Crop Rotation Patterns Research Articles

Regulation of crop rotation patterns on soil labile organic carbon, carbon-degrading microorganisms and their roles in organic carbon mineralization

Regulation of crop rotation patterns on soil labile organic carbon, carbon-degrading microorganisms and their roles in organic carbon mineralization

Geospatial analysis of California strawberry fields reveals regional differences in crop rotation patterns and the potential for lengthened rotations at current levels of production

Geospatial analysis of California strawberry fields reveals regional differences in crop rotation patterns and the potential for lengthened rotations at current levels of production

Maize, Peanut, and Millet Rotations Improve Crop Yields by Altering the Microbial Community and Chemistry of Sandy Saline-Alkaline Soils.

Crop rotation increases crop yield, improves soil health, and reduces plant disease. However, few studies were conducted on the use of intensive cropping patterns to improve the microenvironment of saline soils. The present study thoroughly evaluated the impact of a three-year maize-peanut-millet crop rotation pattern on the crop yield. The rhizosphere soil of the crop was collected at maturity to assess the effects of crop rotation on the composition and function of microbial communities in different tillage layers (0-20 cm and 20-40 cm) of sandy saline-alkaline soils. After three years of crop rotation, the maize yield and economic benefits rose by an average of 32.07% and 22.25%, respectively, while output/input grew by 10.26%. The pH of the 0-40 cm tillage layer of saline-alkaline soils decreased by 2.36%, organic matter rose by 13.44%-15.84%, and soil-available nutrients of the 0-20 cm tillage layer increased by 11.94%-69.14%. As compared to continuous cropping, crop rotation boosted soil nitrogen and phosphorus metabolism capacity by 8.61%-88.65%. Enrichment of Actinobacteria and Basidiomycota increased crop yield. Crop rotation increases microbial community richness while decreasing diversity. The increase in abundance can diminish competitive relationships between species, boost synergistic capabilities, alter bacterial and fungal community structure, and enhance microbial community function, all of which elevate crop yields. The obtained insights can contribute to achieving optimal management of intensive cultivation patterns and green sustainable development.

Multi-year crop rotation and quicklime application promote stable peanut yield and high nutrient-use efficiency by regulating soil nutrient availability and bacterial/fungal community.

Diversifying cultivation management, including different crop rotation patterns and soil amendment, are effective strategies for alleviating the obstacles of continuous cropping in peanut (Arachis hypogaea L.). However, the peanut yield enhancement effect and temporal changes in soil chemical properties and microbial activities in response to differential multi-year crop rotation patterns and soil amendment remain unclear. In the present study, a multi-year localization experiment with the consecutive application of five different cultivation managements (including rotation with different crops under the presence or absence of external quicklime as soil amendment) was conducted to investigate the dynamic changes in peanut nutrient uptake and yield status, soil chemical property, microbial community composition and function. Peanut continuous cropping led to a reduction in peanut yield, while green manure-peanut rotation and wheat-maize-peanut rotation increased peanut yield by 40.59 and 81.95%, respectively. A combination of quicklime application increased yield by a further 28.76 and 24.34%. Alterations in cultivation management also strongly affected the soil pH, nutrient content, and composition and function of the microbial community. The fungal community was more sensitive than the bacterial community to cultivation pattern shift. Variation in bacterial community was mainly attributed to soil organic carbon, pH and calcium content, while variation in fungal community was more closely related to soil phosphorus content. Wheat-maize-peanut rotation combined with quicklime application effectively modifies the soil acidification environment, improves the soil fertility, reshapes the composition of beneficial and harmful microbial communities, thereby improving soil health, promoting peanut development, and alleviating peanut continuous cropping obstacles. We concluded that wheat-maize-peanut rotation in combination with quicklime application was the effective practice to improve the soil fertility and change the composition of potentially beneficial and pathogenic microbial communities in the soil, which is strongly beneficial for building a healthy soil micro-ecology, promoting the growth and development of peanut, and reducing the harm caused by continuous cropping obstacles to peanut.

