Crops for Carbon Farming

Microbial community structure and carbon transformation characteristics of different aggregates in black soil

Background

Previous research on whole-soil measurements has failed to explain the spatial distribution of soil carbon transformations, which is essential for a precise understanding of the microorganisms responsible for carbon transformations. The microorganisms involved in the transformation of soil carbon were investigated at the microscopic scale by combining 16S rDNA sequencing technology with particle-level soil classification.

Methods

In this experiment,16S rDNA sequencing analysis was used to evaluate the variations in the microbial community structure of different aggregates in no-tillage black soil. The prokaryotic microorganisms involved in carbon transformation were measured before and after the freezing and thawing of various aggregates in no-tillage black soil. Each sample was divided into six categories based on aggregate grain size: >5, 2-5, 1-2, 0.5-1, 0.25-0.5, <0.25 mm, and bulk soil.

Results

The relative abundance of Actinobacteria phylum in <0.25 mm aggregates was significantly higher compared to that in other aggregates. The Chao1 index, Shannon index, and phylogenetic diversity (PD) whole tree index of <0.25 mm aggregates were significantly smaller than those of in bulk soil and >5 mm aggregates. Orthogonal partial least-squares discrimination analysis showed that the microbial community composition of black soil aggregates was significantly different between <1 and >1 mm. The redundancy analysis (RDA) showed that the organic carbon conversion rate of 0.25-0.5 mm agglomerates had a significantly greater effect on their bacterial community structure. Moreover, humic acid conversion rates on aggregates <0.5 mm had a greater impact on community structure. The linear discriminant analysis effect size (LEfSe) analysis and RDA analysis were combined. Bradyrhizobium, Actinoplane, Streptomyces, Dactylosporangium, Yonghaparkia, Fleivirga, and Xiangella in <0.25 mm aggregates were positively correlated with soil organic carbon conversion rates. Blastococcus and Pseudarthrobacter were positively correlated with soil organic carbon conversion rates in 0.25-0.5 mm aggregates. In aggregates smaller than 1 mm, the higher the abundance of functional bacteria that contributed to the soil's ability to fix carbon and nitrogen.

Discussion

There were large differences in prokaryotic microbial community composition between <1 and >1 mm aggregates. The <1 mm aggregates play an important role in soil carbon transformation and carbon fixation. The 0.25-0.5 mm aggregates had the fastest organic carbon conversion rate and increased significantly more than the other aggregates. Some genus or species of Actinobacteria and Proteobacteria play a positive role in the carbon transformation of <1 mm aggregates. Such analyses may help to identify microbial partners that play an important role in carbon transformation at the micro scale of no-till black soils.

Evaluation of net carbon sequestration and ecological benefits from single biochar-incorporated sorghum farmland systems in saline-alkali areas of Inner Mongolia, China

Biochar is widely recognized as a soil amendment to reduce greenhouse gas emissions and enhance soil carbon storage in agroecosystems; however, the systematic focus on carbon balance and ecological benefits in cropping systems remains unclear in saline-alkali areas under water-saving irrigation. Here, a 2-yr field experiment with carbon footprint method was conducted to determine soil carbon budgets, biochar carbon efficiency performance, and the economic and ecological benefits of mulched drip-irrigated sorghum production, in an arid salinized region of Inner Mongolia, China. Corn straw-derived biochar dosages of 0 (CK), 15 (B15), 30 (B30), and 45 (B45) t hm-2 were just applied into the soil in the first crop growing season. A single application of biochar to soil significantly reduced CO2 emissions for the current and subsequent crop-growing seasons, with 13.1%, 16.7%, and 12.5% reductions for B15, B30, and B45, respectively. Compared with the non-biochar control plots, B15, B30, and B45 also increased NPP by 36.7%, 38.4%, and 27.1%, respectively. The actual effects on improving net carbon sequestration for B15, B30, and B45 in the first year were higher than those in the second year, with mean increases of 1.27, 1.47, and 1.36 times, respectively; however, the efficiencies of biochar for fixing carbon per biochar dosage input for B15 were 72.8% and 64.1% higher than those of B30 and B45, respectively. Net profits were significantly improved by 57.2-87.1% by biochar treatments. The environmental benefits of biochar carbon trading revenues for B15, B30, and B45 increased by 105.9%, 162.1%, and 109.6%, respectively. The minimum observation for carbon productivity and the maximum measurements for both the economic and ecological benefits were B15. The B15 also significantly increased sorghum yield and grain number. Results demonstrate that biochar application in the current growing season helps reduce soil carbon emissions, increases net carbon sequestration for current and subsequent sorghum agroecosystems, and enhances net profit and ecological benefits. The optimal positive synergistic effect was observed at a biochar application rate of 15 t hm-2 for reducing soil carbon emissions, increasing crop production, and improving the ecological environment.

