Agriculture and Natural Resources

Phyllospheric bacteria isolated from broccoli (Brassica oleracea L. var. italica) as biocontrol agents against Ralstonia solanacearum and as plant growth promoting bacteria

2026-06-12T10:16:39+07:00

Importance of the work: Phyllospheric bacteria play a crucial role in shaping plant microenvironments
and offer sustainable alternatives to synthetic fertilizers and pesticides. The increasing environmental
concerns associated with agrochemicals highlight the need to explore plant growth-promoting
bacteria (PGPB) for enhancing crop productivity and disease resistance. One major phytopathogen,
Ralstonia solanacearum, causes bacterial wilt and greatly impacts a wide range of crops.
Objectives: 1) To characterize bacterial isolates from the broccoli phyllosphere; 2) to evaluate their
antagonistic activity against R. solanacearum; 3) to assess their plant growth-promoting traits; and
4) to identify the most promising isolate using 16S rRNA gene analysis.
Materials and Methods: Bacterial isolates were obtained from broccoli phyllosphere samples and
screened for antagonistic activity against R. solanacearum using the disc diffusion method. Plant
growth-promoting traits were evaluated based on nitrogen fixation, phosphate solubilization and
indole-3-acetic acid (IAA) production assays. Molecular identification of the selected isolate was
performed using 16S rRNA sequencing.
Results: In total, 10 bacterial isolates were obtained, among which isolate FB5 had the highest
antagonistic activity, with an inhibition zone diameter of 16.37 mm. FB5 tested negative for
nitrogen fixation but was positive for phosphate solubilization and IAA production. Molecular
identification revealed 91.43% similarity to Bacillus velezensis, indicating that the isolate belonged
to the genus Bacillus.
Main finding: Bacillus sp. FB5 had strong antagonistic activity against R. solanacearum and
displayed key plant growth-promoting traits, highlighting its potential as a biocontrol agent and
biofertilizer for Solanaceae crops such as potato, tomato and chili.

Dietary effect of Xylopia aethiopica supplementation on growth performance, hematology, serum biochemistry and tissue histology in African catfish hybrids (Clarias gariepinus ♀ × Heterobranchus bidorsalis ♂)

2026-06-12T10:23:10+07:00

Importance of the work: The incorporation of medicinal plants as natural feed additives is
recognized increasingly as essential for improving productivity and profitability in catfish
aquaculture.
Objectives: To evaluate the effects of dietary Xylopia aethiopica (Dunal) A. Rich. on growth
performance, health indices, tissue histology and economic returns in hybrid catfish.
Materials and Methods: Hybrid catfish fingerlings with an initial mean weight of 15.95 ± 0.01 g
were fed diets containing 0 to 2.0% X. aethiopica (XE) for 56 d and assessed for growth
performance, hematological parameters, serum biochemistry, enzyme activities, histological
alterations and profitability.
Results: Growth parameters differed significantly (p < 0.05), with 0.5% XE producing
the highest final weight, weight gain, specific growth rate and feed efficiency. Conversely,
2.0% XE significantly (p < 0.05) reduced performance. Hematological indices (red and white
blood cell counts, hemoglobin and packed cell volume) improved at 0.5% XE (p < 0.05).
Based on serum biochemical markers, there were increased protein and globulin levels,
reduced cortisol and glucose and enhanced hepatic and renal function at 0.5–1.0% XE. Plasma
electrolytes remained stable at moderate XE inclusion but were significantly (p < 0.05)
altered at 2.0% XE. Histological examination revealed minimal hepatic and renal changes at
0.5–1.0% XE, while 2.0% XE caused vacuolation and inflammation. Economic analysis
indicated that 0.5% XE achieved the highest profit index and gross margin (p < 0.05).
Main finding: Moderate supplementation of X. aethiopica at 0.5–1.0% enhanced growth, health
and profitability in hybrid catfish culture, while excessive inclusion at 2.0% had adverse effects.

ackfruit (Artocarpus heterophyllus Lam.) waste extracts as rich source of flavonoids with potential antioxidant and α-glucosidase inhibitory activities

