Long-term Crop Research Articles

Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield

Statistical crop modeling is pivotal for understanding climate impacts on crop yields. Choices of models matter: Linear regression is interpretable but limited in predictive power; machine learning predicts well but often remains a black box. To develop explainable artificial intelligence (AI) for exploring historical crop yield data and predicting crop yield, here we reported a Bayesian ensemble model (BM) that is interpretable with great explanatory and predictive power. BM embraces many competitive models via Bayesian model averaging, fits complex functions, and quantifies model uncertainty. Long-term crop yields are driven by both climate and technology; the common practice of first detrending and then analyzing the detrended data has an incorrigible bias. Therefore, BM was also aimed at decomposing historical yield data to jointly estimate technological trends and climate effects on crop yield. We compared BM with ElasticNet, Neural Network, MARS, SVM, Random Forests, and XGBoost. BM excelled at both predicting and explaining. When tested on synthetic data, BM was the only method unveiling the true relationships: BM has stronger interpretability; other methods predicted well but for wrong reasons. When tested on maize yield data in Ohio, BM detected two technological shifts, attributable to hybrid corn adoption in the 1940′s and the technological slowing-down in the 1970′s: No other methods detected such changepoints. BM derived nonlinear asymmetric crop responses to climate and non-negligible temperature-precipitation interacting effects, with patterns consistent with theoretical or experimental evidence. Extrapolation of all the models for future yield prediction was highly uncertain, but BM provided more reliable predictions under novel climate whereas Random Forests and XGBoost proved unsuitable for extrapolation. Overall, BM provided new insights unattainable by the existing black-box methods. We caution against blind use of black-box machine learning for statistical crop modeling and call for more efforts to apply interpretable machine learning for mechanistic understandings of crop-climate interactions.

The role of inherited characteristics from parent materials in shaping bacterial communities in agricultural soils

Parent materials are crucial in soil formation and development, but their importance in shaping soil bacterial communities after thousands of years of soil formation remains unknown, especially in agricultural soils. To resolve the influence of underlying features inherited from parent materials on soil microbiome, the microbial community in 197 agricultural soils with long-term crop cultivation history and nonagricultural reference soils from four major types of soils in China, i.e., quaternary red clay soils, tertiary red sandstone soils, alluvial soils and black soils, were analyzed and compared. We found that different types of soils supported distinct bacterial communities. The characteristics inherited from parent materials explained more of the variation (31.47%) in bacterial community structure than the selected variables regulated by soil management (1.63%) and the climate condition (1.10%). Only 9.0% of total bacterial amplicon sequence variants (ASVs) which contributed, on average, 47% of the total bacterial abundances in a given agricultural soil, were shared by all soil types. These abundant common ASVs were closely related to agricultural practices, suggesting a strong enrichment effect of a small number of core taxa by long-term crop cultivation. In contrast, approximately 55.6% of ASVs with low relative abundance were specific to soil type. These specific groups were closely associated with the distinctive features of soil type, implying that they represent unique populations selected by the parent material features during pedogenesis. Collectively, soil type may have a strong selective pressure on the bacterial communities in matured agricultural soils, leading to a large pool of specific taxa with limited environmental occurrence. Whilst a small number of core taxa achieve high abundances by responding to long-term crop cultivation.

Evaluation of MODIS, Landsat 8 and Sentinel-2 Data for Accurate Crop Yield Predictions: A Case Study Using STARFM NDVI in Bavaria, Germany