Quantifying aboveground biomass, soil organic carbon and erosion with a detailed crop map and PESERA model in the Yangtze River Basin

AbstractSoil erosion represents a primary threat to soil systems with adverse implications for ecosystem services, crop production, potable water and carbon storage. While numerous studies have quantified the spatial distribution of aboveground Biomass (AGB), soil erosion and soil organic carbon (SOC) in the Yangtze River Basin (YRB), limited attention has been given to assessing the contributions of different land use types and especially crop types to AGB, soil erosion and SOC. In most studies, cropland is taken as a land use class, while detailed crop types and rotation patterns, and their effect on soil erosion and SOC, vary significantly. In this study, we used the Metronamica model to generate a detailed crop rotation and distribution map across the YRB and subsequently employed the Pan‐European Soil Erosion Risk Assessment (PESERA) model to simulate the spatial distribution of AGB, soil erosion and SOC on a monthly basis. PESERA model simulations indicate an average soil erosion rate across the entire YRB of 7.7 ton/ha/yr, with erosion hotspots concentrated in the Sichuan Basin and the central‐southern regions. The southwestern region and western Sichuan show elevated levels of AGB and SOC, while the eastern plains display lower levels. Erosion rates are lowest in areas designated as artificial land, pasture and grassland, whereas croplands and fruit tree plantations experience the highest erosion rates. In terms of crop types, the highest erosion rates and lowest AGB are observed under fallow and potato cultivation, while the lowest erosion rates and highest AGB are found in rice‐wheat rotation fields. To the best of our knowledge, this is the first study taking detailed crop types and patterns into account while evaluating their effect at a relatively large scale (i.e., YRB). These findings can help to develop sustainable soil management and (cropping) conservation strategies.

The state and trends of land use development in Krasnoarmeysky district of the Krasnodar territory

The article analyzes the state and trends in the development of land use in the rice-growing zone of Kuban. The lands of Krasnoarmeysky district were chosen as the object of study, since it is the main rice growing area in Krasnodar region. It has been established that rice production makes significant influence to the nature, as it changes and transforms the environment, and especially land resources. An analysis of indicators characterizing the state of the lands in Krasnoarmeysky district was carried out, and a forecast for each of these indicators was calculated here as well. The results of this forecast until 2035 indicate a gradual decrease of agricultural lands (and arable lands) in the area, that can lead to reduction of the resource potential of agricultural production. The dynamics of indicators of the sown area, gross harvest and yield of rice in Krasnoarmeysky region are considered by the authors. It was found that rice production is growing steadily, however, an analysis of changes in the area under crops and the gross yield of rice indicates the insufficient efficiency of the existing technology for cultivating this crop, based on the intensive use of mineral fertilizers. Forecasting shows huge increase of used mineral fertilizers, accompanied by a reduction of organic substances in the soil and deterioration of the environmental situation. In order to ensure the environmental sustainability of Krasnoarmeysky district, the new ecosystem approach to land use in the rice-growing zone has been proposed, including a set of environmental and resource-saving measures. As a result of the proposed measures, the structure of land use, crop rotation patterns and production technology have to be changed, use environmentally friendly directions, and preserve and improve the conditions of land resources.

Rotational complexity across US counties is currently insufficient to observe yield gains in major crops

Landscape complexity promotes ecosystem services and agricultural productivity, and often encompasses aspects of compositional or configurational land cover diversity across space. However, a key agricultural diversification practice, crop rotation, extends crop land cover complexity concurrently across space and time. Long-term experiments suggest that complex crop rotations can facilitate yield increases in major crops. Using a compiled county-annual panel dataset, we examined whether yield benefits of crop rotational complexity were apparent on a landscape scale in the conterminous US for four major crops between 2008 and 2020. We found that the benefit of rotational complexity was only apparent for cotton and winter wheat, and that the benefit for wheat was driven by one region. Corn exhibited the opposite pattern, wherein higher yields were consistently obtained with lower rotational complexity, while soybean yield appeared relatively insensitive to rotational complexity. Effects of rotational complexity were sometimes influenced by agrochemical usage. Positive effects of rotational complexity were only apparent with high fertilizer for soybean and wheat, and with low fertilizer for cotton. Corn yield in high-complexity, low-yielding counties appeared to improve with high fertilizer inputs. For the overwhelming majority of acres growing these major crops, crop rotation patterns were quite simple, which when combined with the short time span of available data, may explain the apparent discrepancy between long-term experiments and nationwide data. Current demand and incentives that promote highly intensified and specialized agriculture likely hinder realization of the benefits of rotational complexity for production of key crops in the US. Increasing rotational complexity where major crops are grown thus remains an underutilized approach to mitigate landscape simplification and to promote ecosystem services and crop yields.