Photosynthesis 2.0: Realizing New-to-Nature CO2-Fixation to Overcome the Limits of Natural Metabolism

Synthetic biology provides opportunities to realize new-to-nature CO2-fixation metabolisms to overcome the limitations of natural photosynthesis. Two different strategies are currently being pursued: One is to realize engineered plants that feature carbon-neutral or carbon-negative (i.e., CO2-fixing) photorespiration metabolism, such as the tatronyl-CoA (TaCo) pathway, to boost CO2-uptake rates of photosynthesis between 20% and 60%. Another (arguably more radical) is to create engineered plants in which natural photosynthesis is fully replaced by an alternative CO2-fixation metabolism, such as the CETCH cycle, which carries the potential to improve CO2 uptake rates between 20% and 200%. These efforts could revolutionize plant engineering by expanding the capabilities of plant metabolism beyond the constraints of natural evolution to create highly improved crops addressing the challenges of climate change in the future.

A plant's perception of growth-promoting bacteria and their metabolites

Many recent studies have highlighted the importance of plant growth-promoting (rhizo)bacteria (PGPR) in supporting plant's development, particularly under biotic and abiotic stress. Most focus on the plant growth-promoting traits of selected strains and the latter's effect on plant biomass, root architecture, leaf area, and specific metabolite accumulation. Regarding energy balance, plant growth is the outcome of an input (photosynthesis) and several outputs (i.e., respiration, exudation, shedding, and herbivory), frequently neglected in classical studies on PGPR-plant interaction. Here, we discuss the primary evidence underlying the modifications triggered by PGPR and their metabolites on the plant ecophysiology. We propose to detect PGPR-induced variations in the photosynthetic activity using leaf gas exchange and recommend setting up the correct timing for monitoring plant responses according to the specific objectives of the experiment. This research identifies the challenges and tries to provide future directions to scientists working on PGPR-plant interactions to exploit the potential of microorganisms' application in improving plant value.

Unleashing the sequestration potential of soil organic carbon under climate and land use change scenarios in Danish agroecosystems

Future global climate changes are expected to increase soil organic carbon (SOC) decomposition. However, the combined effect of C inputs, land use changes, and climate on SOC turnover is still unclear. Exploring this SOC-climate-land use interaction allows us to understand the SOC stabilization mechanisms and examine whether the soil can act as a source or a sink for CO2. The current study estimates the SOC sequestration potential in the topsoil layer of Danish agricultural lands by 2038, considering the effect of land use change and future climate scenarios using the Rothamsted Carbon (RothC) model. Additionally, we quantified the loss vulnerability of existing and projected SOC based on the soil capacity to stabilize OC. We used the quantile random forest model to estimate the initial SOC stock by 2018, and we simulated the SOC sequestration potential with RothC for a business-as-usual (BAU) scenario and a crop rotation change (LUC) scenario under climate change conditions by 2038. We compared the projected SOC stocks with the carbon saturation deficit. The initial SOC stock ranged from 10 to 181 Mg C ha-1 in different parts of the country. The projections showed a SOC loss of 8.1 Mg C ha-1 for the BAU scenario and 6 Mg C ha-1 after the LUC adoption. This SOC loss was strongly influenced by warmer temperatures and clay content. The proposed crop rotation became a mitigation measure against the negative effect of climate change on SOC accumulation, especially in sandy soils with a high livestock density. A high C accumulation in C-saturated soils suggests an increase in non-complexed SOC, which is vulnerable to being lost into the atmosphere as CO2. With these results, we provide information to prioritize areas where different soil management practices can be adopted to enhance SOC sequestration in stable forms and preserve the labile-existing SOC stocks.

