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Introduction: Crop rotation of tobacco with other crops could effectively break the negative impact of continuous tobacco cropping, but the mechanisms of intercropping system effects on tobacco, especially on the rhizosphere, are not clear. Methods: In this study, we investigated the impact of intercropping system on the diversity and function of tobacco metabolites and microorganisms through metabolomic and metagenomic analyses of the tobacco rhizosphere microenvironment intercropped with maize and soybean. Results: The results showed that the contents of huperzine b, chlorobenzene, and P-chlorophenylalanine in tobacco rhizosphere soils differed significantly among soybean-tobacco and maize-tobacco intercropping system. Chlorobenzene and P-chlorophenylalanine had the highest relative abundance under the soybean-tobacco intercropping system, and huperzine b had the highest relative abundance in the maize-tobacco cropping system. At the phylum level, the three most dominant strains were the same across all treatments: Proteobacteria, Actinobacteria , and Acidobacteria , with only minor differences in their abundance, with the fourth most abundant strain in both the tobacco monoculture. KEGG enrichment analysis of the tobacco rhizosphere soil microbiome revealed that intercropping significantly increased the abundance of metabolites in the ABC transporters pathway and up-regulated the LivK, LivH, Livg, LivM , and LivF genes of the branched-chain amino acid pathway Discussion: Collectively, our results indicate that the intercropping could enhance the activity of Livs to enhance the ABC transport pathway, and thus improve the transmembrane transport ability of tobacco roots, thus reducing the negative impact of continuous tobacco cropping. At the same time, the maize-tobacco intercropping could promote the production and transportation of phenolic acids, flavonoids, and other bioactive substances in the tobacco root system, which could enhance tobacco adaptation capacity to abiotic stress. [ABSTRACT FROM AUTHOR]

IntroductionCrop rotation of tobacco with other crops could effectively break the negative impact of continuous tobacco cropping, but the mechanisms of intercropping system effects on tobacco, especially on the rhizosphere, are not clear.MethodsIn this study, we investigated the impact of intercropping system on the diversity and function of tobacco metabolites and microorganisms through metabolomic and metagenomic analyses of the tobacco rhizosphere microenvironment intercropped with maize and soybean.ResultsThe results showed that the contents of huperzine b, chlorobenzene, and P-chlorophenylalanine in tobacco rhizosphere soils differed significantly among soybean-tobacco and maize-tobacco intercropping system. Chlorobenzene and P-chlorophenylalanine had the highest relative abundance under the soybean-tobacco intercropping system, and huperzine b had the highest relative abundance in the maize-tobacco cropping system. At the phylum level, the three most dominant strains were the same across all treatments: Proteobacteria, Actinobacteria, and Acidobacteria, with only minor differences in their abundance, with the fourth most abundant strain in both the tobacco monoculture. KEGG enrichment analysis of the tobacco rhizosphere soil microbiome revealed that intercropping significantly increased the abundance of metabolites in the ABC transporters pathway and up-regulated the LivK, LivH, Livg, LivM, and LivF genes of the branched-chain amino acid pathwayDiscussionCollectively, our results indicate that the intercropping could enhance the activity of Livs to enhance the ABC transport pathway, and thus improve the transmembrane transport ability of tobacco roots, thus reducing the negative impact of continuous tobacco cropping. At the same time, the maize-tobacco intercropping could promote the production and transportation of phenolic acids, flavonoids, and other bioactive substances in the tobacco root system, which could enhance tobacco adaptation capacity to abiotic stress.