Boosting crop classification by hierarchically fusing satellite, rotational, and contextual data

Accurate early-season crop type classification is crucial for the crop production estimation and monitoring of agricultural parcels. However, the complexity of the plant growth patterns and their spatio-temporal variability present significant challenges. While current deep learning-based methods show promise in crop type classification from single- and multi-modal time series, most existing methods rely on a single modality, such as satellite optical remote sensing data or crop rotation patterns. We propose a novel approach to fuse multimodal information into a model for improved accuracy and robustness across multiple crop seasons and countries. The approach relies on three modalities used: remote sensing time series from Sentinel-2 and Landsat 8 observations, parcel crop rotation and local crop distribution. To evaluate our approach, we release a new annotated dataset of 7.4 million agricultural parcels in France (FR) and the Netherlands (NL). We associate each parcel with time-series of surface reflectance (Red and NIR) and biophysical variables (LAI, FAPAR). Additionally, we propose a new approach to automatically aggregate crop types into a hierarchical class structure for meaningful model evaluation and a novel data-augmentation technique for early-season classification. Performance of the multimodal approach was assessed at different aggregation levels in the semantic domain, yielding to various ranges of the number of classes spanning from 151 to 8 crop types or groups. It resulted in accuracy ranging from 91% to 95% for the NL dataset and from 85% to 89% for the FR dataset. Pre-training on a dataset improves transferability between countries, allowing for cross- domain and label prediction, and robustness of the performances in a few-shot setting from FR to NL, i.e., when the domain changes as per with significantly new labels. Our proposed approach outperforms comparable methods by enabling deep learning methods to use the often overlooked spatio-temporal context of parcels, resulting in increased precision and generalization capacity.

Effects of Continuous Annual Crop Rotation and Fallow on Soil Aggregate Stability and Organic Carbon

In order to explore the effects of continuous annual crop rotation and fallow on aggregate stability and organic carbon content in red soil, the red soil in sloping farmland was taken as the research object, and the water-stable aggregates and organic carbon content were determined using the wet sieve method and potassium dichromate-concentrated sulfuric acid external heating method, respectively. The changes in soil aggregate stability and organic carbon content under the four treatments of maize-vetch-maize rotation (M-V-M), maize-pea-maize rotation (M-P-M), maize-fallow-maize (M-F-M), and annual fallow (F-F-F) from 2020 to 2022 and the relationships between them were analyzed. The results showed that in 2021 and 2022, the contents of > 2 mm aggregates treated with F-F-F, M-V-M, and M-P-M were significantly increased by 67.01%-100.92%, 29.71%-33.67%, and 29.68%-38.07%, respectively, compared with that treated with M-F-M. In 2021 and 2022, the stability parameters of F-F-F and M-V-M were significantly higher than those of M-F-M (P < 0.05). The content of > 2 mm aggregates, geometric mean diameter (GMD), and mean weight diameter (MWD) under the M-V-M treatment and R0.25 (> 0.25 mm aggregate contents), MWD and > 2 mm aggregate contents under the F-F-F treatment increased with the increase in fallow years, whereas the content of 1-2 mm and < 0.25 mm under the F-F-F treatment decreased with the increase in fallow years. Both green manure rotation and fallow treatment could increase the SOC content, and the SOC content of F-F-F and M-V-M treatment increased with the extension in age. Correlation analysis showed that SOC content was significantly positively correlated with R0.25 and GMD under all treatments. R0.25 and GMD under the F-F-F treatment and GMD and MWD under M-V-M were significantly positively correlated with SOC content. The results showed that continuous annual crop rotation and fallow was beneficial to improve the content of soil macro-aggregates, aggregate stability, and SOC content, which could provide theoretical basis for the implementation of reasonable continuous annual crop rotation and fallow patterns and soil erosion control in red soil areas of sloping farmland in southern China.

Responses of Yield and Photosynthetic Characteristics of Rice to Climate Resources under Different Crop Rotation Patterns and Planting Methods.

