Spatial information on soil organic carbon (SOC) stocks is essential for assessing soil fertility and ecosystem services. However, the influence of different mapping methods on SOC map accuracy and bias remains insufficiently quantified. This study synthesizes evidence from 37 published studies comparing four main approaches: basic interpolation, geostatistical methods, statistical and machine learning models, and remote sensing. Overall, SOC mapping accuracy varied substantially across methods, with a median mean absolute error (MAE) of approximately 40% of mean SOC stocks. Statistical and machine learning approaches, as well as hybrid methods, were generally associated with comparatively lower errors, although results were strongly context-dependent and influenced by study design heterogeneity. Bias across methods was generally low, but differences among approaches were observed. Mapping errors were strongly influenced by spatial scale, increasing with study area size and reaching very high values in large regions. Errors also showed moderate relationships with environmental factors such as precipitation and soil carbon levels, indicating that both methodological choice and environmental context contribute to prediction uncertainty. These findings highlight substantial variability in SOC mapping performance and demonstrate that scale and environmental conditions strongly influence reported model errors. The study emphasizes the need for standardized evaluation metrics, improved reporting consistency, and broader integration of environmental and management drivers in future SOC mapping efforts. Interpretation is limited by study heterogeneity and potential publication bias inherent in the 37 available studies.

IntroductionMaize is a global commodity crop cultivated under monocropping systems and diverse environmental conditions. While different genotypes exist with various abilities to store carbon into tissues and into the soil to mitigate against climate change and soil degradation, the links with grain yield remains uncertain.MethodsTherefore, the present study aimed to screen a series of maize germplasm planted in southern Africa for carbon storage and agronomic performance to assess the link between these and identify superior genotypes. We evaluated as a first attempt, forty-five genotypes using a 5 x 9 alpha lattice design across two South African sites during the 2022/23 growing season. The recorded agronomic traits include plant height (PH), grain yield (GY), total plant biomass (PB), shoot biomass (SB) and root biomass (RB) together with total plant carbon stocks (PCs), shoot carbon stock (SCs), root carbon stock (RCs), root to shoot carbon stock ratio (RCs/SCs), and grain carbon stock (GCs).ResultsSignificant (p< 0.05) genetic variations were recorded for all the assessed agronomic traits. The high yielding maize genotypes were TZECOMP3DT-C2, TZE(OMP3DT/WHITEDTSTRSYN)CZ and DT-STR-Y-SYN14. The maize genotypes which sequestered more carbon were TZE(OMP3DT/WHITEDTSTRSYN)CZ, 9022–13 and ZDIPLOBC4-C3-W. High phenotypic and genotypic coefficient of variations were recorded for PB and GY, respectively. The GY showed significant positive correlation with PH, SB, RB and PB. The principal component analysis highlighted that RCs, RCs/SCs, PCs, SCs, and GCs as key contributors to carbon sequestration.DiscussionGenotypes TZECOMP3DT-C2, TZE(OMP3DT/WHITEDTSTRSYN)CZ, TZECOMP5C7/ TZECOMP39TCZ and 9022–13 were selected for their high GY production and carbon storage capacity. The selected genotypes are recommended for production and future breeding.

Limited and variable rainfall conditions during flowering and grain filling stages remain the leading cause of poor yields and quality in the major produced crops, including wheat. Cultivating water-use-efficient wheat cultivars will buffer yield stability and environmental plasticity to achieve food security and economic opportunities. Therefore, this study aimed to evaluate the agronomic performance and water use efficiency (WUE) of newly bred wheat populations under drought-stressed and non-stressed conditions to select drought-tolerant families for genetic advancement and production. Field experiments were conducted in the 2022 and 2023 growing seasons to evaluate 100 genotypes (10 parental lines and 90 families) using a 5 × 20 alpha-lattice design under drought-stressed (DS) and non-stressed (NS) conditions. Controlled experiments were conducted using custom-made plastic mulch under field conditions. The following agronomic traits were recorded: number of days to 50

Abstract. Soil organic matter (SOM), which associates organic carbon to key plant nutrients, is a corner stone of soil health, agricultural productivity and ecosystem functioning. While virgin lands (forest or grassland) exhibit the highest SOM stocks, their cultivation leads to their sharp decrease and that of crop yields in the first decade(s), even when zero tillage and cover crops are promoted. The decline in SOM is less acute when crops are fertilized with N, P, K at rates recommended to meet crop needs than when not fertilized, and is often reversed when nutrients are applied above recommendations. This points to the key role of fertilization to manage croplands’ soil carbon that needs to be better understood to mitigate against soil degradation for promoting sustainable agriculture, while minimizing environmental hazards such as water pollution.