Abstract Background Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf area or biomass. A prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further information about the field treatment. While image-based models provide more flexibility for crop growth modeling than process-based models, there is still a significant research gap in the comprehensive integration of various growth-influencing conditions. Further exploration and investigation are needed to address this gap. Methods We present a two-stage framework consisting first of an image generation model and second of a growth estimation model, independently trained. The image generation model is a conditional Wasserstein generative adversarial network (CWGAN). In the generator of this model, conditional batch normalization (CBN) is used to integrate conditions of different types along with the input image. This allows the model to generate time-varying artificial images dependent on multiple influencing factors. These images are used by the second part of the framework for plant phenotyping by deriving plant-specific traits and comparing them with those of non-artificial (real) reference images. In addition, image quality is evaluated using multi-scale structural similarity (MS-SSIM), learned perceptual image patch similarity (LPIPS), and Fréchet inception distance (FID). During inference, the framework allows image generation for any combination of conditions used in training; we call this generation data-driven crop growth simulation. Results Experiments are performed on three datasets of different complexity. These datasets include the laboratory plant Arabidopsis thaliana (Arabidopsis) and crops grown under real field conditions, namely cauliflower (GrowliFlower) and crop mixtures consisting of faba bean and spring wheat (MixedCrop). In all cases, the framework allows realistic, sharp image generations with a slight loss of quality from short-term to long-term predictions. For MixedCrop grown under varying treatments (different cultivars, sowing densities), the results show that adding these treatment information increases the generation quality and phenotyping accuracy measured by the estimated biomass. Simulations of varying growth-influencing conditions performed with the trained framework provide valuable insights into how such factors relate to crop appearances, which is particularly useful in complex, less explored crop mixture systems. Further results show that adding process-based simulated biomass as a condition increases the accuracy of the derived phenotypic traits from the predicted images. This demonstrates the potential of our framework to serve as an interface between a data-driven and a process-based crop growth model. Conclusion The realistic generation and simulation of future plant appearances is adequately feasible by multi-conditional CWGAN. The presented framework complements process-based models and overcomes their limitations, such as the reliance on assumptions and the low exact field-localization specificity, by realistic visualizations of the spatial crop development that directly lead to a high explainability of the model predictions.

Cropping system diversification is a key factor in developing more sustainable crops and increase food security. A two-year field experiment was conducted at South-East part of Romania, to emphasize the right plant types, both legumes and non-legumes which can be used in intercropping system for organic agriculture. Intercropping pattern with two (Peas + Camelina; Peas + Flax; Peas + Oats; Flax + Oats; Spring Wheat + Camelina and Spring Wheat + Flax) and three species (Peas + Camelina + Spring Wheat; Peas + Flax + Spring wheat; Peas + Flax + Oats; Peas + Camelina + Oats) was used. Sole cropping of peas, camelina, flax, oats and spring wheat were also used. Two sowing rates were tested, at 50% and 100% of the recommended amount of seed. Results showed that averaged across years and intercropping patterns, yields were significantly more increased in mixtures crops compared to sole cropping ones. Through the land equalization ratio (LER) with values greater than 1, the mixtures of crops (of two or three species) that use environmental resources more efficiently and productively were identified. [ABSTRACT FROM AUTHOR]

Background: Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf area or biomass. A prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further information about the field treatment. While image-based models provide more flexibility for crop growth modeling than process-based models, there is still a significant research gap in the comprehensive integration of various growth-influencing conditions. Further exploration and investigation are needed to address this gap. Methods: We present a two-stage framework consisting first of an image generation model and second of a growth estimation model, independently trained. The image generation model is a conditional Wasserstein generative adversarial network (CWGAN). In the generator of this model, conditional batch normalization (CBN) is used to integrate conditions of different types along with the input image. This allows the model to generate time-varying artificial images dependent on multiple influencing factors. These images are used by the second part of the framework for plant phenotyping by deriving plant-specific traits and comparing them with those of non-artificial (real) reference images. In addition, image quality is evaluated using multi-scale structural similarity (MS-SSIM), learned perceptual image patch similarity (LPIPS), and Fréchet inception distance (FID). During inference, the framework allows image generation for any combination of conditions used in training; we call this generation data-driven crop growth simulation. Results: Experiments are performed on three datasets of different complexity. These datasets include the laboratory plant Arabidopsis thaliana (Arabidopsis) and crops grown under real field conditions, namely cauliflower (GrowliFlower) and crop mixtures consisting of faba bean and spring wheat (MixedCrop). In all cases, the framework allows realistic, sharp image generations with a slight loss of quality from short-term to long-term predictions. For MixedCrop grown under varying treatments (different cultivars, sowing densities), the results show that adding these treatment information increases the generation quality and phenotyping accuracy measured by the estimated biomass. Simulations of varying growth-influencing conditions performed with the trained framework provide valuable insights into how such factors relate to crop appearances, which is particularly useful in complex, less explored crop mixture systems. Further results show that adding process-based simulated biomass as a condition increases the accuracy of the derived phenotypic traits from the predicted images. This demonstrates the potential of our framework to serve as an interface between a data-driven and a process-based crop growth model. Conclusion: The realistic generation and simulation of future plant appearances is adequately feasible by multi-conditional CWGAN. The presented framework complements process-based models and overcomes their limitations, such as the reliance on assumptions and the low exact field-localization specificity, by realistic visualizations of the spatial crop development that directly lead to a high explainability of the model predictions. [ABSTRACT FROM AUTHOR]