Climate is the most important environmental factor influencing yield during rice growth and development. To investigate the relationships between climate and yield under different crop rotation patterns and planting methods, three typical rotation patterns (vegetable-rice (V), rape-rice (R), and wheat-rice (W)) and two mechanical planting methods (mechanical transplanting (T1) and mechanical direct seeding (T2)) were established. The results showed that compared to the V rotation pattern, the average daily temperature (ADT) during the sowing to heading stage increased under both R and W rotation patterns, which significantly shortened the growth period. Thus, the effective accumulated temperature (EAT), photosynthetic capacity, effective panicle (EP), and spikelet per panicle (SP) under R and W rotation patterns significantly decreased, leading to reductions in grain yield (GY). VT2 had a higher ratio of productive tillers (RPT), relative chlorophyll content (SPAD), leaf area index (LAI), and net photosynthetic rate (Pn) than those of VT1, which significantly increased panicle dry matter accumulation (DMA), resulting in an increase in GY. Although RT2 and WT2 had a higher RPT than those of RT1 and WT1, the GY of RT1 and WT1 decreased due to the significant reductions in EAT and photosynthetic capacity. Principal component analysis (PCA) showed that the comprehensive score for different rotation patterns followed the order of V > R > T with VT2 ranking first. The structural equation model (SEM) showed that EAT and ADT were the most important climate factors affecting yield, with total effects of 0.520 and -0.446, respectively. In conclusion, mechanical direct seeding under vegetable-rice rotation pattern and mechanical transplanting under rape-rice or wheat-rice rotation pattern were the rice-planting methods that optimized the climate resources in southwest China.

Improving the Key Enzyme Activity, Conversion Intensity, and Nitrogen Supply Capacity of Soil through Optimization of Long-Term Oilseed Flax Rotation Planting Patterns in Dry Areas of the Loess Plateau of China

Various crop rotation patterns can result in differences in nutrient consumption and the accumulation of toxic substances in the soil, indirectly impacting the soil environment and its nutrient supply capacity. Implementing optimized crop planting practices is beneficial for maintaining the favorable physical and chemical properties of farmland soil in the arid area of northwestern China. This study aimed to establish a crop rotation pattern to improve key enzyme activities and soil nitrogen conversion efficiency, as well as understand the underlying mechanism for enhancing nitrogen supply capacity. A field experiment was conducted to study the effect of four flax planting patterns, which included 13 crop rotation patterns with different crop frequencies: 100% Flax (Cont F), 50% Flax (I) (WFPF, FPFW, PFWF, FWFP), 50% Flax (II) (FWPF, WPFF, PFFW, FFWP), 25% Flax (WPWF, PWFW, WFWP, FWPW), on the key enzyme activities and the rate of soil nitrogen conversion, as well as the nitrogen supply capacity. Here, F, P, and W represent oilseed flax, potato, and wheat, respectively. The results indicated that the wheat stubble significantly increased the intensity of soil ammonification and denitrification before planting. Additionally, the activity levels of soil nitrate reductase and nitrite reductase under wheat stubble were significantly increased by 66.67% to 104.55%, while soil urease activity significantly decreased by 27.27–133.33% under wheat stubble compared to other stubbles. After harvest, the activities of soil nitrate reductase and nitrite reductase under the wheat stubble decreased significantly, and the intensity of soil ammonification, nitrification, and denitrification reduced significantly by 7.83–27.72%. The WFWP and FWFP treatments led to a significant increase in soil nitrogen fixation intensity under various crop rotations after harvest and significantly increased the levels of inorganic nitrogen in the soil before the planting of the next crop. This study suggests that the long-term rotation planting patterns WFWP and FWFP can significantly enhance the key enzyme activities of soil nitrogen conversion and significantly improve soil nitrogen conversion before crop sowing. This may increase the rate of soil nitrogen transfer and raise the available nitrogen content of the soil. These findings are crucial for reducing soil nitrogen loss and improving soil nitrogen nutrient supply capacity in dry areas of the Loess Plateau of China.