Role of Arbuscular Mycorrhizal Fungi in Regulating Growth, Enhancing Productivity, and Potentially Influencing Ecosystems under Abiotic and Biotic Stresses

Arbuscular mycorrhizal fungi (AMF) form symbiotic relationships with the roots of nearly all land-dwelling plants, increasing growth and productivity, especially during abiotic stress. AMF improves plant development by improving nutrient acquisition, such as phosphorus, water, and mineral uptake. AMF improves plant tolerance and resilience to abiotic stressors such as drought, salt, and heavy metal toxicity. These benefits come from the arbuscular mycorrhizal interface, which lets fungal and plant partners exchange nutrients, signalling molecules, and protective chemical compounds. Plants' antioxidant defence systems, osmotic adjustment, and hormone regulation are also affected by AMF infestation. These responses promote plant performance, photosynthetic efficiency, and biomass production in abiotic stress conditions. As a result of its positive effects on soil structure, nutrient cycling, and carbon sequestration, AMF contributes to the maintenance of resilient ecosystems. The effects of AMFs on plant growth and ecological stability are species- and environment-specific. AMF's growth-regulating, productivity-enhancing role in abiotic stress alleviation under abiotic stress is reviewed. More research is needed to understand the molecular mechanisms that drive AMF-plant interactions and their responses to abiotic stresses. AMF triggers plants' morphological, physiological, and molecular responses to abiotic stress. Water and nutrient acquisition, plant development, and abiotic stress tolerance are improved by arbuscular mycorrhizal symbiosis. In plants, AMF colonization modulates antioxidant defense mechanisms, osmotic adjustment, and hormonal regulation. These responses promote plant performance, photosynthetic efficiency, and biomass production in abiotic stress circumstances. AMF-mediated effects are also enhanced by essential oils (EOs), superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX), hydrogen peroxide (H2O2), malondialdehyde (MDA), and phosphorus (P). Understanding how AMF increases plant adaptation and reduces abiotic stress will help sustain agriculture, ecosystem management, and climate change mitigation. Arbuscular mycorrhizal fungi (AMF) have gained prominence in agriculture due to their multifaceted roles in promoting plant health and productivity. This review delves into how AMF influences plant growth and nutrient absorption, especially under challenging environmental conditions. We further explore the extent to which AMF bolsters plant resilience and growth during stress.

Ensemble machine learning-based recommendation system for effective prediction of suitable agricultural crop cultivation

Agriculture is the most critical sector for food supply on the earth, and it is also responsible for supplying raw materials for other industrial productions. Currently, the growth in agricultural production is not sufficient to keep up with the growing population, which may result in a food shortfall for the world's inhabitants. As a result, increasing food production is crucial for developing nations with limited land and resources. It is essential to select a suitable crop for a specific region to increase its production rate. Effective crop production forecasting in that area based on historical data, including environmental and cultivation areas, and crop production amount, is required. However, the data for such forecasting are not publicly available. As such, in this paper, we take a case study of a developing country, Bangladesh, whose economy relies on agriculture. We first gather and preprocess the data from the relevant research institutions of Bangladesh and then propose an ensemble machine learning approach, called K-nearest Neighbor Random Forest Ridge Regression (KRR), to effectively predict the production of the major crops (three different kinds of rice, potato, and wheat). KRR is designed after investigating five existing traditional machine learning (Support Vector Regression, Naïve Bayes, and Ridge Regression) and ensemble learning (Random Forest and CatBoost) algorithms. We consider four classical evaluation metrics, i.e., mean absolute error, mean square error (MSE), root MSE, and R 2, to evaluate the performance of the proposed KRR over the other machine learning models. It shows 0.009 MSE, 99% R 2 for Aus; 0.92 MSE, 90% R 2 for Aman; 0.246 MSE, 99% R 2 for Boro; 0.062 MSE, 99% R 2 for wheat; and 0.016 MSE, 99% R 2 for potato production prediction. The Diebold-Mariano test is conducted to check the robustness of the proposed ensemble model, KRR. In most cases, it shows 1% and 5% significance compared to the benchmark ML models. Lastly, we design a recommender system that suggests suitable crops for a specific land area for cultivation in the next season. We believe that the proposed paradigm will help the farmers and personnel in the agricultural sector leverage proper crop cultivation and production.