The importance of habitat spatial variability as a key driver of soil biota patterning (e.g., soil nematodes) has lately gained a lot of attention. It is generally accepted that rhizosphere soil has a distinct faunal assemblage than bulk soil, but less is known about the patterning of soil nematodes and the causes of these changes in maize-alfalfa agroecosystems. As a result, the purpose of this study was to assess the dynamic changes in soil nematodes across bulk and rhizosphere soils when maize and alfalfa were grown separately and in a combination at varying levels of nitrogen fertilizer. The results of a field experiment in a 2 × 3 factorial completely randomized block design revealed that total nematode and omnivore-predator abundance, as well as nematode generic diversity and richness, maturity, and structure indices, were significantly increased in the rhizosphere of monoculture alfalfa and alfalfa grown in a mixture with maize when compared to the bulk soil. Furthermore, we discovered elevated levels of total sugars and organic acids in rhizosphere soils. Plant- and fungal-feeding nematodes increased in both bulk and rhizosphere soils, whereas omnivores and predators decreased in soils treated with monoculture and nitrogen fertilizer. Furthermore, we discovered a significant positive relationship between total nematode and omnivore-predator abundance and soil organic carbon and total nitrogen, soil moisture content, and microbial biomass C and N, implying that changes in these soil properties and rhizodeposition may shape the nematode community assemblage between the bulk and rhizosphere soils. Our findings suggest that crop mixes containing alfalfa would improve soil characteristics and rhizodeposition, resulting in increased nematode number and variety and contributing to sustainable agriculture.

Ecological intensification (EI) is the enhancement of ecosystem services to complement or substitute for the role of anthropogenic inputs in maintaining or increasing yields. EI has potential to increase farming's environmental sustainability, e.g. reducing environmentally harmful management activities while sustaining yields. EI is based upon ecological processes which in turn are influenced by biodiversity. We review how biodiversity, particularly vascular plant diversity, can regulate ecosystem processes relevant to EI at multiple spatial scales. At an individual plant genotype level, complementarity in functional traits has a direct impact on productivity. At in-field, population level, mixtures of crop types confer resilience to minimize the risk of pest and disease incidence and spread. Scaling up to the field level, a diversity of non-crop plants (i.e. weeds) provides resources necessary for in-field functional processes, both below ground (carbon inputs, decomposition) and above ground (resource continuity for pollinators and natural enemies). At the landscape scale, mosaics of semi-natural and managed vegetation provide buffers against extreme events through flood and drought risk mitigation, climate amelioration and pest population regulation. Overall this emphasizes the importance of heterogeneity across scales in maintaining ecosystem functions in farmland. Major research challenges highlighted by our review include the need: to better integrate plant functional diversity (from traits to habitat scales) into cropping system design; to quantify the (likely interactive) contribution of plant diversity for effective EI relative to other management options; and to optimize through targeted management the system function benefits of biodiversity for resilient, efficient and productive agroecosystems. [ABSTRACT FROM AUTHOR]

Plant-soil feedback can influence aboveground interactions between plants and herbivores by affecting plant chemistry. Such interactions can be utilized in pest management. However, cropping systems such as maize-legume intercropping (MLI) can influence these interactions which is not well understood. In this study, we explored effects of MLI systems on soil physico-chemical properties, maize growth, larval feeding and development of fall armyworm (Spodoptera frugiperda). We used sterile soil and soil conditioned by different MLI and maize-monoculture cropping systems to explore these interactions. Soil samples that included soil conditioned by different MLI and maize-monoculture cropping systems were collected from smallholder farmer fields in eastern Kenya, where different MLI and maize-monoculture cropping systems were being practiced. These soil samples were compared with sterile soils for physico-chemical properties using black oxidation and Walkley methods. Three-weeks-old maize plants grown in the different soil treatments in the greenhouse were used for larval feeding and development assays. Neonate S. frugiperda larvae were allowed to feed on maize leaf discs for 24 hours and another set of plants were inoculated with the neonates for 15 days and the larval survival and development monitored. Soil obtained from different maize-edible legume intercropping systems had a higher pH, electrical conductivity, nitrogen, organic carbon, potassium, phosphorus, calcium, magnesium, exchangeable acidity, copper, clay and silt compared to maize-monoculture and sterile soil. Maize plants grown in MLI soil had better growth parameters compared to those in maize-monoculture and sterile soils. A high correlation was found between pH and plant biomass, while no significant correlation with other physico-chemical properties was noted. There were significant differences in larval feeding by S. frugiperda neonates when exposed to constitutive and induced maize leaf discs with more leaf tissue fed on maize grown in maize-monoculture and sterile soil. When allowed to feed for 15 days, S. frugiperda larval weight and length were significantly lower on maize plants grown in soils conditioned by MLI than those grown in soil conditioned by maize-monoculture and sterile soils. Findings from this study show how conditioning soil by MLI systems improve soil health, maize growth and reduces S. spodoptera larval feeding and development.

