low GWP, which is in contrast with T3 showing high GWP, but relatively low P (Figure 6).

4. Conclusions

The intensively irrigated rice field increases GHG emissions, and contributes to elevated global average temperature. Additionally, the use of fertilizers and pesticides to increase crop yield and control disease in crop fields may cause global environmental effects. Thus, an appropriate practice of chemical application for sustaining rice productivity and reducing GHG emissions should be implemented in rice cultivation. In the experiment, GroMore^® programs (T4 and T5), which is a combined application method of pesticides and amino acids, avoid yield loss compared to T2 and T3, although it shortens the spraying time by 95% and uses 64% less pesticide amount than conventional practices (T2 and T3). In addition, the cumulative amount of GHG emissions in T4 and T5 showed similar and lower GHG emissions compared to T2 and T3 during the rice growing season. These results of the impact of GroMore^® programs on relatively lower GHGI values have herein been presented. However, in order to have sustainable and productive rice production, pesticide application needs to be performed at an appropriate rate through either synthetic or organic N fertilizers. Also, it is imperative to test an optimal practice for pesticides in future research to compromise the negative impact of agrochemical application in rice production.