Effects of cropping patterns on the distribution, carbon contents, and nitrogen contents of aeolian sand soil aggregates in Northwest China

The long-term physicochemical responses of aeolian sandy soil aggregates to different crop rotation patterns are poorly understood. Here, we collected soil samples from the 0 to 20 cm tillage layer of continuous maize crop and alfalfa–maize rotation plots situated on the edge of the Zhangye Oasis, Northwest China. These samples were analyzed to quantify the influence of both cropping patterns on the structure, carbon content, and nitrogen content of aeolian sandy soils. When compared with long-term continuous maize cropping, planting alfalfa–maize rotation system significantly increased the mass fraction of macro-aggregates with sizes of > 2 mm and 0.25–2 mm from 8.7 to 12.1% and 19.1 to 21.2%, respectively, but decreased the mass fraction of micro-aggregates (0.053–0.25 mm) from 8.1 to 6.2%. Further, there was no significant difference in the content of silt and clay particles between each system. The alfalfa–maize rotation increased the stability of aggregates from 32 to 37%, representing an increase of 15.6%. Soil organic carbon, inorganic carbon, and total nitrogen were mainly enriched in macro-aggregates with sizes of > 2 mm, and silt and clay fractions for both cropping patterns. Implementation of a rotation pattern increased organic carbon contents by 27.2%, 25.6%, 26.7%, and 27.6%, inorganic carbon contents by 14.4%, 4.5%, 53.3%, and 21.0%, and total nitrogen contents by 29.7%, 7.0%, 4.2%, and 50.0% in aggregate particle sizes of > 2 mm, 0.25–2 mm, 0.053–0.25 mm, and < 0.053 mm, respectively, when compared to continuous maize cropping. The alfalfa–maize crop rotation can therefore effectively improve soil aggregate composition and aggregate stability, alongside organic carbon content, inorganic carbon content, total nitrogen content, and their storage capacity. This system thus represents a soil cultivation technique that can increase the soil carbon sequestration capacity in the oasis zone of Northwest China.

Response of Productivity of Oilseed Flax Farmland to Different Crop Rotation Patterns Based on DSSAT Modeling

Abstract To further study the effect of different crop rotation patterns on the productivity of oilseed flax. In this study, the “Jinya No. 10” flax cultivar was used as the object, and a DSSAT model was constructed using 2017-2018 data to simulate the field trials (4-year rotation cycle) during the 30 years from 1994. The experiments were designed with six different crop rotation patterns including the following: flax→flax→flax→flax[(F)FFF], flax→wheat→maize→flax[(F)WMF], flax→maize→flax→wheat[(F)MFW], flax→flax→wheat→maize[(F)FWM], flax→wheat→flax→maize [(F)WFM], flax→wheat→maize→wheat[(F)WMW]. We investigated the effects of crop stubble, planting frequency of oilseed flax, years between plantings of oilseed flax, and years of continuous cropping on grain yield, aboveground biomass, and water use efficiency (WUE) in a semi-arid agricultural area. The results of the study showed that: (1) In the model calibration and validation, the RMSE of yield was 213.67 kg ha−1−217.43 kg ha−1, the RRMSE was 9.76%-10.79%; the RMSE of aboveground biomass was 796.24 kg ha−1−1527.81kg ha−1, the RRMSE was 13.46%-22.71%. The growing period of the cultivar was 95-97 d, indicating that the DSSAT model can simulate the productivity index of oilseed flax well. (2) Oilseed flax yield rotation than continuous mode significantly increased, the increase in 53.43%-54.28%, wheat, and maize stubble both significantly increased oilseed flax yield, compared with oilseed flax stubble increased by 31.04%, 31.95%. 25% oilseed flax frequency and 50% oilseed flax frequency than 100% oilseed flax planting frequency was significantly increased by 54.28% and 53.79%. The increase in grain yield of oilseed flax in the planting interval years was shown as 2a (32.97%) &gt; 3a (31.51%) &gt; 1a (30.84%). (3) The aboveground biomass of oilseed flax in the crop rotation compared to the continuous cropping pattern had a significant increase in the increase ranged from 60.49% to 100.31%. Wheat and maize stubble significantly increased the aboveground biomass of oilseed flax, compared with oilseed flax stubble increased by 25.67% and 22.56%. 25% oilseed flax frequency and 50% oilseed flax frequency than 100% oilseed flax planting frequency significantly increased by 92.02% and 72.81%. Oilseed flax aboveground biomass production in the planting intervals between the years of the increase in the performance of the 3a (39.8%) &gt; 2a (28.99%) &gt; 1a (19.45%). (4) The WUE of rotation compared to the continuous cropping mode increased between 45.78% and 58.54% for flax. The presence of wheat and maize stubble significantly increased the WUE of oilseed flax, compared to stubble of oilseed flax, which increased by 29.32% and 32.41%. 25% flax frequency and 50% flax frequency than 100% oilseed flax planting frequency significantly increased by 45.77% and 59.73%. Compared to the interval year 0a, the specific increase in WUE showed 2a (33.03%) &gt; 1a (31.37%) &gt; 3a (26.06%). Therefore, the continuous cultivation of oilseed flax will reduce productivity, should choose to rotate farming methods, replace different stubble, reduce the frequency of oilseed flax planting, and extend the interval between years of oilseed flax planting, and flax→wheat→maize→wheat is a suitable crop rotation mode in the northwestern dry zone.