Abstract Background Legumes can fix atmospheric nitrogen (N) and facilitate N availability to their companion plants in crop mixtures. However, biological nitrogen fixation (BNF) of legumes in intercrops varies largely with the identity of the legume species. The aim of our study was to understand whether BNF and concentration of plant nutrients by common bean is influenced by the identity of the companion plant species in crop mixtures. In this greenhouse pot study, common beans were cultivated with another legume (chickpea) and a cereal (Sorghum). We compared BNF, crop biomass and nutrient assimilation of all plant species grown in monocultures with plants grown in crop mixtures. Results We found beans to exhibit low levels of BNF, and to potentially compete with other species for available soil N in crop mixtures. The BNF of chickpeas however, was enhanced when grown in mixtures. Furthermore, biomass, phosphorous and potassium values of chickpea and Sorghum plants were higher in monocultures, compared to in mixtures with beans; suggesting competitive effects of beans on these plants. Concentration of calcium, magnesium and zinc in beans was higher when grown with chickpeas than with Sorghum. Conclusions It is generally assumed that legumes benefit their companion plant species. Our study highlights the contrary and shows that the specific benefits of cereal-legume mixtures are dependent on the growth rate of the species concerned. We further highlight that the potential of legume-legume mixtures is currently undervalued and may play a strong role in increasing N use efficiency of intercrop-based systems.

Background: Legumes can fix atmospheric nitrogen (N) and facilitate N availability to their companion plants in crop mixtures. However, biological nitrogen fixation (BNF) of legumes in intercrops varies largely with the identity of the legume species. The aim of our study was to understand whether BNF and concentration of plant nutrients by common bean is influenced by the identity of the companion plant species in crop mixtures. In this greenhouse pot study, common beans were cultivated with another legume (chickpea) and a cereal (Sorghum). We compared BNF, crop biomass and nutrient assimilation of all plant species grown in monocultures with plants grown in crop mixtures. Results: We found beans to exhibit low levels of BNF, and to potentially compete with other species for available soil N in crop mixtures. The BNF of chickpeas however, was enhanced when grown in mixtures. Furthermore, biomass, phosphorous and potassium values of chickpea and Sorghum plants were higher in monocultures, compared to in mixtures with beans; suggesting competitive effects of beans on these plants. Concentration of calcium, magnesium and zinc in beans was higher when grown with chickpeas than with Sorghum. Conclusions: It is generally assumed that legumes benefit their companion plant species. Our study highlights the contrary and shows that the specific benefits of cereal-legume mixtures are dependent on the growth rate of the species concerned. We further highlight that the potential of legume-legume mixtures is currently undervalued and may play a strong role in increasing N use efficiency of intercrop-based systems. [ABSTRACT FROM AUTHOR]

Cereal–legume intercropping is a diversification practice that offers many advantages, especially in low-input systems. However, its adoption remains low on European farms, as technical and economic barriers hinder its development. In recent years, an increase in the proportion of arable land cultivated with cereal–legume intercrops has been observed in France. Three areas in particular – in Western, Eastern and Southern France – seem to be particularly dynamic. This study aimed (i) to identify the main farm characteristics associated with the presence of cereal–legume intercrops at the national level in France and (ii) to highlight more specific characteristics that could explain the particular dynamics observed in each focus region. We analysed data from the 2020 French Agricultural Census for 43,968 farms representative of the French arable crop, livestock, and mixed crop–livestock farming systems. Through a literature review, we identified key factors linked to the presence of cereal–legume intercrops and related them to 42 variables in the census. At the national level, the most important of these variables were identified and interpreted using a balanced random forest and a classification and regression tree (CART). We tested the CART obtained at the national level in the Western, Eastern, and Southern areas and conducted a random forest analysis for each area to identify local particularities. At the national level, the presence of cereal–legume intercropping was strongly linked to organic farming and the presence of livestock, especially ruminants. These intercrops were prevalent on farms with high feed autonomy for the cattle and sheep. Additionally, they were commonly observed on farms with grain storage, possibly indicating feed autonomy, on-farm transformation, or marketing outside of agricultural cooperatives. The belonging to a farm machinery cooperative was also strongly associated with cereal–legume intercropping, likely because these cooperatives give farmers access to specific machinery and provide opportunities for knowledge exchange regarding their practices. Similar characteristics were identified at the local level; organic farming was pivotal in the Western and Eastern areas, followed by feed autonomy for cattle. In the Southern area, however, on-farm grain storage capacity was dominant, likely due to longstanding efforts to achieve feed autonomy. This exhaustive study on French farms identified key farm characteristics strongly linked to cereal–legume intercrops adoption. This insight is critical for promoting this practice, whether through national public policies or local farming support services. The methodology proposed can be easily reproduced to investigate other farming practices at different spatial scales. [Display omitted] • A sample of 43,968 French farms was analysed from the French Agricultural Census. • Cereal–legume intercrops are mainly found on organic and/or feed-autonomous farms. • Belonging to a farm machinery cooperative was also linked to C–L intercropping. • The methodology can apply to other agricultural practices at various scales. • Results suggest ways to promote intercropping, e.g. peer exchanges, market access. [ABSTRACT FROM AUTHOR]