2026-06-12T10:33:13+07:00

Importance of the work: Agricultural waste from the food industry presents a serious disposal
challenge, yet it can serve as a valuable source of bioactive compounds. Jackfruit (Artocarpus
heterophyllus Lam.) waste, often discarded, has potential to be repurposed into high-value products
for food and pharmaceutical applications.
Objectives: To investigate the antioxidant and α-glucosidase inhibitory activities of jackfruit waste
extracts and to identify their metabolite composition using liquid chromatography combined with
tandem mass spectrometry (LC-MS/MS).
Materials and Methods: Jackfruit waste was extracted using different ethanol concentrations
and the extracts were evaluated for total phenolic content (TPC), 2,2-diphenyl-1-picrylhydrazyl
(DPPH) radical scavenging activity, nitric oxide radical inhibition and α-glucosidase inhibitory
activity. Then, the most active extract was analyzed further using LC-MS/MS coupled with
a spectral library search through Global Natural Products Social Molecular Networking for
compound identification.
Results: The 50% ethanolic extract had the highest TPC (mean ± SD, 73.76±2.19 mg gallic acid
equivalents per gram of extract), with strong bioactivities, including DPPH radical scavenging
(concentration of sample required to scavenge 50% of the DPPH free radicals = 85.83±3.14
µg/mL), nitric oxide radical inhibition (37.49±1.83% at 250 µg/mL) and potent α-glucosidase
inhibition (half maximal inhibitory concentration = 3.75±0.15 µg/mL). The LC-MS/MS analysis
identified 28 compounds, including 12 flavonoids with documented biological activities.
Main finding: Jackfruit waste is a rich source of natural antioxidants and α-glucosidase inhibitors,
which collectively highlight their prospective applications in food and pharmaceutical industries
and contribute to the sustainable valorization of agro-industrial waste streams.

Molecular diversity and phylogenetic relationship of native Garcinia (mangosteen and relatives) from Kalimantan, Indonesia

2026-06-12T10:43:10+07:00

Importance of the work: Globally, Indonesia is one of the biggest producers of
mangosteen (Garcinia mangostana L.), known as the “queen of fruits”.
Objectives: To determine the molecular diversity and phylogenetic relationship of
mangosteen and its wild relatives (Garcinia spp.), native to Kalimantan, Indonesia, using
the matK and rbcL markers and to compare these to other data in the GenBank database.
Materials and Methods: In total, 34 Garcinia samples were used, with 12 originating
from Kalimantan, Indonesia. Molecular analysis began with DNA isolation using a CTAB
method, with a soft modification. Next, the DNA isolates were quantified and amplified
using an ultraviolet-visible spectrum spectrophotometer and a thermal cycler to perform
polymerase chain reaction. The DNA targets (matK and rbcL) were sequenced using the
ABI PRISM 377 sequencer at Apical Scientific Sdn. Bhd. (Seri Kembangan, Selangor,
Malaysia). The molecular diversity was assessed using the nucleotide diversity index (π),
while the molecular phylogeny was determined based on maximum likelihood analysis
with a statistical bootstrap.
Results: Molecular analysis revealed that Garcinia had high molecular diversity,
as indicated by π values of 0.062 for matK and 0.083 for rbcL. The phylogenetic analysis,
based on the combination of the matK and rbcL markers, revealed that this germplasm
could be divided into three (local scale) and six groups (global scale), with G. mangostana
being closely related to G. parvifolia, G. latissima, and G. dulcis.
Main finding: This essential information could be used to enhance the future efficiency
and effectiveness of the mangosteen breeding and conservation program.

Integrated assessment of climate change and land use impacts on multicrop vulnerability in Mun River Basin, northeast Thailand

2026-06-12T10:47:31+07:00

Importance of the work: The quantification of climate and land use change effects on
multi-crop systems can inform strategic agricultural adaptation.
Objectives: To evaluate the combined effects of climate (CMIP5/CMIP6) and land use
change (LUC) on multi-crop economic output and to determine spatial susceptibility
across the Mun River Basin, northeast Thailand.
Materials and Methods: The decision support system for agrotechnology transfer
(DSSAT) model and the land-similarity-unit technique were applied to assess four major
cash crops: rice, maize, cassava and sugarcane. Land use was projected using a cellular
automata-Markov chain model. Economic effects were quantified across four scenarios:
baseline, climate change (CC)-only, LUC-only and integrated CC & LUC.
Results: The CC-only scenario caused an 8.9% reduction in total output. Rice and maize
had very unstable yields (coefficient of variance up to 43.0%). The LUC-only scenario
increased output by 4.5%, driven by converting rice paddies to higher-value crops.
The integrated effect resulted in a net reduction of 4.4%. District-level analysis revealed
non-uniform responses: uplands experienced output increases (+22.2% in Sangkha),
reflecting successful adaptation, whereas lowlands showed aggravated losses (-15.0%
in Kaset Wisai).
Main finding: Strategic land use adaptation can offset economic losses from climate
change. Spatial targeting is critical and vulnerability remains high in rainfed lowlands
where crop conversion is unsuitable.