PlantACT! - how to tackle the climate crisis

Greenhouse gas (GHG) emissions have created a global climate crisis which requires immediate interventions to mitigate the negative effects on all aspects of life on this planet. As current agriculture and land use contributes up to 25% of total GHG emissions, plant scientists take center stage in finding possible solutions for a transition to sustainable agriculture and land use. In this article, the PlantACT! (Plants for climate ACTion!) initiative of plant scientists lays out a road map of how and in which areas plant scientists can contribute to finding immediate, mid-term, and long-term solutions, and what changes are necessary to implement these solutions at the personal, institutional, and funding levels.

Age effects of Moso bamboo on leaf isoprene emission characteristics

Isoprene is a highly reactive volatile organic compound that significantly affects atmospheric oxidant capacity, regional air quality, and climate change. Moso bamboo (Phyllostachys edulis), a species widely distributed in tropical and subtropical regions, particularly in China, is a strong isoprene emitter with great potential for carbon sequestration. Carbon sequestration is negatively correlated with culm age; however, the effect of this correlation on isoprene emissions remains unknown. In this study, we investigated the photosynthetic and isoprene emission characteristics of Moso bamboo at different culm ages. The results showed that the age effect on isoprene emission was different from that on photosynthesis; the net photosynthesis rate (Pn) was the highest in young, followed by mature, and then old bamboo, whereas the isoprene emission rate (Iso) was the highest in young, followed by old, and then mature bamboo. Moreover, the percentage of carbon loss as isoprene emission (C-loss) during photosynthesis of old bamboo was 35% higher than that of mature bamboo under standard conditions (leaf temperature: 30°C; light intensity: 1000 µmol m-2 s-1). Therefore, we strongly recommend considering the culm age when establishing an isoprene emission model of Moso bamboo. Additionally, because the Iso and C-loss of old bamboo were higher than those of mature bamboo, we suggest that attention should be paid to the management of bamboo age structure and timely felling of aged bamboo to reduce environmental risk.

Retrieval of carbon content and biomass from hyperspectral imagery over cultivated areas

Spaceborne imaging spectroscopy is a highly promising data source for all agricultural management and research disciplines that require spatio-temporal information on crop properties. Recently launched science-driven missions, such as the Environmental Mapping and Analysis Program (EnMAP), deliver unprecedented data from the Earth's surface. This new kind of data should be explored to develop robust retrieval schemes for deriving crucial variables from future routine missions. Therefore, we present a workflow for inferring crop carbon content (Carea ), and aboveground dry and wet biomass (AGBdry , AGBfresh ) from EnMAP data. To achieve this, a hybrid workflow was generated, combining radiative transfer modeling (RTM) with machine learning regression algorithms. The key concept involves: (1) coupling the RTMs PROSPECT-PRO and 4SAIL for simulation of a wide range of vegetation states, (2) using dimensionality reduction to deal with collinearity, (3) applying a semi-supervised active learning technique against a 4-years campaign dataset, followed by (4) training of a Gaussian process regression (GPR) machine learning algorithm and (5) validation with an independent in situ dataset acquired during the ESA Hypersense experiment campaign at a German test site. Internal validation of the GPR-Carea and GPR-AGB models achieved coefficients of determination (R 2) of 0.80 for Carea and 0.80, 0.71 for AGBdry and AGBfresh , respectively. The mapping capability of these models was successfully demonstrated using airborne AVIRIS-NG hyperspectral imagery, which was spectrally resampled to EnMAP spectral properties. Plausible estimates were achieved over both bare and green fields after adding bare soil spectra to the training data. Validation over green winter wheat fields generated reliable estimates as suggested by low associated model uncertainties (< 40%). These results suggest a high degree of model reliability for cultivated areas during active growth phases at canopy closure. Overall, our proposed carbon and biomass models based on EnMAP spectral sampling demonstrate a promising path toward the inference of these crucial variables over cultivated areas from future spaceborne operational hyperspectral missions.