Multiple trait selection guides the deployment of wheat varieties with high grain yield (GY) and water-use efficiency (WUE). The study aimed to determine the degree and trend of association between agronomic traits and major metabolites to identify influential traits and metabolites optimised by wheat genotypes for improved GY, WUE and drought tolerance. One hundred wheat genotypes were evaluated under drought-stressed (DS) and non-stressed (NS) using a 5 x 20 alpha-lattice design with two replications. The recorded agronomic traits included GY, shoot biomass (SB), root biomass (RB) and plant biomass (PB). The WUE in relation to GY (WUEgy) was computed based on GY produced under DS and NS. The grain of 10 wheat genotypes with high GY under DS were assayed for their metabolic responses to DS. The WUEgy showed significant correlations with PB, RB and SB under DS and NS conditions. Citric acid was strongly correlated with GY and WUEgy than other metabolites under DS. The SB had high positive direct effects on GY under both treatments, while PB had high and positive direct effects on WUEgy under DS. Therefore, selection based on SB, PB and citric acid is effective when selecting wheat ideotypes for drought tolerance and WUE.

AbstractSorghum is a vital food and feed crop in the world’s dry regions. Developing sorghum cultivars with high biomass production and carbon sequestration can contribute to soil health and crop productivity. The objective of this study was to assess agronomic performance, biomass production and carbon accumulation in selected sorghum genotypes for production and breeding. Fifty sorghum genotypes were evaluated at three locations (Silverton, Ukulinga, and Bethlehem) in South Africa during 2022 and 2023 growing seasons. Significant genotype × location (p < 0.05) interactions were detected for days to 50% heading (DTH), days to 50% maturity (DTM), plant height (PH), total plant biomass (PB), shoot biomass (SB), root biomass (RB), root-to-shoot biomass ratio (RS), and grain yield (GY). The highest GY was recorded for genotypes AS115 (25.08 g plant−1), AS251 (21.83 g plant−1), and AS134 (21.42 g plant−1). Genotypes AS122 and AS27 ranked first and second, respectively, for all the carbon stock parameters except for root carbon stock (RCs), whereas genotype AS108 had the highest RCs of 8.87 g plant−1. The principal component analysis identified GY, DTH, PH, PB, SB, RB, RCs, RCs/SCs, total plant carbon stock (PCs), shoot carbon stock (SCs), and grain carbon stock (GCs) as the most discriminated traits among the test genotypes. The cluster analysis using agronomic and carbon-related parameters delineated the test genotypes into three genetic groups, indicating marked genetic diversity for cultivar development and enhanced C storage and sustainable sorghum production. The selected sorghum genotypes are recommended for further breeding and variety release adapted to various agroecologies in South Africa.

Integrating grain yield, component traits and metabolite profiles aids in selecting drought-adapted and climate-smart crop varieties preferred by end users. Understanding the trends and magnitude of grain-based metabolites is vital for selecting wheat genotypes with higher grain yield, drought tolerance, water use efficiency and product profiles. The aim of this study was to determine the response of newly developed wheat genotypes for grain yield and component traits and metabolites under drought stress to guide selection. One hundred wheat genotypes were preliminarily evaluated for agro-morphological traits and water use efficiency under drought-stressed and non-stressed conditions during the 2022 and 2023 growing seasons using a 5 x 20 alpha lattice design with two replications. Ten high-yielding genotypes were selected based on grain yield and were validated for agronomic traits and water use efficiency (WUE), and grain samples were assayed to profile their key metabolites under drought-stressed conditions. Significant differences existed (p < 0.05) among the tested wheat genotypes for yield and yield components, WUE, drought tolerance and major metabolites to discern trait associations. The grain yield of the 10 genotypes ranged from 590.00 g m(-2) (genotype LM70 x BW140) to 800.00 g m-2 (BW141 x LM71) under drought-stressed treatment, whilst under non-stressed it ranged from 760.06 g m -2 (LM70 x BW140) to 908.33 g m(-2) (LM71 x BW162). Grain yield-based water use efficiency of the assessed genotypes was higher under non-stressed (0.18 g mm(-1)) than drought-stressed (0.17 g mm-1) conditions. The highest drought tolerance index (211.67) and stress susceptibility index (0.77) were recorded for BW162 x LM71, whilst the lowest tolerance index (23.33) and stress susceptibility index (0.09) were recorded in BW141 x LM71. Grain metabolites, including the apigenin-8-C-glucoside (log2Fold = 3.00) and malate (log2Fold = 3.60) were present in higher proportions in the high-yielding genotypes (BW141 x LM71 and LM71 x BW162) under drought-stressed conditions, whilst fructose (log2Fold = -0.50) and cellulose (log2Fold = -3.90) showed marked decline in the two genotypes. Based on phenotypic and metabolite profile analyses, genotypes BW141 x LM71 and LM71 x BW162 were selected for being drought-tolerant, water-use efficient and recommended for production or breeding. The findings revealed associations between yield components, water use efficiency and grain metabolites to guide the selection of best-performing and drought-tolerant wheat varieties.