Cereal-legume intercrops have numerous advantages over monocultures. However, the intercrop's performance depends on the plant genotypes, management, and environment. Process-based agro-ecosystem models are important tools to evaluate the performance of intercrop systems as field experiments are limited in the number of treatments. The objective of this study was to calibrate and evaluate a new process-based intercrop model using an extensive experimental data set and to test whether the model is suitable for comparing intercrop management strategies. The data set includes all combinations of 12 different spring wheat entries (SW, Triticum aestivum L.) with two faba bean (FB, Vicia faba L.) cultivars, at two sowing densities, in three different environments. The results show that the intercrop model was capable of simulating the absolute mixture (intercrop) effects (AME) for grain yield, above-ground biomass, and topsoil root biomass, for both crops. However, the intercrop model does not perform better than a benchmark that ignores the intercrop effects when simulating plant height, fraction of intercepted radiation, volumetric soil water content, and subsoil root biomass. The intercrop model predicted reasonably well the differences between species and between SW cultivars for grain yield and aboveground plant biomass. Overall, the tested process-based model can be a useful tool for designing and pre-evaluation multiple combinations of crop management, species, and cultivars suitable for intercropping in diverse conditions. • A new intercrop model was tested against extensive experimental field intercrop data. • We used "no intercrop effect" as a benchmark to quantify the skill of the intercrop model. • The model successfully simulated grain yield, shoot, and root biomass per species. • The model was able to simulate species, cultivars, and environmental differences. [ABSTRACT FROM AUTHOR]

Context: Crop rotations, within-field mixtures, and landscape mosaics including susceptible and resistant crops are three commonly adopted crop diversification strategies that can limit crop epidemics. Typically, the effects of crop diversification at these three scales have been studied separately, on single pathogen species, and with low environmental variability. Objectives: We aim to compare the disease-limitation effect of these three types of crop diversification on two highly damaging fungal pathogens of wheat Puccinia recondita (WLR) and Zymoseptoria tritici (STB) and under varying weather conditions (warmer or cooler climate for WLR, wetter or drier conditions for STB). Methods: We built a dynamic mathematical model of epidemics at the field scale (based on classical Susceptible-Exposed-Infectious-Removed epidemiological models) embedded in a spatially explicit landscape grid framework. We use it to simulate an agricultural landscape in which diversification translates into different proportions of wheat and resistant crops in the landscape. Results: In our simulations, for both pathogens and in all weather conditions, within-field crop mixtures had the greatest impact in limiting epidemics, crop rotations were second-best, while landscape mosaics were the least effective. We also found that the threshold above which further addition of resistant plants to crop mixtures would not cause further disease limitation to be dependent on weather conditions. The more favorable the weather is for pathogens the more resistant plants are required. Conclusions: Our findings imply that interactions between spatial scale of crop diversification, pathogen characteristics and weather conditions should be considered in order to maximize benefits from disease-regulation properties of diversified cropping systems under climate change. [ABSTRACT FROM AUTHOR]