Bioclimatic modeling and FACE study forecast a bleak future for wheat production in India

Since the impact of future climate change on wheat productivity is inconsistent, we studied geographic distribution and yield of wheat using two global General Circulation Models (GCMs) and Free Air CO_2/O₃ Enrichment (FACE) experiments. The GCMs (IPSL-CM5A-LR and NIMR-HADGEM2-AO) with four Representative Concentration Pathways (RCPs) and 19 bioclimatic variables were used for distribution/ecological niche modeling (ENM). Currently cultivated eight wheat cultivars were exposed to individual treatment of (i) ambient CO₂, temperature, and ozone (ACO + AO + AT) representing the present climate scenario, and (ii) elevated CO₂ (550 ppm) (ECO), (iii) elevated temperature (+ 2 °C) (ET), (iv) elevated O₃ (ambient + 20 ppb) (EO), (v) elevated CO₂ + elevated O₃ (ECO + EO), and (vi) elevated CO₂ + elevated temperature + elevated O₃ (ECO + EO + ET) under FACE facility simulating the future climate change scenarios in 2050. The niche models predicted a reduction in climatically suitable areas for wheat, and identified "maximum temperature" as the most influencing factor for area reduction. The elevated CO₂, O₃, and temperature individually and in combinations had differential impacts on the yield of wheat cultivars. Only two cultivars, viz., DBW 184 and DBW 187 did not exhibit yield decline suggesting their suitability in the future climate change scenario. Since the performance of six out of eight cultivars significantly declined under simulated FACE experiment, and ENM predicted reduction in wheat cultivation area under RCP 8.5 in 2050, it was concluded that future of wheat cultivation in India is bleak. The study further indicates that coupling of bioclimatic modeling and FACE experiment can effectively predict the impact of climate change on different crops.

Tapping into Plant-Microbiome Interactions through the Lens of Multi-Omics Techniques

This review highlights the pivotal role of root exudates in the rhizosphere, especially the interactions between plants and microbes and between plants and plants. Root exudates determine soil nutrient mobilization, plant nutritional status, and the communication of plant roots with microbes. Root exudates contain diverse specialized signaling metabolites (primary and secondary). The spatial behavior of these metabolites around the root zone strongly influences rhizosphere microorganisms through an intimate compatible interaction, thereby regulating complex biological and ecological mechanisms. In this context, we reviewed the current understanding of the biological phenomenon of allelopathy, which is mediated by phytotoxic compounds (called allelochemicals) released by plants into the soil that affect the growth, survival, development, ecological infestation, and intensification of other plant species and microbes in natural communities or agricultural systems. Advances in next-generation sequencing (NGS), such as metagenomics and metatranscriptomics, have opened the possibility of better understanding the effects of secreted metabolites on the composition and activity of root-associated microbial communities. Nevertheless, understanding the role of secretory metabolites in microbiome manipulation can assist in designing next-generation microbial inoculants for targeted disease mitigation and improved plant growth using the synthetic microbial communities (SynComs) tool. Besides a discussion on different approaches, we highlighted the advantages of conjugation of metabolomic approaches with genetic design (metabolite-based genome-wide association studies) in dissecting metabolome diversity and understanding the genetic components of metabolite accumulation. Recent advances in the field of metabolomics have expedited comprehensive and rapid profiling and discovery of novel bioactive compounds in root exudates. In this context, we discussed the expanding array of metabolomics platforms for metabolome profiling and their integration with multivariate data analysis, which is crucial to explore the biosynthesis pathway, as well as the regulation of associated pathways at the gene, transcript, and protein levels, and finally their role in determining and shaping the rhizomicrobiome.