Crop residue decomposability in soils is of major importance for maintaining soil carbon (C) stocks and nitrogen (N) mineralization, which are vital for soil fertility and climate change mitigation. The impact of biochemical quality on decomposition and N mineralization of sorghum cultivars and/or crop residue parts is not well documented. In the present study, field and laboratory experiments spanning 168 and 120 days, respectively, were used to assess the rate of decomposition and N mineralization in soils from five sorghum cultivars and to relate the results with residue quality (i.e. lignin: N ratio) over time. High-quality cultivars (i.e., Mamolokwane and OS-Potch) exhibit rapid decomposition (>50% DM loss) and elevated carbon dioxide emissions in shoots, attributed to a low lignin-to-nitrogen ratio. Low-quality residues (i.e., AS8 and KZ5246) initially undergo net nitrogen immobilization, transitioning to mineralization at later stages. Notably, shoots consistently release more nitrogen than roots, with distinct NO3 -N mineralization values ranging from 22.7 to 11.5 mg N/kg for OS-Potch and KZ5246 shoots and 20.6 to 9.3 mg N/kg for their root residues. Results suggest that low-quality sorghum residues, particularly KZ5246 and AS8 roots, release carbon and nitrogen at a slower rate, providing potential for carbon storage and limited nitrogen availability compared to high-quality residues like OS-Potch shoots.

Abstract Field assessments of crop water use efficiency (WUE) are resource‐consuming since they require simultaneous assessment of the total amount of water assimilated by crops for biomass and/or grain production. Alternative methods exist, such as estimating the carbon isotopic ratio (13C/12C) of the crop's leaf, aboveground biomass, or grain samples. There is limited information on the determinants of the accuracy of carbon isotopes in estimating water use efficiency between crop types and environments. Therefore, this study aimed to evaluate the extent to which the estimation of the 13C/12C ratio in crop parts constitutes an accurate proxy of WUE, globally. Data on observed WUE (WUEobs) were collated involving 518 experiments conducted worldwide on major cereals and legumes and compared with WUE estimates (WUEest) from carbon isotopes. The mean WUEobs among all experiments was 3.4 g L−1 and the mean absolute error (MAE) was 0.5 g L−1 or 14.7% of WUEobs, corresponding to accurate predictions at p < 0.05. However, the percentage mean absolute error of observed water use efficiency (%MAE) estimated from grains was 3.6 ± 11.5%, which was lower than the %MAE from aboveground biomass collected at harvest (3 ± 22.8%). In addition, the %MAE increased from 1.1 ± 5.1% for soybean, 1.6 ± 7.2% for maize, 1.2 ± 8.6% for rice, 1.8 ± 12.1% for groundnut, 2.1 ± 14.3% for cowpea, 2.3 ± 16.2% for bush bean, 1.8 ± 19.9% for wheat, 2.2 ± 21.4% for barley to 6.3 ± 39.3% for oat, with only the latter corresponding to significant errors. WUEest were, in all cases, unbiased but slightly overestimated from 0.8% (maize) to 15.4% (oat). The accuracy in estimating WUE significantly decreased with the increase in soil clay content, with sand, showing a positive correlation of 0.3 with %MAE, but negatively correlated with the silt content (r = −0.4). Furthermore, a multivariate analysis pointed out a tendency for prediction errors and bias to increase with the decrease in WUEobs and air temperature. Using carbon isotopes for estimating crop WUE thus appeared reliable for all crops and world environments, provided grain samples are considered. The technique tended to perform better under high WUE conditions, such as those generally found in maize and soybean cropping systems. The identified factors that affect the accuracy of using carbon isotopes in measuring WUE provide valuable insights for water resource management and sustainable crop production. These findings contribute to the ongoing discourse on water conservation strategies in agriculture, offering a basis for decision‐making in crop improvement programs. Implementing the recommended practices from this study can potentially improve yield gains and promote resilient and sustainable agricultural systems in the changing environmental circumstances. Further research should investigate the mechanisms that cause low accuracy of the isotopic technique using aboveground biomass and under arid and cool environments.