Crop diversification through intercropping is known to suppress disease severity and incidence. Strip cropping is an adaptation of intercropping in which strips are made wide enough e.g. 3 m or wider to allow management with tractor-pulled equipment. There is, however, little evidence of the efficacy of disease suppression in strip cropping. Furthermore, it is unclear how and to which extent the choice of companion crop species affects the suppression of diseases. Here we determine how potato late blight, caused by Phytophthora infestans , is affected by strip cropping potatoes with three different companion crops: grass, maize or faba bean. Potato late blight severity and tuber yield were determined in field experiments in the Netherlands during three years that differed in both weather conditions and timing of the onset of the epidemic. Strip cropping with grass or maize lowered disease severity compared with potatoes grown in monoculture. Across the three years, the average severity over the observation period was significantly lower in the strip-crop with grass (0.040) or in the strip-crop with maize (0.053) than in the potato monoculture (0.105). Strip-cropping with faba bean did not significantly reduce the average severity. In 2021 and 2022, strip cropping with grass resulted in the highest potato yields (per m2 potato area) (25.9 and 38.9 t ha−1 potato area in 2021 and 2022, respectively), which was 31–33 % higher than the monoculture (19.8 and 29.2 t ha−1). Despite the observed reduction in disease in potato strip-cropped with maize, it resulted in similar yield per unit area of potato as the monoculture, presumably due to competition for light with the taller maize plants. Together these results show that strip cropping, when integrated with other control measures, can be used to reduce late blight severity. A short non-competitive companion crop species, grass, was effective in simultaneously reducing late blight and enhancing tuber yield. • Strip cropping lowered late blight severity compared to potato monoculture. • Strip cropping with both grass or maize reduced potato late blight severity. • Grass as a companion was slightly more effective than maize for disease suppression. • Potatoes strip-cropped with grass yielded more than achieved in potato monoculture. • Strip cropping can thus be used a disease control strategy. [ABSTRACT FROM AUTHOR]

Compared to sole crops, intercropping—especially of legumes and cereals—has great potential to improve crop yield and resource use efficiency, and can provide many other ecosystem services. However, the beneficial effects of intercrops are often greatly dependent on the end use as well as the specific species and genotypes being co-cultivated. In addition, intercropping imposes added complexity at different levels of the supply chain. While the need for developing crop genotypes for intercropping has long been recognized, most cultivars on the market are optimized for sole cropping and may not necessarily perform well in intercrops. This paper aims to place breeding targets for intercrop-adapted genotypes in a supply chain perspective. Three case studies of legumes and cereals intercropped for human consumption are used to identify desirable intercrop traits for actors across the supply chains, many of which are not targeted by traditional breeding for sole crops, including certain seed attributes, and some of which do not fit traditional breeding schemes, such as breeding for synchronized maturity and species synergies. Incorporating these traits into intercrop breeding could significantly reduce complexity along the supply chain. It is concluded that the widespread adoption and integration of intercrops will only be successful through the inclusion and collaboration of all supply chain actors, the application of breeding approaches that take into account the complexity of intercrop supply chains, and the implementation of diversification strategies in every process from field to fork. [ABSTRACT FROM AUTHOR]

Compared to sole crops, intercropping—especially of legumes and cereals—has great potential to improve crop yield and resource use efficiency, and can provide many other ecosystem services. However, the beneficial effects of intercrops are often greatly dependent on the end use as well as the specific species and genotypes being co-cultivated. In addition, intercropping imposes added complexity at different levels of the supply chain. While the need for developing crop genotypes for intercropping has long been recognized, most cultivars on the market are optimized for sole cropping and may not necessarily perform well in intercrops. This paper aims to place breeding targets for intercrop-adapted genotypes in a supply chain perspective. Three case studies of legumes and cereals intercropped for human consumption are used to identify desirable intercrop traits for actors across the supply chains, many of which are not targeted by traditional breeding for sole crops, including certain seed attributes, and some of which do not fit traditional breeding schemes, such as breeding for synchronized maturity and species synergies. Incorporating these traits into intercrop breeding could significantly reduce complexity along the supply chain. It is concluded that the widespread adoption and integration of intercrops will only be successful through the inclusion and collaboration of all supply chain actors, the application of breeding approaches that take into account the complexity of intercrop supply chains, and the implementation of diversification strategies in every process from field to fork.