Machine learning based sugar recovery prediction model in sugarcane agroindustry

2026-06-16T09:39:43+07:00

Importance of the work: Sugar recovery is crucial for mill efficiency. In Indonesia,
recovery rates declined by 1.91% from 2019 to 2023, hitting a decade low of 6.6% in 2022.
These fluctuations indicate inefficiencies. This work introduced a machine learning-based
model for early prediction and process optimization to achieve better production planning.
Objectives: To develop a model for predicting final sugar recovery with machine learning,
using a multistage process and related variables in processing terms.
Materials and Methods: Day-to-day data from Sugar Mill XYZ (2020–2024) in West Java,
Indonesia were used, including Brix, purity and pol values from multiple processing stages.
Random forest, extreme gradient boosting (XGBoost) and artificial neural network (ANN)
methods were used to develop a model and its evaluation using mean squared error (MSE)
and mean absolute error (MAE). mean absolute percentage error (MAPE), coefficient of
determination (R²) and feature importance analysis.
Results: The model was developed using 699 daily milling records from 2020–2024,
comprising 18 initial features. XGBoost outperformed random forest and ANN, achieving an
MAE of 0.116, MSE of 0.03852, MAPE of 1.81% and a coefficient of determination (R²) of
86.84% on the testing set. Feature significance analysis, which combines machine learning
insights with empirical plant data, identified the key variables that had the greatest impact on
sugar recovery, such as boiling house recovery, winter recovery, Pol in cane, milling potential
efficiency and Pol in bagasse. The model correctly predicted the daily sugar recovery for
production in 2024.
Main finding: This work provides a decision-support tool for sugar mill optimization.
It illustrates how well XGBoost and random search optimization work together to predict
sugar recovery depending on process variables.

Time-ordered empirical framework for forecasting climate-driven oil palm yield in southern Thailand

2026-06-12T11:05:14+07:00

Importance of the work: Oil palm yield in southern Thailand is strongly sensitive to
climatic variations; however, robust intra-annual forecasting frameworks are largely absent.
Objectives: To quantify lagged climate-yield relationships and to build province-scale
empirical models for reliable intra-annual yield forecasting.
Materials and Methods: Monthly yield data were compiled for 13 southern provinces
(2005–2022) to derive province-averaged reanalysis climate variables with lag adjustments.
Collinearity was reduced using variance inflation factor analysis and models were trained
through exhaustive search with expanding-window cross-validation.
Results: Robust models with 2–8 predictors were produced for 11 provinces. Across test
splits, the ranges were: coefficient of determination (R2
), 0.33–0.73; root mean square
error, 0.14–0.30 t/ha; coefficient of variation of the root mean square error, 8.38–23.75 %;
and mean bias error, within ±0.13 t/ha. Dew-point temperature, soil moisture at 1.6 m
and precipitation dominated the selected predictors, with common lags near 3 mth and
21 mth. Forecast lead time spanned 3–20 mth, most often 6–11 mth ahead of harvest.
The lowest errors occurred in Nakhon Si Thammarat and Surat Thani provinces, while
southernmost provinces had higher relative errors. Partial-R² attribution highlighted
mid-season soil moisture (often a 7 mth lag) as the most influential predictor in 7 of the
11 provinces.
Main finding: A time-ordered empirical framework successfully forecast province-scale oil
palm yields several months in advance using reanalysis climate and soil-moisture predictors.
The results could support operational early warning for mills and agencies, while also
clarifying the lagged climatic controls that shape yield variability in southern Thailand.

Nutritional composition and cannabinoid concentrations of hemp leaf hay during 5 mth of storage