In the context of escalating global concerns for “carbon neutrality and peak carbon” and the urgent need for ecological conservation, deciphering the spatiotemporal interactions between carbon emissions and the ecosystem service value (ESV) in relation to land use changes becomes critically significant. Identifying areas to bolster ecosystem services and curtail carbon emissions, especially within the Guanzhong urban agglomeration, is crucial for advancing sustainable and low-carbon regional development. The study focuses on the urban agglomeration of Guanzhong, using land use and socio-economic data from three periods between 2010 and 2020. Methods such as grid analysis and bivariate spatial autocorrelation models are employed to explore the temporal and spatial evolution characteristics and interaction patterns of carbon emissions and ESV in relation to land use. The findings reveal: (1) during 2010–2020, the Guanzhong urban agglomeration experienced varied transitions in land use types, marked by a significant net decrease in arable land and net increases in grasslands and urban construction areas. (2) The ESV in the Guanzhong urban agglomeration witnessed a consistent rise, exhibiting a spatial distribution pattern with higher values in the southwest and lower in the northeast. Among the categorized ecosystem service functions, services related to hydrological and climate regulation stood out. (3) The Guanzhong urban agglomeration observed an average annual growth rate of 5.03% in carbon emissions due to land use, with a spatial trend that was higher in the center and tapered towards the periphery. Predominant carbon sources included arable lands and urban construction areas, while forests accounted for 94% of carbon sequestration. (4) A pronounced negative correlation between the ESV and carbon emissions was discerned in Guanzhong. Regions with a stronger correlation were primarily centered in Guanzhong, notably around Xi’an and Baoji. The results emphasize the pivotal role of the primary sector’s qualitative development in harmonizing the ESV and carbon emission dynamics in the Guanzhong urban agglomeration. This research provides valuable insights for optimizing land resource management, aligned with the rural revitalization strategy, streamlining carbon dynamics, bolstering ESV, augmenting carbon sequestration efficiency, and guiding ecological spatial planning.

Biochar application to soil is commonly recognized to improve soil fertility and consequently biomass and food production sustainably.We re-examined the robustness of the underlying data and found that,of the 12 000+publications on"biochar and agriculture"used in meta-studies,only 109 Institute for Scientific Information(ISI)papers(or 0.9％)provide experimental data on the impacts on crop yield and/or biomass production.

Crop biomass is the reservoir of carbon (C), a valuable input to the soil, thus supporting the soil fauna and enhancing soil health. There are limited studies that compared the major cereal crops for C storage for regenerative agriculture and to optimize C sequestration strategies. The objective of this study was to quantify the extent of variation in biomass allocation and C storage between maize (Zea mays L.), sorghum (Sorghum bicolor [L.] Moench), and wheat (Triticum aestivum L.) for crop production, and C sequestration potential. The study used metadata from 40 global studies that reported on the allocation of plant biomass and C between roots and shoots of the major cereal crops. Key statistics were computed to determine the variability between genotypes for total plant biomass (Pb), shoot biomass (Sb), root biomass (Rb), root-to-shoot biomass ratio (Rb/Sb), total plant carbon content, shoot carbon content, root carbon content, total plant carbon stock (PCs), shoot carbon stock, root carbon stock, and root-to-shoot carbon stock ratio (RCs/SCs). Maize exhibited the highest variability for Pb (with a coefficient of variation [CV] of 31.2% and a mean of 4.2 +/- 1.3 Mg ha-1 year-1), followed by wheat (CV of 24.2% and a mean of 1.5 +/- 0.4 Mg ha-1 year-1) and sorghum (CV of 16.8% and a mean of 2.0 +/- 0.8 Mg ha-1 year-1), respectively. A similar trend was observed for PCs, with maize (CV of 40.1% and mean of 1.6 +/- 0.7 Mg ha-1 year-1) showing the highest total plant C stock variability, followed by wheat (24.4% and 0.2 +/- 0.1 Mg ha-1 year-1) and sorghum (16.3% and 0.9 +/- 0.3 Mg ha-1 year-1), respectively. Maize (with a CV of 24.4% and mean of 0.1 +/- 0.03 Mg ha-1 year-1) exhibited the highest variability for Rb/Sb, while wheat (30.92% and 0.2 +/- 0.05 Mg ha-1 year-1) exhibited the highest variability for RCs/SCs. Correlation analysis revealed the following significant associations: Pb and mean annual temperature (MAT) (r = -0.47), and Sb and MAT (r = -0.43), and Pb and mean annual precipitation (MAP) (r = -0.34), and Sb and MAP (r = -0.30). Rb had a strong, significant positive correlation with MAT (r = 0.72) and MAP (r = 0.85). The meta-analysis revealed that maize and sorghum have the highest variability for Pb and plant carbon stocks, while wheat exhibited the highest variability for the below-ground biomass and carbon stocks. The data aided in crop selection and suggested that the best cultivars could be developed and identified for production and C sequestration potential for cultivation by farmers, land rehabilitation, and climate change mitigation. There is sufficient genetic variation in maize, sorghum, and wheat cultivars for manipulation of biomass and carbon allocation. Root carbon is a major contributor to soil organic carbon. Above-ground biomass is important for atmospheric carbon sequestration.