The increasing availability and variety of global satellite products and the rapid development of new algorithms has provided great potential to generate a new level of data with different spatial, temporal, and spectral resolutions. However, the ability of these synthetic spatiotemporal datasets to accurately map and monitor our planet on a field or regional scale remains underexplored. This study aimed to support future research efforts in estimating crop yields by identifying the optimal spatial (10 m, 30 m, or 250 m) and temporal (8 or 16 days) resolutions on a regional scale. The current study explored and discussed the suitability of four different synthetic (Landsat (L)-MOD13Q1 (30 m, 8 and 16 days) and Sentinel-2 (S)-MOD13Q1 (10 m, 8 and 16 days)) and two real (MOD13Q1 (250 m, 8 and 16 days)) NDVI products combined separately to two widely used crop growth models (CGMs) (World Food Studies (WOFOST), and the semi-empiric Light Use Efficiency approach (LUE)) for winter wheat (WW) and oil seed rape (OSR) yield forecasts in Bavaria (70,550 km2) for the year 2019. For WW and OSR, the synthetic products’ high spatial and temporal resolution resulted in higher yield accuracies using LUE and WOFOST. The observations of high temporal resolution (8-day) products of both S-MOD13Q1 and L-MOD13Q1 played a significant role in accurately measuring the yield of WW and OSR. For example, L- and S-MOD13Q1 resulted in an R2 = 0.82 and 0.85, RMSE = 5.46 and 5.01 dt/ha for WW, R2 = 0.89 and 0.82, and RMSE = 2.23 and 2.11 dt/ha for OSR using the LUE model, respectively. Similarly, for the 8- and 16-day products, the simple LUE model (R2 = 0.77 and relative RMSE (RRMSE) = 8.17%) required fewer input parameters to simulate crop yield and was highly accurate, reliable, and more precise than the complex WOFOST model (R2 = 0.66 and RRMSE = 11.35%) with higher input parameters. Conclusively, both S-MOD13Q1 and L-MOD13Q1, in combination with LUE, were more prominent for predicting crop yields on a regional scale than the 16-day products; however, L-MOD13Q1 was advantageous for generating and exploring the long-term yield time series due to the availability of Landsat data since 1982, with a maximum resolution of 30 m. In addition, this study recommended the further use of its findings for implementing and validating the long-term crop yield time series in different regions of the world.

Establishing Optimal Planting Windows for Contrasting Sorghum Cultivars across Diverse Agro-Ecologies of North-Eastern Nigeria: A Modelling Approach

In the context of climate change, the sowing date and cultivar choice can influence the productivity of sorghum, especially where production is constrained by low soil fertility and early terminal drought across the challenging agro-ecologies of north-eastern Nigeria. Planting within an optimal sowing window to fit the cultivar’s maturity length is critical for maximizing/increasing the crop yield following the appropriate climate-smart management practices. In this study, the APSIM crop model was calibrated and validated to simulate the growth and yield of sorghum cultivars with differing maturing periods sown within varying planting time windows under improved agricultural practices. The model was run to simulate long-term crop performance from 1985 to 2010 to determine the optimal planting windows (PWs) and most suitable cultivars across different agro-ecological zones (AEZs). The performance of the model, validated with the observed farm-level grain yield, was satisfactory across all planting dates and cropping systems. The model predicted a lower mean bias error (MBE), either positive or negative, under the sole cropping system in the July sowing month compared to in the June and August sowing months. The seasonal climate simulations across sites and AEZs suggested increased yields when using adapted sorghum cultivars based on the average grain yield threshold of ≥1500 kgha−1 against the national average of 1160 kgha−1. In the Sudan Savanna (SS), the predicted optimum PWs ranged from 25 May to 30 June for CSR01 and Samsorg-44, while the PWs could be extended to 10 July for ICSV400 and Improved Deko. In the Northern Guinea Savanna (NGS) and Southern Guinea Savanna (SGS), the optimal PWs ranged from 25 May to 10 July for all cultivars except for SK5912, for which predicted optimal PWs ranged from 25 May to 30 June. In the NGS zone, all cultivars were found to be suitable for cultivation with exception of SK5912. Meanwhile, in the SGS zone, the simulated yield below the threshold (1500 kgha−1) could be explained by the sandy soil and the very low soil fertility observed there. It was concluded that farm decisions to plant within the predicted optimal PWs alongside the use of adapted sorghum cultivars would serve as key adaptation strategies for increasing the sorghum productivity in the three AEZs.

Integrated weed management strategies in a long-term crop rotation system

Background Diversified crop systems provide several advantages for crop production and the agricultural ecosystem. In contrast, growing the same crop for consecutive years increases weeds, insects, and diseases issues, adding further cost to crop production owing to their management. Objective The objective was to evaluate the effects of six different winter cover crops and compare the impacts of a diversified rotation system in contrast to the succession system, combined with three different post-emergence herbicide management looking up to soybean [...]