2026-06-12T11:13:52+07:00

Importance of the work: The leaves of hemp (Cannabis sativa L.) obtained as a by-product after
fiber harvest represent a potential conserved-feed ingredient for ruminants; however, information
remains limited on the changes in nutritive value and cannabinoid profiles during hay storage.
Objectives: To assess the nutritional value and cannabinoid content of hemp leaf hay during
different storage durations compared to leucaena.
Materials and Methods: Hemp leaves and leucaena leaves were harvested, sun-dried and stored
for 0, 1, 2, 3, 4 and 5 mth. Proximate composition and fiber fractions were analyzed using standard
methods, while cannabinoids were quantified using high-performance liquid chromatography with
ultraviolet detection.
Results: Initially, the hemp leaf hay contained 23.89% crude protein (CP), which declined
significantly to 10.06% after 5 mth of storage. In contrast, the detergent fiber fractions and ash
content remained statistically unchanged over storage (neutral detergent fiber, 42.97%; ash,
12.46%). Total cannabidiol (CBD) and total Δ9
-tetrahydrocannabinol (Δ9
-THC) did not change
significantly across storage durations, although slight numerical increases were observed, whereas
cannabinol (CBN) increased significantly (2.05–2.20 mg/g at month 3), consistent with oxidative
conversion of THC to CBN under ambient storage. Compared with leucaena, the hemp leaves had
lower CP and total fiber contents but higher levels of hemicellulose and ash. Correlation analysis
showed that CBD was strongly correlated with CBN, while Δ9
-THC was significantly correlated
with CBN, suggesting possible co-variation among major cannabinoids during storage.
Main finding: The hemp leaf hay maintained statistically unchanged total CBD and total THC
contents during 1–5 mth of storage, despite slight numerical increases, whereas CBN increased
and CP declined markedly. Therefore, early utilization of the hay is recommended to preserve
protein value. Hemp leaf hay may be used as a complementary feed ingredient for ruminants under
farm-like storage conditions.

Evaluating compatibility of Trichoderma asperellum with dimethomorph and fluazinam for integrated disease management in durian

2026-06-16T09:43:09+07:00

Importance of the work: Fungicide-biocontrol compatibility for sustainable durian
disease management remains underexplored.
Objectives: To evaluate the compatibility of Trichoderma asperellum with dimethomorph
and fluazinam for sustainable durian disease management.
Materials and Methods: Pathogens from diseased durian tissues were identified
morphologically and molecularly. Five Trichoderma isolates were screened; Tri-1 was
confirmed as T. asperellum. Dual culture, poisoned food and soil assays were used to
assess antagonistic activity and survival under fungicide treatments.
Results: Four pathogens (Phytophthora palmivora, Fusarium solani, Lasiodiplodia
theobromae, Phomopsis sp.) were isolated. Tri-1 achieved the highest inhibition
(up to 86.17% against Phomopsis sp.). Dimethomorph had no inhibitory effect on
T. asperellum, while fluazinam suppressed growth by up to 55.13%. In dual culture,
dimethomorph + Trichoderma achieved 90–100% pathogen inhibition, whereas fluazinam
reduced Trichoderma viability. Based on the soil assay results, the microbial population
was stable when dimethomorph was used (2.93 × 10³ colony-forming units (CFU)/g
soil–3.67 × 10³ CFU/g soil at 60 d), while it dropped sharply when fluazinam was used
(0.12 × 10³ CFU/g soil).
Main finding: Trichoderma asperellum was compatible with dimethomorph but was
inhibited by fluazinam, which should be useful information in guiding fungicide selection
for integrated durian disease management.

Role of Rhizobium inoculation and mycorrhizal fungi in enhancing growth of soybean seedlings in sterilized gypsum soil fertilized with phosphorus

2026-06-16T09:49:23+07:00

Importance of the work: Soybean production in sterile gypsum soils is constrained by
low fertility and poor nutrient availability, particularly of nitrogen and phosphorus, which
are essential for plant growth. Although biological inoculants, such as Bradyrhizobium
japonicum Kirchnerand Glomus mosseae T.H. Nicolson & Gerd, are known to improve
nitrogen fixation and phosphorus uptake, there is insufficient understanding of their
combined effects under gypsum soil conditions, especially in relation to phosphate
fertilization.
Objectives: To assess the impact of Rhizobium, mycorrhizal fungi and phosphorus
fertilization on soybean growth in sterilized gypsum soil.
Materials and Methods: A field experiment was conducted using a 4 × 2 × 2 factorial
arrangement in a randomized complete block design with three replications.
The experimental factors consisted of phosphorus applied at four levels (0 kg/ha (control),
80 kg/ha, 160 kg/ha, 240 kg/ha), two rhizobial treatments (with and without B. japonicum
inoculation) and two mycorrhizal treatments (with and without G. mosseae inoculation).
Results: The analysis of variance revealed significant 3-way interaction effects for
all measured traits. Single inoculation with Rhizobium or mycorrhiza and phosphorus
application significantly increased plant height (up to 71.13 cm/plant), vegetative dry weight
(up to 3.22 g/plant) and root dry weight (up to 0.58 g/plant). Co-inoculation enhanced
phosphorus concentration in the vegetative part (up to 0.63%). Mycorrhizal infection rates
reached 67.33%. Phosphorus application and biofertilizer co-inoculation significantly
improved all growth parameters and symbiotic efficiency in early soybean development.
Main finding: The triple interaction of Rhizobium, mycorrhizal fungi and phosphorus
fertilizer significantly boosted soybean early growth, offering a sustainable strategy for
improving productivity in nutrient-poor soils.