Effects of aftercrop tomato and maize on the soil microenvironment and microbial diversity in a long-term cotton continuous cropping field.

Long-term continuous cropping affects the soil microecological community and leads to nutrient imbalances, which reduces crop yields, and crop rotation can increase soil productivity. To study the effects of the cultivation of tomato (Solanum lycopersicum) and corn (Zea mays) on the microbial community, physical and chemical factors and the structure of aggregates in cotton (Gossypium hirsutum) long-term continuous cropping soils were examined. Four cropping patterns were established, including one continuous cropping pattern and three crop rotation patterns, and the diversity of the soil microecological community was measured using high-throughput sequencing. The physical and chemical properties of different models of soil were measured, and the soil aggregate structure was determined by dry and wet sieving. Planting of aftercrop tomato and corn altered the bacterial community of the cotton continuous soil to a lesser extent and the fungal community to a greater extent. In addition, continuous cropping reduced the diversity and richness of the soil fungal community. Different aftercrop planting patterns showed that there were very high contents of soil organic carbon and organic matter in the cotton-maize rotation model, while the soil aggregate structure was the most stable in the corn-cotton rotation model. Planting tomato in continuous cropping cotton fields has a greater effect on the soil microbial community than planting maize. Therefore, according to the characteristics of different succeeding crop planting patterns, the damage of continuous cropping of cotton to the soil microenvironment can be alleviated directionally, which will enable the sustainable development of cotton production.

Surface temperature adjustment in METRIC model for monitoring crop water consumption in North China Plain

Evapotranspiration is the real water consumption element in agricultural water management. In order to improve the efficiency of agricultural water use and maintain the sustainable development of agriculture, more and more attention has been paid to the improvement of monitoring and management of farmland evapotranspiration. In this study, MODIS data and the Temperature Vegetation Dryness Index (TVDI) were used in the METRIC model to estimate evapotranspiration for winter wheat and summer corn in the North China Plain. In order to decrease the error caused by the spatial heterogeneity of air temperature in the estimation of evapotranspiration, based on the characteristics of cold pixels with surface temperatures close to their air temperature, the TVDI was used to assist the selection of cold pixels and obtain the spatial variation trend of air temperature with latitude from all cold pixels in the study area. The influence of the spatial heterogeneity of air temperature on the surface temperature at the time of the satellite overpass was corrected accordingly, thereby the estimation accuracy of evapotranspiration was improved. A METRIC-TVDI model was established and the evapotranspiration of winter wheat and summer corn in Hebei Plain was estimated from 2017 to 2019. The average evapotranspiration of the winter wheat over these three years were 361 mm, 327 mm and 354 mm respectively, and that of summer corn were 394 mm, 388 mm and 405 mm respectively. Based on the farmland water balance, the irrigation water consumption (evapotranspiration minus precipitation) of winter wheat and summer corn rotation were 324 mm, 134 mm and 360 mm respectively. This kind of crop rotation pattern consumed more groundwater for irrigation, especially the winter wheat. In order to realize the balance of groundwater between exploitation and replenishment in Hebei Plain, more water-saving irrigation technologies should be adopted to reduce the evapotranspiration and improving water use efficiency.

Legume-potato rotation affects soil physicochemical properties, enzyme activity, and rhizosphere metabolism in continuous potato cropping