Soil carbon storage potential of acid soils of Colombia's Eastern High Plains

Improving soil organic carbon (SOC) storage enhances soil quality and mitigates climate change. Agricultural and livestock specialists increasingly view tropical grasslands as a potential target for storing more soil carbon while boosting productivity. Earlier research in the 1990s showed the promise of improving SOC storage in the Eastern High Plains of Colombia. But these studies were limited to two experimental stations, without focusing on conditions on farms or under variable management. This research examined whether those early studies did indeed reflect possibilities for improving SOC storage and livestock productivity. We measured SOC stocks at one of the experiment stations from previous research and on farms throughout the study area in Colombia's Eastern High Plains. Complementarily our team sampled other predominant land uses to map SOC storage across the nearly 1 million ha study area. Using that information, we also constructed scenarios suggesting changes in SOC and productivity based on land-use changes. The high SOC accumulation found at experimental sites in the 1990s declined 24 years later. However, SOC storage was over 27 Mg ha−1 yr−1 higher than reference native savanna sites, with an accumulation rate of 0.96 Mg ha−1 yr−1. On farms under variable management, improved pastures stored 10 Mg ha−1 more SOC than degraded pastures or native savanna. For the whole region, we estimate that carbon storage observed across soils and land use of the 1 million ha study area could store 0.08 Gt of carbon down to 1 m depth, with wide variation across the region. While the SOC measured in grasslands in the early 1990s did not persist under inadequate management over the period of two decades, the potential to accumulate SOC of Colombia's Eastern High Plains through appropriate management is high, pointing to a sustainable livestock strategy that boosts productivity and reduces emissions.

Management of Rhizosphere Microbiota and Plant Production under Drought Stress: A Comprehensive Review

Drought generates a complex scenario worldwide in which agriculture should urgently be reframed from an integrative point of view. It includes the search for new water resources and the use of tolerant crops and genotypes, improved irrigation systems, and other less explored alternatives that are very important, such as biotechnological tools that may increase the water use efficiency. Currently, a large body of evidence highlights the role of specific strains in the main microbial rhizosphere groups (arbuscular mycorrhizal fungi, yeasts, and bacteria) on increasing the drought tolerance of their host plants through diverse plant growth-promoting (PGP) characteristics. With this background, it is possible to suggest that the joint use of distinct PGP microbes could produce positive interactions or additive beneficial effects on their host plants if their co-inoculation does not generate antagonistic responses. To date, such effects have only been partially analyzed by using single omics tools, such as genomics, metabolomics, or proteomics. However, there is a gap of information in the use of multi-omics approaches to detect interactions between PGP and host plants. This approach must be the next scale-jump in the study of the interaction of soil–plant–microorganism. In this review, we analyzed the constraints posed by drought in the framework of an increasing global demand for plant production, integrating the important role played by the rhizosphere biota as a PGP agent. Using multi-omics approaches to understand in depth the processes that occur in plants in the presence of microorganisms can allow us to modulate their combined use and drive it to increase crop yields, improving production processes to attend the growing global demand for food.

Genetic Circuit Design in Rhizobacteria

Genetically engineered plants hold enormous promise for tackling global food security and agricultural sustainability challenges. However, construction of plant-based genetic circuitry is constrained by a lack of well-characterized genetic parts and circuit design rules. In contrast, advances in bacterial synthetic biology have yielded a wealth of sensors, actuators, and other tools that can be used to build bacterial circuitry. As root-colonizing bacteria (rhizobacteria) exert substantial influence over plant health and growth, genetic circuit design in these microorganisms can be used to indirectly engineer plants and accelerate the design-build-test-learn cycle. Here, we outline genetic parts and best practices for designing rhizobacterial circuits, with an emphasis on sensors, actuators, and chassis species that can be used to monitor/control rhizosphere and plant processes.