Trait heritability and the response to selection depend on genetic variation, a prerequisite to developing sorghum varieties with desirable agronomic traits and high carbon sequestration for sustainable crop production and soil health. The present study aimed to assess the extent of genetic variability and associations among agronomic and carbon storage traits in selected sorghum genotypes to identify the best candidates for production or breeding. Fifty genotypes were evaluated at Ukulinga, Bethlehem and Silverton sites in South Africa during the 2022/23 growing season. The following agronomic and carbon storage traits were collected: days to 50% heading (DTH), days to 50% maturity (DTM), plant height (PH), total plant biomass (PB), shoot biomass (SB), root biomass (RB), root-to-shoot biomass ratio (RS), grain yield (GY), harvest index (HI), shoot carbon content (SCc), root carbon content (RCc), grain carbon content (GCc), total plant carbon stock (PCs), shoot carbon stock (SCs), root carbon stock (RCs), and root-to-shoot carbon stock ratio (RCs/SCs), and grain carbon stock (GCs). Higher genotypic coefficient of variations (GCVs) were recorded for GY at 45.92%, RB (39.24%), RCs/SCs (38.45), and RCs (34.62). Higher phenotypic coefficient of variations (PCVs) were recorded for PH (68.91%), followed by GY (51.8%), RB (50.51%), RS (41.96%), RCs/SCs (44.90%), and GCs (41.90%). High broad-sense heritability and genetic advance were recorded for HI (83.76 and 24.53%), GY (78.59 and 9.98%), PB (74.14 and 13.18%) and PCs (53.63 and 37.57%), respectively, suggesting a marked genetic contribution to the traits. Grain yield exhibited positive association with HI (r = 0.76; r = 0.79), DTH (r = 0.13; r = 0.31), PH (r = 0.1; r = 0.27), PB (r = 0.01; r = 0.02), RB (r = 0.05; r = 0.06) based on genotypic and phenotypic correlations, respectively. Further, the path analysis revealed significant positive direct effects of SB (0.607) and RB (0.456) on GY. The RS exerted a positive and significant indirect effect (0.229) on grain yield through SB. The study revealed that PB, SB, RB, RS, RCs, and RCs/SCs are the principal traits when selecting sorghum genotypes with high yield and carbon storage capacity.

The transfer of atmospheric carbon (C) in soils is a possible strategy for climate change mitigation and for restoring land productivity. While some studies have compared the ability of existing crops to allocate C into the soil, the genetic variations between crop genotypes have received less attention. The objective of this study was to compare the allocation to the soil of atmospheric C by genetically diverse wheat genotypes under different scenarios of soil water availability. The experiments were set up under open-field and greenhouse conditions with 100 wheat genotypes sourced from the International Maize and Wheat Improvement Centre and grown at 25% (drought stressed) and 75% (non-stressed) field capacity, using an alpha lattice design with 10 incomplete blocks and 10 genotypes per block. The genotypes were analyzed for grain yield (GY), plant shoot and root biomass (SB and RB, respectively) and C content, and stocks in plant parts. Additionally, 13C pulse labeling was performed during the crop growth period of 10 selected genotypes for assessing soil C inputs. The average GY varied from 75 to 4696 g m−2 and total plant biomass (PB) from 1967 to 13,528 g m−2. The plant C stocks ranged from 592 to 1109 g C m−2 (i.e., an 87% difference) under drought condition and between 1324 and 2881 g C m−2 (i.e., 117%) under well-watered conditions. Atmospheric C transfer to the soil only occurred under well-drained conditions and increased with the increase in the root to shoot ratio for C stocks (r = 0.71). Interestingly, the highest transfer to the soil was found for LM-26 and LM-47 (13C/12C of 7.6 and 6.5 per mille, respectively) as compared to LM-70 and BW-162 (0.75; 0.85). More is to be done to estimate the differences in C fluxes to the soil over entire growing seasons and to assess the long-term stabilization of the newly allocated C. Future research studies also need to identify genomic regions associated with GY and soil C transfer to enable the breeding of “carbon-superior” cultivars.