Análisis y caracterización de poblaciones bacterianas solubilizadoras de P en un ensayo de larga duración con diferentes secuencias de cultivo

It is well known that different soil use and management systems affect the abundance, activity and composition of the soil microbial community. In this work, the behavior of cultivable bacterial populations and, in particular, P (PSB) solubilizing bacteria in soil samples from a long-term trial with different culture sequences was studied. The results obtained show that the clearing and subsequent agricultural use after 11 years generated a decrease in the population of cultivable bacteria in general, and of P-solubilizing bacteria in particular, with respect to the pristine soil. Isolates with high P solubilization efficiency were obtained from the soils from the different rotations. These efficient isolates were taxonomically classified by 16S RNA analysis as belonging to the genera Bacillus, Paenibacillus, Pseudomonas and Xanthomonas. In particular, the characterization of the culture supernatants of the isolates Pseudomonas koreensis and Paenibacillus pabuli showed they are producers of organic acids. The combined inoculation tests of these two strains on maize plants in a culture chamber revealed a synergistic effect on the growth promotion of this species. The results presented here suggest that although PSB populations are more numerous in pristine soils, certain long-term crop rotations favor the increase of more efficient solubilizing bacteria, an aspect that should be considered when designing future search strategies for potential bioinoculants.

Dynamic of the Soil Microbiota in Short-Term Crop Rotation

Crop rotation is one of the oldest and most effective methods of restoring soil fertility, which declines when the same plant is grown repeatedly. One of the reasons for a reduction in fertility is the accumulation of pathogenic and unfavorable microbiota. The modern crop rotation schemes (a set of plant species and their order in the crop rotation) are highly effective but are designed without considering soil microbiota dynamics. The main goal of this study was to perform a short-term experiment with multiple plant combinations to access the microbiological effects of crop rotation. It could be useful for the design of long-term crop rotation schemes that take the microbiological effects of the crop rotation into account. For the analysis, five plants (legumes: vetch, clover, and cereals: oats, wheat, and barley) were used. These five plants were separately grown in pots with soil. After the first phase of vegetation, the plants were removed from the soil and a new crop was planted. Soil samples from all 25 possible combinations of primary and secondary crops were investigated using v4-16S rDNA gene sequencing. It was shown that the short-term experiments (up to 40 days of growing) are effective enough to find microbial shifts in bulk soil from different plants. Both primary and secondary cultures are significant factors for the microbial composition of microbial soil communities. Changes are the most significant in the microbial communities of vetch soils, especially in the case of vetch monoculture. Growing clover also leads to changes in microbiota, especially according to beta-diversity. Data obtained can be used to develop new crop rotation schemes that take into account the microbiological effects of various crops.

Mapping crop type in Northeast China during 2013–2021 using automatic sampling and tile-based image classification

Northeast China is one of the most major grain banks in China and has an overwhelming influence on food security. To mitigate the challenges caused by increasing food demands and soil protection, crop rotation and fallowing policies have been introduced in Northeast China. These soil protection policies change annual crop planting area and crop distribution. To monitor crop type and its changes on a regional scale in time series, we explore the automatic sampling approach by hexagon strategy and tile-based classification by random forest (RF) algorithm using time-series Landsat-8 Operational Land Imager (OLI) images during 2013–2021. The crop maps have high credibility with the overall accuracies (OA) wall-to-wall ranging from 0.89 to 0.97, and also have close agreement with statistical data city by city. This study provides a highly reliable long-term crop maps dataset, which can be helpful for food security and regional agricultural production management.

Cropping systems and agricultural management strategies affect soil organic carbon dynamics in semi-arid regions