Feeding effect of complete pellets with inclusions of Sesbania grandiflora leaf on feed intake, growth performance, digestibility and meat quality of growing rabbits

2026-06-16T09:52:47+07:00

Importance of the work: Sesbania grandiflora leaf could reduce dependence on
imported protein feed ingredients in rabbit production systems in Malaysia.
Objectives: To evaluate the effects of dietary S. grandiflora leaf inclusion on rabbit
growth, digestibility, carcass composition and meat quality.
Materials and Methods: A completely randomized design was used to assign 15 male
rabbits, aged approximately 2 mth after weaning, to three dietary treatments containing
0% (T1), 5% (T2) or 10% (T3) S. grandiflora (L.) Poir. leaves. The rabbits were
fed ad libitum for 62 d, including a digestibility trial for 7 d. Carcass composition and
meat quality were evaluated after slaughtering.
Results: The rabbits fed the T2 diet had higher dry matter, crude fiber (CF) and ether
extract intake than the rabbits fed the T1 diet. CF digestibility was significantly higher
in the rabbits fed the T3 diet compared with the rabbits fed the T1 and T2 diets, while no
significant difference was observed between T1 and T2. Ash digestibility was higher in
the rabbits fed the T2 and T3 diets than in the rabbits fed the T1 diet. Growth performance
was improved in the rabbits fed the T2 diet, with higher total body weight gain (BWG)
and daily BWG. Carcass composition and meat quality were not significantly affected,
although the meat ash content was higher in the rabbits fed the T2 diet.
Main finding: Inclusion of 5–10% S. grandiflora leaves in the rabbit diets partially
replaced imported feed ingredients without adversely affecting growth performance,
nutrient digestibility, carcass composition or meat quality

Cocoa pod biochar improves yield performance of brinjal (Solanum melongena L.) in a controlled pot experiment

2026-06-12T11:20:44+07:00

Importance of the work: Assessment of the impact of underutilized cocoa pod biochar
on brinjal (Solanum melongena L.) yield in soil addresses both waste valorization and
productivity gaps.
Objectives: To evaluate the effects of cocoa pod biochar on the morphological traits and yield
performance of brinjal cultivated in soil.
Materials and Methods: Brinjal plants were grown in polybags filled with soil amended with
cocoa pod biochar at different rates in six treatments: 0 g (T0, the control); 20 g (T1); 40 g
(T2); 60 g (T3); 80 g (T4); and 100 g (T5) per polybag. A randomized complete block design
was used with five replications. The measured parameters were: plant height, leaf number,
SPAD value, root and shoot biomass, fruit count, fruit weight and total yield. Results were
reported as mean ± SD values.
Results: Only leaf number showed a significant (p < 0.01) morphological response to
biochar, with the highest value (46.4 ± 5.13 leaves) in T3 (60 g). Yield attributes were
highly significantly (p < 0.001) affected. Treatment T2 (40 g) recorded the highest yield
(3576.2 ± 640.09 g per plant) and the highest fruit count (19.4 ± 3.85). The control
produced the lowest yield and fruit number (633.1 ± 540.93 g and 6.0 ± 4.70, respectively).
These findings highlighted the positive impact of moderate biochar application on brinjal yield
performance.
Main finding: Cocoa pod biochar at 40 g per plant or 60 g per plant improved brinjal yield
and growth in soil, demonstrating its effectiveness as a sustainable amendment. This finding
supports waste valorization and advances soil cultivation practices for enhanced brinjal
productivity.

Simulation spatial model for analyzing cooling effects of downwash turbulence on maize canopies to enhance pollination efficiency using thermal imaging data collected from unmanned aerial vehicles

2026-06-16T10:00:56+07:00

Importance of the work: Maize pollination is sensitive to canopy microclimate, including temperature, humidity, and airflow. UAV-assisted pollination may improve pollen dispersal; however, the effects of UAV-induced downwash turbulence on canopy cooling and pollen movement remain unclear.

Objectives: To develop a simulation model to analyze the cooling effects of UAV-induced downwash turbulence on maize canopies, using thermal imaging to optimize pollination efficiency.