Increasing biodiversity generally enhances productivity through selection and complementarity effects not only in natural, but also in agricultural, systems. However, the quest to explain why diverse cropping systems are more productive than monocultures remains a central goal in agricultural science. In a mesocosm experiment, we constructed monocultures, two‐ and four‐species mixtures from eight crop species with or without fertilizer and both in temperate Switzerland and dry, Mediterranean Spain. We measured physical factors and plant traits and related these in structural equation models to selection and complementarity effects to explain seed yield differences between monocultures and mixtures. Increased crop diversity increased seed yield in Switzerland. This positive biodiversity effect was driven to almost the same extent by selection and complementarity effects, which increased with plant height and specific leaf area (SLA), respectively. Also, ecological processes driving seed yield increases from monocultures to mixtures differed from those responsible for seed yield increases through the diversification of mixtures from two to four species. Whereas selection effects were mainly driven by one species, complementarity effects were linked to larger leaf area per unit leaf weight. Seed yield increases due to mixture diversification were driven only by complementarity effects and were not mediated through the measured traits, suggesting that ecological processes beyond those measured in this study were responsible for positive diversity effects on yield beyond two‐species mixtures. By understanding the drivers of positive biodiversity–productivity relationships, we can improve our ability to predict species combinations that enhance ecosystem functioning and can promote sustainable agricultural production. [ABSTRACT FROM AUTHOR]

The present study was conducted in Sulaimani region at two different locations, Kanipanka and Qlyasan during winter season of 2019-2020 to estimate the response of forage yield and some competition indices to the effect of crop pure stands and their mixtures of barley and triticale intercropped with narbon vetch and grass pea with some different patterns. The experiment was designed according to Completely Randomized Block Design with three replications. As the average of both location the maximum green forage yield was produced by pure narbon vetch 32.610 ton ha-1, while pure barley produce maximum dry forage yield and dry matter % reached 5.506 ton ha-1 and 8.55% at booting stage respectively, but the crop mixture barley/grass pea at a rate 2:1 produce maximum green and dry forage yield 32.083 and 5.616 ton ha-1 respectively at booting stage. The crop mixture barley/vetch 1:1 gave maximum dry matter% 17.88% at the same stage. The highest value for total LER was 1.401recorded by the mixture of triticale/grass pea at elongation stage, while the highest relative crowding coefficient was 1.285 recorded by the same mixture at a rate 1:1 at the same cutting stage. Maximum competitive ratio for cereals was 3.652 recorded by barley in the mixture barley/grass pea 1:2 at elongation stage, while for legume it was 2.292 for narbon vetch in the mixture triticale/vetch 2:1 at booting stage. [ABSTRACT FROM AUTHOR]

Weeds remain a challenge in organic arable farming, as well as supply ecosystem services. The aim is to control weed densities while hosting a diverse and manageable weed community, preventing domination of few deleterious species. Therefore, we want to understand how specific species are stimulated, and which traits are selected for. This study focuses on crop diversity hypothesizing that (1) regions and (2) crop diversity function as filters for specific weed species traits. We conducted a weed monitoring in spring cereals over 2 years on organic farms in five northern European regions. Management and weed trait variables collected for the occurring species allowed an RLQ fourth-corner analysis. The weed communities were regionally specific, but trait selection was not observed, except in Latvia. Hence, the regional species pool provided different species with similar traits. Crop diversity within the management of spring cereals, such as undersowing and cereal frequency in the rotation, affected weed traits. The number of years under organic production selected no traits, although species numbers are known to increase. Hence, general weed species diversity increased, irrespective of traits. We conclude that organic management may support the agility within the weed community against selection of species and act as a buffer rather than as filter.

Experimental studies to date have demonstrated the agronomic and environmental benefits of intercropping, making it a key diversification method for reducing chemical inputs in agriculture. However, intercropping is still a niche practice in European cropping systems, particularly for arable crops. Few studies have focused on farmers' perspectives or used farm data to assess the on-farm performances of intercropping. Here, we present an analysis of data collected from farms of the DEPHY network, a demonstration farm network that aims to show that pesticide use can be reduced through changes in farming practices. We focused our study on four main species in France: winter wheat (Triticum aestivum L.) , winter barley (Hordeum vulgare L.), pea (Pisum sativum L.) and rapeseed (Brassica napus L.). We carried out paired comparison tests between sole crops and intercrops for each species (16 pairs for winter wheat, 12 for winter barley, 15 for peas and 31 for rapeseed) to compare the use of pesticides (herbicides, fungicides, insecticides and all pesticides combined), mineral nitrogen fertiliser and the gross margin. We showed that pesticide use was reduced on average by 40–50% in the case of wheat- and barley-based intercrops compared with sole wheat and barley crops, respectively. Pesticide use for peas was reduced by 72% on average. Nitrogen fertiliser use was also reduced by up to 38% for wheat. On the other hand, in the case of rapeseed, which is mainly intercropped with unharvested companion plants, we found no significant differences in pesticide or fertiliser use between the sole crops and intercrops. This suggests that farmers must choose companion plants carefully depending on their objectives and desired services. Finally, our findings show that intercropping negatively affects gross margins for wheat, but gross margins are maintained for barley-, pea- and rapeseed-based intercrops compared to sole crops. • We compared sole crops and intercrops performances in a demonstration farm network. • Cereal-legume intercropping reduced pesticides by 40–72%. • Fertilisation was reduced by up to 38% for wheat-based intercrops. • Pesticides and fertilisers were not reduced for rapeseed-companion plant intercrops. • Gross margin is maintained for barley-, pea- and rapeseed-based intercrops. [ABSTRACT FROM AUTHOR]