IntroductionSoil organic carbon (SOC) dynamic is one of the important factors that directly influence soil properties and quality. In agro-ecosystems, the SOC dynamics are strongly linked to agricultural management practices.MethodsIn this study, we investigated the response of SOC and its fractions to various combination of agricultural management practices based on measurements obtained from an experiment conducted over four growing seasons from 2018 to 2020 in Ahvaz, Iran. The experimental treatments involved three agricultural strategies combined with four crop rotation systems. The agricultural strategies comprised conventional (CON: mineral fertilizer, removal of all crop residues), organic (ORG: organic fertilizer, 30% return of crop residues to the soil), and integrated (INT: mineral/organic fertilizer, 15% return of crop residues) strategies. The crop rotation systems were: fallow-wheat (F-W), corn-wheat (C-W), sesame-wheat (S-W), and mung bean-wheat (B-W). Soil samples were collected from all treatments and SOC, labile-C, and non-labile-C were measured.Results and discussionAfter two years of experiment, no significant improvement was found in SOC of CON strategy (p ≤ 0.05). The ORG and INT strategies contained on average 1.1 and 1.06 times more SOC than the CON strategy, respectively. The value of labile-C was decreased during summer cultivations and increased in the soil samples collected after winter cultivations. However, although the quantity of labile-C in ORG (2 g kg−1) was higher than INT (1.83 g kg−1) and CON (1.87 g kg−1) overall during the experiment time, after the second summer cultivation despite the gradual accumulation of organic matter due to high levels of temperature and humidity, the content in ORG reduced to1.47 g kg−1. In all three agricultural management strategies, the SOC content in the four rotation systems was according to the following descending order B-W (5.7 g kg−1) > C-W (5.29 g kg−1) > S-W (5.23 g kg−1) > F-W (4.52 g kg−1). Therefore, for this region M-W and S-W crop rotation systems are recommended in addition to C-W (which is the most common rotation system). However, crop rotation systems were more beneficial for C-sequestration when combined with organic and inorganic fertilization and crop residue incorporation. This study gives promising results for implementing INT and ORG strategies under long-term cropping systems containing various summer crops in rotation with wheat for improving SOC dynamics in semi-arid regions in Iran.

Soil Aggregation and Aggregate-associated Carbon affected by Long-term Crop Residues Incorporation in Rice-Wheat Cropping System

Crop residue management is one of the options for enhancing soil organic carbon stabilization by improving soil aggregation in semi-tropical soil. We studied the influence of different levels crop residues incorporation on aggregation and carbon stabilization in different soil aggregates after 23 years of continuous rice- wheat cropping system on sandy loam calcareous soil. 100% residue incorporation caused a significant increment of 49.09 % in total water stable aggregates (>0.25 mm) in surface soil. Carbon content in both macro- and microaggregates was increased, but increment was greater in macroaggregates (33.47%) than microaggregates (16.23%). These results show that long-term application of organics in combination with inorganic fertilizers helped in carbon accumulation in macroaggregates, and thereby improving soil carbon status.

Soil aggregation and aggregate-associated carbon affected by long-term crop residues incorporation in rice-wheat cropping system

Soil aggregation and aggregate-associated carbon affected by long-term crop residues incorporation in rice-wheat cropping system

Modeling the Impact of Climate Change on Sustainable Production of Two Legumes Important Economically and for Food Security: Mungbeans and Cowpeas in Ethiopia

Climate change is one of the most serious threats to global crops production at present and it will continue to be the largest threat in the future worldwide. Knowing how climate change affects crop productivity might help sustainability and crop improvement efforts. Under existing and projected climate change scenarios (2050s and 2070s in Ethiopia), the effect of global warming on the distribution of V. radiata and V. unguiculata was investigated. MaxEnt models were used to predict the current and future distribution pattern changes of these crops in Ethiopia using different climate change scenarios (i.e., lowest (RCP 2.6), moderate (RCP 4.5), and extreme (RCP 8.5)) for the years 2050s and 2070s. The study includes 81 and 68 occurrence points for V. radiata and V. unguiculata, respectively, along with 22 environmental variables. The suitability maps indicate that the Beneshangul Gumuz, Oromia, Amhara, SNNPR, and Tigray regions are the major Ethiopian regions with the potential to produce V. radiata, while Amhara, Gambella, Oromia, SNNPR, and Tigray are suitable for producing V. unguiculata. The model prediction for V. radiata habitat ranges distribution in Ethiopia indicated that 1.69%, 4.27%, 11.25% and 82.79% are estimated to be highly suitable, moderately suitable, less suitable, and unsuitable, respectively. On the other hand, the distribution of V. unguiculata is predicted to have 1.27%, 3.07%, 5.22%, and 90.44% habitat ranges that are highly suitable, moderately suitable, less suitable, and unsuitable, respectively, under the current climate change scenario by the year (2050s and 2070s) in Ethiopia. Among the environmental variables, precipitation of the wettest quarter (Bio16), solar radiation index (SRI), temperature seasonality (Bio4), and precipitation seasonality (Bio15) are discovered to be the most effective factors for defining habitat suitability for V. radiata, while precipitation of the wettest quarter (Bio16), temperature annual range (Bio7) and precipitation of the driest quarter (Bio17) found to be better habitat suitability indicator for V. unguiculata in Ethiopia. The result indicates that these variables were more relevant in predicting suitable habitat for these crops in Ethiopia. A future projection predicts that the suitable distribution region will become increasingly fragmented. In general, the study provides a scientific basis of suitable agro-ecological habitat for V. radiata and V. unguiculata for long-term crop management and production improvement in Ethiopia. Therefore, projections of current and future climate change impacts on such crops are vital to reduce the risk of crop failure and to identify the potential productive areas in the country.