Materials and Methods: Advanced techniques (the lattice Boltzmann method (LBM) and finite-difference time-domain (FDTD) simulations) were used to evaluate the impact of UAV airflow on canopy temperature and pollen dispersion during sensitive pollination stages. Data from UAVs equipped with thermal cameras (DJI Matrice 300 RTK and Zenmuse H20T) were combined with global navigation satellite systems to capture spatial variations in land surface temperature and airflow patterns.

Results: UAV-induced turbulence reduced canopy temperature and humidity, enhancing pollination success, while cooling the surrounding soil and vegetation.

Main finding: These findings highlight the importance of UAV airflow management in precision agriculture, demonstrating its potential to improve crop health and pollination outcomes through advanced environmental monitoring and control.

Impacts of climate warming and carbon intensity on rice yield: Implications for adaptation strategies in the Mekong Delta, Vietnam

2026-06-12T11:29:23+07:00

Importance of the work: Rice yield response to warming exhibits non-linear threshold
behavior dependent on rhizosphere biogeochemical status.
Objectives: To identify thermal tipping points and quantify carbon intensity (CI)
moderation of temperature-yield relationships.
Materials and Methods: A balanced panel dataset (1995−2024, n = 180) across six
Mekong Delta provinces was analyzed using data envelopment analysis and Hansen’s
threshold model, with temperature data from the Ca Mau hydrological station and
emission factors from the Intergovernmental Panel on Climate Change guidelines.
Results: A statistically significant threshold was identified at γ = 27.5°C (95% confidence
interval: 27.3−27.7°C, p < 0.01). Below this threshold, each 1°C increase raised yields
by 0.18 t/ha, whereas above it for each 1°C, yields declined by 0.24 t/ha. Systems with
CI >1.2 kg CO2e/kg had 35% greater yield volatility and 82% larger thermal penalties at
supra-threshold temperatures than low-carbon systems.
Main finding: This study provided the first regional-scale, panel-based quantification of
a 27.5°C thermal tipping point governing rice yield in the Mekong Delta, demonstrating
that CI functions as a biophysical stress multiplier. Specifically, high-emission systems
(CI >1.2 kg CO2e/kg) suffer 50% larger thermal yield penalties above the threshold
than their low-emission counterparts. Achieving CI <1.0 kg CO2e/kg (as mandated
by Decision No. 1490/QD-TTg by the Prime minister of Vietnam) confers the dual
co-benefits of a reduction in CH4 and N2O emissions, as well as enhanced thermal
resilience, providing a biophysical basis for differentiated provincial adaptation strategies
under National Assembly of Vietnam Resolution No. 202/2025/QH15.

Soil methane dynamics: Microbial mechanisms and agricultural management strategies

2026-06-12T10:54:38+07:00

Importance of the work: Soil methane (CH4) dynamics remain poorly addressed in terms
of microbial interactions and integrated mitigation strategies under agricultural management.
Objectives: To review soil microbial mechanisms of CH4 production/consumption and to
evaluate how management strategies influence CH4 emissions.
Materials and Methods: A narrative literature review was conducted using scientific
databases (Web of Science, Scopus, Google Scholar) and tools such as Connected Papers.
Studies were synthesized on methanogenic/methanotrophic microorganisms, biofertilizer
applications and management interventions (such as water and fertilizer regimes) across
agroecosystems.
Results: CH4 production in soil is driven by anaerobic methanogenic archaea, while aerobic
methanotrophic bacteria consume CH4. This balance is strongly regulated by environmental
factors, such as soil moisture, redox potential and substrate availability. Alternate wetting and
drying practices have reduced CH4 emissions by 30–70%, while ammonium-based fertilizers
may suppress methanotrophy. Inoculation with methanotrophs and co-inoculation with plant
growth-promoting rhizobacterial strains have produced emission reductions up to 68%.
In addition, Azolla-cyanobacteria systems decrease emissions by increasing soil redox
potential and O2 availability. However, interactions among practices (such as fertilization ×
water regime) are complex and many single-factor interventions fail under field conditions.
It is essential for consistent mitigation outcomes to maintain microbial diversity and to
understand these synergistic/antagonistic effects.
Main finding: Integrated, site-specific strategies, combining microbial agents with optimized
water and fertilizer management, enhance CH4 oxidation and suppress production. Holistic,
microbiome-informed interventions are critical for effective and sustainable greenhouse gas
mitigation in agriculture