BackgroundContinuous cropping can reduce soil quality and affect rhizosphere metabolism, ultimately reducing crop yield. Crop rotation can mitigate the damage caused by continuous cropping, but different crop rotation patterns respond differently to soil quality and rhizosphere metabolism. We investigated the effects of different cropping patterns on soil physicochemical properties, enzyme activities, microbial quantity, and rhizosphere metabolism of continuous potato cropping based on a long-term field study from 2018 to 2022. The experiment was set up with the following three treatments: potato (Solanum tuberosum L.)-potato-potato-potato-potato (CK), potato-potato-potato-pea (Pisum arvense L.)-potato (T1), and potato-potato-potato-faba bean (Vicia faba L.)-potato (T2).ResultsThe results showed that pea-potato rotation (T1) and faba bean-potato rotation (T2) significantly improved soil physicochemical properties and microbial quantity, enhanced enzyme activity, and increased yield by 21.19% and 28.38%, respectively, compared with the continuous potato crop. Non-targeted metabolomics analysis showed that the differential metabolites of pea-potato and faba bean-potato rotation were mainly nucleotides, organic acids and derivatives, and flavonoids compared to continuous potato cropping. These differential metabolites are mainly enriched in the ABC transporter, purine metabolism, pyrimidine metabolism, and phenylalanine metabolism pathways. Combined analyses showed that legume-potato rotations improved soil physicochemical properties, enzyme activities, and microbial quantity of continuous potato cropping, ultimately increasing tuber yields. In addition, correlation analyses showed that differential metabolites significantly enriched in purine and phenylalanine metabolism (l-Tyrosine, Trans-Cinnamic acid, Guanine, and Adenine) were also strongly associated with these measurements.ConclusionsTherefore, we conclude that legume-potato rotations modulate the abundance and function of rhizosphere metabolites and significantly alter the low molecular metabolite profile of the soil under continuous potato conditions. Some of these important metabolites may play a part in the cycling of nutrients in the soil, making its physicochemical properties and microbial quantity better, raising the activity of soil enzymes, and ultimately increasing the yield of potato tubers. The above results indicate that legume-potato rotation has a positive effect on continuous potato soils. It lays a solid foundation for revealing the complex molecular network and metabolic pathways of microbial communities in soil after legume crop rotation.Graphical

Is there a future for smallholder farmers in bioeconomy? The case of ‘improved’ seeds in South Punjab, Pakistan

Smallholder farmers are key players in agrarian value chains, particularly in the Global South. In the planning of technology-oriented agricultural interventions featured prominently in bioeconomy policies they are however often neglected. As global demand for food and biomass is expected to rise, production increase through (bio)technological means is framed as a necessity. Yet its ecological and social sustainability has been debated. We add to this debate by investigating the possibilities and challenges for smallholder farmers to participate in the intensification of production in an emerging bioeconomy. We scrutinize the case of Pakistan, an agricultural country where 65% of farms operate less than 2 ha of land and where bioeconomy approaches such as biotechnology and advanced plant breeding have gained momentum in policy debates. We specifically analyze a cornerstone of the bioeconomy value chain—namely ‘improved’ seed varieties by looking at the experiences of smallholder farmers with genetically modified cotton and hybrid maize. We build on qualitative data from South Punjab collected between 2019 and 2022. Smallholders value improved seeds. However, the poorest strata are hindered from adopting improved seed varieties due to lack of resources, established crop rotation patterns, and frequent oscillations of the cropping trends. Market and climatic factors also limit the profitability of improved seed varieties as higher input costs disproportionately affect smallholder farmers. Furthermore, highly productive crops and frequent crop cycles result in surging tenancy rates for smallholders and can lead to their expulsion from agriculture. Our results contribute to the understanding of the complex role of smallholder farmers in the Global South under a bioeconomy scenario.

Effects of Maize-Crop Rotation on Soil Physicochemical Properties, Enzyme Activities, Microbial Biomass and Microbial Community Structure in Southwest China.