Integrated weed management strategies in a long-term crop rotation system

Background Diversified crop systems provide several advantages for crop production and the agricultural ecosystem. In contrast, growing the same crop for consecutive years increases weeds, insects, and diseases issues, adding further cost to crop production owing to their management. Objective The objective was to evaluate the effects of six different winter cover crops and compare the impacts of a diversified rotation system in contrast to the succession system, combined with three different post-emergence herbicide management looking up to soybean [...]

Relating soil physical properties to other soil properties and crop yields

Soil physical properties can be related to other soil properties and crop yields, but their evaluations as soil health indicators relating to extensive soil properties and long-term crop yields need further exploration. We evaluated the long-term (14 and 36 year) effect of cropping systems and N fertilizations on selected soil physical properties and related them to 66 soil physical, chemical, biological, and biochemical properties and mean crop yields across years at two dryland farming sites in the semiarid region of the northern Great Plains, USA. Treatments were rotations of no-tillage and conventional tillage spring wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), pea (Pisum sativum L.), and fallow with or without N fertilization. Soil samples collected in April 2019 were analyzed for physical, chemical, biological, and biochemical properties and mean crop yields were determined. The average slake aggregate (ASA), wet aggregate stability index (WASI), and intact core available water holding capacity (IAWHC) were associated with most soil physical, chemical, biological, and biochemical properties and clay concentration was associated with nutrient concentrations. These parameters were also better related to mean crop yields across years than other soil physical properties. Because of the enhanced relationship with soil properties and crop yields and simple and inexpensive measurement, ASA can be used as a potential soil health indicator in dryland cropping systems in semiarid regions.

Plectosphaerella melonis (Syn. Acremonium cucurbitacearum) — Plant Pathogenic Organism

Fungal diseases cause signifi cant damage to agriculture. Plectosphaerella melonis (syn. Acremonium cucurbitacearum and Nodulisporium melonis) is a pathogen of cultivated plant diseases in Spain, Italy, Japan, USA, Egypt, and Ukraine. This review discusses the main results of research related to this phytopathogen. By morphological and cultural features, P. melonis is a morphologically intermediate species between A. strictum and A. charticola, however, 5.8S-ITS regionbased phylogenetic analysis showed that P. melonis is a monophyletic taxon more closely related to Plectosphaerella than to other species of the genus Acremonium. The most susceptible plants are at the stage of germination; however, the development of the disease is manifested in the fruiting period. For a comprehensive assessment of virulence, real leaf area (RLA) of the first two leaves, lesion of hypocotyl (RH), root collar (RSR), primary (R1R) and secondary roots (R2R) are measured. P. melonis affects the root system, in particular the root collar and hypocotyl, and colonizes the epidermis and cortex of the root centrographically towards the stem. The range of host plants includes Cucurbitaceae, however, peppers, tomatoes, basil, and parsley are infected as well. Plants vary in susceptibility depending on the species and even variety. The pathogenic response of plants differs depending on the growing conditions (protected and open soil), the interaction between the pathogen and competing microorganisms, and other ecological and trophic relationships. The main means of control are the use of long-term crop rotations and the selection of resistant varieties. In Ukraine, a strain of the antagonist fungus Trichoderma viride was selected, which is an effective means for controlling P. melonis 502. The aim of our work was to establish the role of P. melonis in the development of diseases of cultivated plants.