Conquering compacted soils: uncovering the molecular components of root soil penetration

Global agriculture and food security face paramount challenges due to climate change and land degradation. Human-induced soil compaction severely affects soil fertility, impairing root system development and crop yield. There is a need to design compaction-resilient crops that can thrive in degraded soils and maintain high yields. To address plausible solutions to this challenging scenario, we discuss current knowledge on plant root penetration ability and delineate potential approaches based on root-targeted genetic engineering (RGE) and genomics-assisted breeding (GAB) for developing crops with enhanced root system penetrability (RSP) into compacted soils. Such approaches could lead to crops with improved resilience to climate change and marginal soils, which can help to boost CO₂ sequestration and storage in deeper soil strata.

Seasonal Variations in Grain Yield, Greenhouse Gas Emissions and Carbon Sequestration for Maize Cultivation in Bangladesh

Rationale: Greenhouse gas (GHG) emissions from crop agriculture are of great concern in the context of changing climatic conditions; however, in most cases, data based on lifecycle assessments are not available for grain yield variations or the carbon footprint of maize. The current study aimed to determine net carbon emissions and sequestration for maize grown in Bangladesh. Methods: The static closed-chamber technique was used to determine total GHG emissions using data on GHG emissions from maize fields and secondary sources for inputs. A secondary source for regional yield data was used in the current study. GHG emission intensity is defined as the ratio of total emissions to grain yield. The net GHG emission/carbon sequestration was determined by subtracting total GHG emissions (CO2 eq.) from net primary production (NPP). Results: Grain yields varied from 1590 to 9300 kg ha−1 in the wet season and from 680 to 11,820 kg ha−1 in the dry season. GHG emission intensities were 0.53–2.21 and 0.37–1.70 kg CO2 eq. kg−1 grain in the wet and dry seasons, respectively. In Bangladesh, the total estimated GHG emissions were 1.66–4.09 million tonnes (MT) CO2 eq. from 2015 to 2020, whereas the net total CO2 sequestration was 1.51–3.91 MT. The net CO2 sequestration rates were 984.3–5757.4 kg ha−1 in the wet season and 1188.62–5757.39 kg ha−1 in the dry season. This study observed spatial variations in carbon emissions and sequestration depending on growing seasons. In the rice–maize pattern, maize sequestered about 1.23 MT CO2 eq. per year−1, but rice emitted about 0.16 MT CO2 eq. per year−1. This study showed potential spatiotemporal variations in carbon footprints. Recommendation: Special care is needed to improve maize grain yields in the wet season. Fertiliser and water use efficiencies need to be improved to minimise GHG emissions under changing climatic conditions. Efforts to increase the area under cultivation with rice–maize or other non-rice crop-based cropping systems are needed to augment CO2 sequestration. The generation of a regional data bank on carbon footprints would be beneficial for combating the impact of climate change.

Wheat Rhizosphere Microbiota Respond to Changes in Plant Genotype, Chemical Inputs, and Plant Phenotypic Plasticity

Modern wheat varieties that were selected since the Green Revolution are generally grown with synthetic chemical inputs, and ancient varieties released before1960 without. Thus, when changes occur in rhizosphere microbiota structure, it is not possible to distinguish if they are due to (i) changes in wheat genotypes by breeding, (ii) modifications of the environment via synthetic chemical inputs, or (iii) phenotypic plasticity, the interaction between wheat genotype and the environment. Using a crossed factorial design in the field, we evaluated the effects of either modern or ancient wheat varieties grown with or without chemical inputs (a N fertilizer, a fungicide, and an herbicide) on “microbiome as a phenotype.” We analyzed the rhizosphere microbiota by bacterial and fungal amplicon sequencing, coupled with microscope observations of mycorrhizal associations. We found that plant genotype and phenotypic plasticity had the most influence on rhizosphere microbiota, whereas inputs had only marginal effects. Phenotypic plasticity was particularly important in explaining diversity variations in bacteria and fungi but had no impact on the mycorrhizal association. Our results show an interest in considering the interaction between wheat genotype and the environment in breeding programs, by focusing on genes involved in the phenotypic plasticity of plant-microbe interactions.