Introducing cover crops into maize rotation systems is widely practiced to increase crop productivity and achieve sustainable agricultural development, yet the potential for crop rotational diversity to contribute to environmental benefits in soils remains uncertain. Here, we investigated the effects of different crop rotation patterns on the physicochemical properties, enzyme activities, microbial biomass and microbial communities in soils from field experiments. Crop rotation patterns included (i) pure maize monoculture (CC), (ii) maize-garlic (CG), (iii) maize-rape (CR) and (iv) maize-annual ryegrass for one year (Cir1), two years (Cir2) and three years (Cir3). Our results showed that soil physicochemical properties varied in all rotation patterns, with higher total and available phosphorus concentrations in CG and CR and lower soil organic carbon and total nitrogen concentrations in the maize-ryegrass rotations compared to CC. Specifically, soil fertility was ranked as CG > Cir2 > CR > Cir3 > CC > Cir1. CG decreased enzyme activities but enhanced microbial biomass. Cir2 decreased carbon (C) and nitrogen (N) acquiring enzyme activities and soil microbial C and N concentrations, but increased phosphorus (P) acquiring enzyme activities and microbial biomass P concentrations compared to CC. Soil bacterial and fungal diversity (Shannon index) were lower in CG and Cir2 compared to CC, while the richness (Chao1 index) was lower in CG, CR, Cir1 and Cir2. Most maize rotations notably augmented the relative abundance of soil bacteria, including Chloroflexi, Gemmatimonadetes and Rokubacteria, while not necessarily decreasing the abundance of soil fungi like Basidiomycota, Mortierellomycota and Anthophyta. Redundancy analysis indicated that nitrate-N, ammonium-N and microbial biomass N concentrations had a large impact on soil bacterial communities, whereas nitrate-N and ammonium-N, available P, soil organic C and microbial biomass C concentrations had a greater effect on soil fungal communities. In conclusion, maize rotations with garlic, rape and ryegrass distinctly modify soil properties and microbial compositions. Thus, we advocate for garlic and annual ryegrass as maize cover crops and recommend a two-year rotation for perennial ryegrass in Southwest China.

Within-Season Crop Identification by the Fusion of Spectral Time-Series Data and Historical Crop Planting Data

Crop mapping at an earlier time within the growing season benefits agricultural management. However, crop spectral information is very limited at the early crop phenological stages, leading to difficulties for within-season crop identification. In this study, we proposed a deep learning-based fusion method for crop mapping within the growing season, which first learned a priori information (i.e., pre-season crop types) from historical crop planting data and then integrated the a priori information with the satellite-derived crop types estimated from spectral times-series data. We expect that preseason crop types provided by crop rotation patterns is an effective supplement to spectral information to generate reliable crop maps in the early growing season. We tested the proposed fusion method at three representative sites in the U.S. with different crop rotation intensities and one site with cloudy weather conditions in the Sichuan Province of China. The experimental results showed that the fusion method incorporated the strengths of pre-season crop type estimates and the spectral-based crop type estimates and thus achieved higher crop classification accuracy than the two estimates throughout the growing season. We found that pre-season crop estimates had a higher accuracy in the scenarios with either nearly continuous planting or half-time planting of the same crop. In addition, the historical crop type data strongly affected the performance of pre-season crop estimates, suggesting that high-quality historical crop planting data are particularly important for crop identification at earlier times in the growing season. Our study highlighted the great potential for near real-time crop mapping through the fusion of spectral information and crop rotation patterns.

Using Time Series Sentinel Images for Object-Oriented Crop Extraction of Planting Structure in the Google Earth Engine

Timely and accurate extraction of crop planting structure information is of great importance for food security and sustainable agricultural development. However, long time series data with high spatial resolution have a much larger data volume, which seriously limits the quality and efficiency of the application of remote sensing to agriculture in complex crop rotation areas. To address this problem, this paper takes Lujiang County, a typical complex crop rotation region in the middle and lower reaches of the Yangtze River in China as an example, and proposes utilizing the Google Earth Engine (GEE) platform to extract the Normalized Difference Vegetation Index (NDVI), Normalized Difference Yellowness Index (NDYI) and Vertical-Horizontal Polarization (VH) time series sets of the whole planting year, and combining the Simple Non-Iterative Clustering (SNIC) multi-scale segmentation with the Support Vector Machine (SVM) and Random Forest (RF) algorithms to realize the fast and high-quality planting information of the main crop rotation patterns in the complex rotation region. The results show that by combining time series and object-oriented methods, SVM leads to better improvement than RF, with its overall accuracy and Kappa coefficient increasing by 4.44% and 0.0612, respectively, but RF is more suitable for extracting the planting structure in complex crop rotation areas. The RF algorithm combined with time series object-oriented extraction (OB + T + RF) achieved the highest accuracy, with an overall accuracy and Kappa coefficient of 98.93% and 0.9854, respectively. When compared to the pixel-oriented approach combined with the Support Vector Machine algorithm based on multi-temporal data (PB + M + SVM), the proposed method effectively reduces the presence of salt-and-pepper noise in the results, resulting in an improvement of 6.14% in overall accuracy and 0.0846 in Kappa coefficient. The research results can provide a new idea and a reliable reference method for obtaining crop planting structure information efficiently and accurately in complex crop rotation areas.