Complex crop rotations improve organic nitrogen cycling

Nitrogen (N) availability in agroecosystems is often poorly coupled to plant N uptake, leading to inefficient fertilizer use and environmental losses. Building soil organic N pools and enhancing internal recycling of N with crop rotations while reducing synthetic inputs may help improve N use efficiency. The organic N pool could be a valuable source of N that could help farmers reduce reliance on large inorganic N inputs if controls on its availability were better understood. While we know that the breakdown of high-molecular weight organic N compounds is the rate-limiting step to accessing bioavailable N from organic sources in natural ecosystems, there has been little work in agroecosystems to identify how management influences this inflection point in the N cycle. To provide insight into how growers can manage the organic N pool to reduce fertilizer input, we examined gross protein depolymerization rates within an agricultural context. Specifically, we investigated 1) how crop rotations affect organic N pools and alter the rate of organic N cycling, and 2) whether inorganic N fertilization enhances, has no effect, or suppresses soil N cycling responses to crop rotation. To test this, we measured gross rates of protein depolymerization, amino acid consumption, mineralization, and ammonium consumption using 15N isotope pool dilution assays on soils collected from a long-term crop complexity experiment near Mead, NE, USA. Treatments sampled included both 0 kg and 180 kg N ha−1 fertilization levels in continuous corn, corn-soybean, and corn-soybean-sorghum-oat/clover rotations. We found that higher cropping complexity coupled with zero fertilization increased gross depolymerization and amino acid consumption rates by 193% and 93%, respectively, relative to fertilized, monocrop plots. Gross mineralization was 2.7 and 3.9x higher in complex rotations than corn-soybean and continuous corn rotations, respectively, while ammonium consumption was 4x higher in fertilized plots than unfertilized plots across all cropping regimes. We show that within our study system internal N cycling is stimulated by cropping system complexity; however, N fertilization suppresses some of the benefits of temporal crop diversification. Balancing reduced mineral fertilizer application rates with increased cropping complexity has the potential to promote internal N cycling while minimizing N losses in agroecosystems.

Relating soil chemical properties to other soil properties and dryland crop production

Soil chemical properties have often been related to some other soil properties and crop yields, but extensive evaluation of the relationships of soil chemical properties with other properties and long-term crop yields under dryland cropping systems is lacking. We related six soil chemical properties (pH, electrical conductivity [EC], cation exchange capacity [CEC], and inorganic P [IP], K, and Al concentrations) with 62 other soil physical, chemical, biological, and biochemical properties and crop yields at two long-term (14- and 36-year old) dryland farming sites in the northern Great Plain, United States. Treatments were rotations of no-tillage and conventional tillage spring wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), pea (Pisum sativum L.), and fallow with or without N fertilization. Soil samples collected to a depth of 0–15 cm in April 2019 were analyzed for soil properties and long-term crop yields were determined. Soil chemical properties were mostly correlated to each other at the short-term than at the long-term site. Based on the principal component analysis, EC, CEC, and IP, and K concentrations were associated with most of the physical, chemical, biological, and biochemical properties at both sites. The CEC, IP, and K concentrations were related to mean crop yields across years at individual or combined sites, but other chemical properties were not related to yields. We conclude that CEC, IP, and K concentrations may be used as potential chemical indicators of soil health that were related to most soil properties and crop yields under dryland cropping systems in the semiarid region.

Spatial Analysis of Soil Properties and Site-Specific Management Zone Delineation for the South Hail Region, Saudi Arabia

Sustainable soil management with the appropriate understanding of soil characteristics is vital in maintaining and improving agriculture soil management. The objectives of the present study are to characterize the spatial variability of soil using the GIS technique and used agglomerative hierarchical clustering (AHC) for the delineation of management zones (MZs) for precision agriculture. A total of 111 soil samples were collected from 37 soil profiles in systematic depths (0–50, 50–100, and 100–150 cm) from the South Hail region, KSA. Samples were analyzed for pH, ECe, CaCO3, available macro and micronutrients, and hydrological properties. The best fit models, using ArcGIS software, were J-Bessel for pH, Clay, bulk density (BD), and available water (AW); K-Bessel for EC and available N; Stable for CaCO3, P, K, Fe, Zn, Sand, field capacity (FC) and saturated hydraulic conductivity (Ks); Spherical for Mn and Cu; Gaussian for saturation percentage (SP); whereas exponential for permanent wilting point (PWP). The principal component analysis (PCA) resulted in six principal components (PCs) explaining 79.75% of the total variance of soil properties. The PC1 was strongly influenced by soil BD, FC, clay, PWP, Ks, and sand. PC2 was dominated by N, ECe, and CaCO3; PC3 was dominated by pH; PC4 was dominated primarily by K and P, PC5 was mainly dominated by Fe; Mn, and Cu, and PC6 was mainly dominated by SP and Zn. Based on AHC, four soil management zones (MZs) cover 77.94, 14.10, 7.11 and 0.85% of the studied area. Management zone 1 (MZ1) and Management zone 3 (MZ3) are classified as moderately saline while Management zone 2 (MZ2) is classified as highly saline soils, greater than the limiting critical value for the sensitive crops. The potential solutions to reduce salinization in the area include: reducing irrigation, moving to salt-tolerant crops or applying humic acids to fix anions and cations and eliminate them from the root zone of the plants. Treating the area with diluted sulfuric acid to remove salts and reduce ECe to less than 2 dSm−1, to get maximum productivity. This finding is diagnostic for determining the amount of fertilizer and irrigation water to be applied to soils in different management zones. Its emphasis’s the importance of site-specific management for long-term crop productivity and, as a result, reducing environmental hazards caused by uneven fertilizers and water applications.