Forensic carbon accounting: Assessing the role of seaweeds for carbon sequestration

Carbon sequestration is defined as the secure storage of carbon-containing molecules for >100 years, and in the context of carbon dioxide removal for climate mitigation, the origin of this CO₂ is from the atmosphere. On land, trees globally sequester substantial amounts of carbon in woody biomass, and an analogous role for seaweeds in ocean carbon sequestration has been suggested. The purposeful expansion of natural seaweed beds and aquaculture systems, including into the open ocean (ocean afforestation), has been proposed as a method of increasing carbon sequestration and use in carbon trading and offset schemes. However, to verify whether CO₂ fixed by seaweeds through photosynthesis leads to carbon sequestration is extremely complex in the marine environment compared to terrestrial systems, because of the need to jointly consider: the comparatively rapid turnover of seaweed biomass, tracing the fate of carbon via particulate and dissolved organic carbon pathways in dynamic coastal waters, and the key role of atmosphere-ocean CO₂ exchange. We propose a Forensic Carbon Accounting approach, in which a thorough analysis of carbon flows between the atmosphere and ocean, and into and out of seaweeds would be undertaken, for assessing the magnitude of CO₂ removal and robust attribution of carbon sequestration to seaweeds.

Oilseed Brassica Species Diversification and Crop Geometry Influence the Productivity, Economics, and Environmental Footprints under Semi-Arid Regions

The article presents the findings of three-year field experiments conducted during 2017–2020 on the productivity, economics, and environmental footprints of the oilseed Brassica (OSB) with species diversification and crop geometry alterations in semi-arid regions of India. The objectives of the field experimentation was to assess the system of mustard intensification (SMI) in enhancing productivity and profitability with ensuring fewer environmental footprints. The results revealed that Brassica carinata gave a maximum seed productivity (3173.8 kg ha−1) and net returns (US$ 1141.72 ha−1) under a crop geometry of 60 cm × 60 cm. Further, an increase of 38% and 54% in seed yield and net returns from B. carinata was observed over the existing traditional Brassica juncea with conventional crop geometry. The maximum energy output was also recorded from B. carinata (246,445 MJ ha−1). The broader crop geometry (60 cm × 60 cm) also resulted in maximum energy output. The environmental footprint was lesser due to increased carbon gain (CG), carbon output (CO), and carbon production efficiency (CPE) and lower greenhouse gas intensity (GHGi) in B. carinata. However, the maximum water-use efficiency (WUE) was recorded in B. juncea (19.15 kg per ha-mm), with a minimum water footprint (WFP), whereas, greater crop geometry (60 cm × 60 cm) resulted in lower WFPs and better irrigation water use. Enhanced seed yield, economics, and fewer environmental footprints were observed at broader crop geometry in B. carinata over remaining OSBs.

Significance of the Diversification of Wheat Species for the Assembly and Functioning of the Root-Associated Microbiome

Wheat, one of the major crops in the world, has had a complex history that includes genomic hybridizations between Triticum and Aegilops species and several domestication events, which resulted in various wild and domesticated species (especially Triticum aestivum and Triticum durum), many of them still existing today. The large body of information available on wheat-microbe interactions, however, was mostly obtained without considering the importance of wheat evolutionary history and its consequences for wheat microbial ecology. This review addresses our current understanding of the microbiome of wheat root and rhizosphere in light of the information available on pre- and post-domestication wheat history, including differences between wild and domesticated wheats, ancient and modern types of cultivars as well as individual cultivars within a given wheat species. This analysis highlighted two major trends. First, most data deal with the taxonomic diversity rather than the microbial functioning of root-associated wheat microbiota, with so far a bias toward bacteria and mycorrhizal fungi that will progressively attenuate thanks to the inclusion of markers encompassing other micro-eukaryotes and archaea. Second, the comparison of wheat genotypes has mostly focused on the comparison of T. aestivum cultivars, sometimes with little consideration for their particular genetic and physiological traits. It is expected that the development of current sequencing technologies will enable to revisit the diversity of the wheat microbiome. This will provide a renewed opportunity to better understand the significance of wheat evolutionary history, and also to obtain the baseline information needed to develop microbiome-based breeding strategies for sustainable wheat farming.