Soil tillage rather than crop rotation determines assembly of the wheat rhizobacterial communities

Root-associated bacterial activity processes are key requirements for agricultural production, yet we have limited understanding about the processes and drivers of rhizobacterial community assembly under typical farming practices. Herein we assessed the rhizobacterial diversity, co-occurrence network connectivity, and assembly processes of dryland wheat rhizobacterial communities and its environmental drivers under a long-term crop rotation (maize-wheat, MW; soybean-wheat, SW) × soil tillage (chisel plow tillage, CPT; zero tillage, ZT; plow tillage, PT) system. The results indicated that crop rotation, soil tillage, and their interactions substantially affected the edaphic properties, where both CPT and ZT increased the levels of soil moisture, pH, organic carbon, and total nitrogen, and SW increased the levels of soil pH and total nitrogen. Compared with MW, SW increased the relative abundance of Proteobacteria (5.82%), while decreased the relative abundances of Firmicutes (22.96%) and Patescibacteria (20.98%). Regardless of crop rotation, there were significant differences in the rhizobacterial community composition among three tillage practices. Rotation × tillage interaction exerted stronger effect on the community composition than their individual contributions. The rhizobacterial network was more densely connected under the SW (edges = 2555, density = 0.122) than that under the MW (edges = 1785, density = 0.082), and the network connectivity showed a decreasing tendency with decreasing tillage intensity. Crop rotation changed the proportions of deterministic and stochastic processes, while soil tillage determined the homogenizing dispersal dominated rhizobacterial community assembly for both MW and SW, due mainly to its significant effects on the soil moisture, total nitrogen, pH, and community diversity. Collectively, these findings provide a theoretical overview of agronomic practice-driven alteration of the rhizobacterial communities, and are expected to provide support for microbiome manipulation and adaptive management toward a more sustainable agriculture under dryland conditions.

Residue incorporation and organic fertilisation improve carbon and nitrogen turnover and stabilisation in maize monocropping

Residue incorporation and organic fertilisation are recommended to increase soil organic matter (SOM) content, thus promoting the provision of multiple ecosystem services. However, the positive effect of crop residue on SOM is often considered rather low, thus requiring a deeper knowledge of their management. In addition, organic fertilisation is thought to be less efficient than mineral. In this context, it is important to understand the response of SOM pools to long-term crop residue incorporation and organic fertilisation and their effect on nutrient cycling and on feed production, in order to judge the sustainability of these practices. We carried out an in-depth multidisciplinary survey to investigate the effect of 28 years of residue incorporation combined with three different nitrogen (N) fertilisation strategies (manure, slurry and mineral) on density fractionated SOM pools differing for their turnover time, and on soil enzymatic activity in a monocropping maize system in NW Italy. Results showed that in the long-term crop production was not altered by organic fertilisation. Organic fertilisation in combination with residue incorporation led to the highest total organic C and total N content down to 90 cm, which was reflected in each SOM pool. In addition, regular applications of crop residue and manures markedly increased C- and N-degrading enzymes, thus enhancing the turnover rates of C and N. We conclude that combining crop residue with organic fertilisation enhanced the provision of regulating services and soil activity, and is a valid approach for maintaining sustainable production in agroecosystems.