Increases in extreme weather events from climate change are likely to hinder forage crop production. Cropping system diversification may be a strategy for improving productivity and enhancing yield stability of forage production systems in the face of climate change, yet farmers are often constrained by their operations as to what strategies they can readily adopt. Moreover, the type of diversity necessary to provide desired outcomes and the potential tradeoffs from such outcomes are largely unknown. We compared three strategies to increase cropping system diversity via intercropping in winter annuals, summer annuals, and perennials in a three-year forage crop experiment conducted in New York, New Hampshire, and Vermont, USA. For each crop type, three diversification strategies, (1) cultivar diversity (Intraspecific), (2) crop species diversity (Interspecific), and (3) both cultivar and species diversities (Intra+Inter), were compared against a control of a single cultivar of a single species (Baseline). Measured responses included yield, weed biomass, forage nutritive value, and yield stability. Across all crop types, yields in Interspecific and Intra+Inter treatments were 15% and 14% greater than the Baseline treatment, respectively. Species diversity had the greatest effect on performance in perennials, which we partially attribute to temporal diversity indicated by differences in biomass composition across harvests within a season. Perennial diversity treatments that contained species diversity had lower weed biomass, lower crude protein, and greater fiber content than the Baseline or Intraspecific treatments. Stability analysis of yields across growing conditions showed that perennial crop yields were consistently greater in the Inter and Intra+Inter treatments than the Baseline treatment. In the summer annuals, yields of the Intra+Inter treatment were greater than yields of the Baseline treatment in sub-optimal environments (20th percentile of the environmental index), whereas, in winter annuals yields in the Intra+Inter treatment were greater than yields of the Baseline treatment in optimal environments (80th percentile of the environmental index). Across crops, strategies of species diversity had a greater impact on responses than cultivar diversity and no additional benefits were detected in strategies that also incorporated cultivar diversity. Benefits of mixtures could be further enhanced by selecting specific traits that maximize both functional and response diversity. Future research should aim to develop guidelines for species and trait compatibility in mixtures and appropriate seeding rates to optimize performance. [Display omitted] • Cultivar and species diversity were added to a monoculture control in annuals and perennials. • Adding crop species diversity improved yields and sometimes yield stability. • Adding cultivar diversity had little effect on yield, weed production, or nutritive value. • Composition of grass-legume perennial mixtures showed temporal diversity. • Mixtures can be constructed more precisely based on traits and seeding rates. [ABSTRACT FROM AUTHOR]

Intercropping is of increasing interest in temperate-arable farming systems. The influence of nitrogen (N) fertilization and sowing ratio on concentrations and uptake of calcium (Ca), potassium (K), magnesium (Mg) and phosphorus (P) by oat and pea was assessed in three substitutive intercrops on a fertile soil in eastern Austria. N decreased Ca in oat grain and increased P in pea grain as well as Ca and Mg in oat residue and Mg and P in pea residue. Intercropping did not affect nutrient concentrations of oat grain, whereas a lower pea share in intercrops increased P in pea grain. In residue, Ca, K and Mg concentrations were higher in oat and Ca and K partly lower in pea with a lower share of each crop. The oat-dominated intercrops could partly achieve a slightly higher total grain nutrient yield than pure stands at no or low N; however, these benefits diminished with a higher pea share and N input. In comparison to pure stands, higher residue nutrient yields were obtained by intercropping in all sowing ratios and fertilization levels. Consequently, oat–pea intercropping can be a strategy for increasing the macronutrient yield of grain and especially of residue for ruminant feeding. [ABSTRACT FROM AUTHOR]

The market for organic malting barley (Hordeum vulgare L.) is growing. One goal of producing malting barley is to attain a defined protein content. This is challenging in organic farming because nutrient uptake is unpredictable. Since malting barley is quality sensitive to high amounts of available nitrogen (N) during the grain filling phase, artificial competition for N from a second crop within a mixed intercropping system could help to limit N uptake during these later growing stages. The objective of this study was to evaluate the effects of intercropping on the brewing quality parameters of malting barley within the framework of organic farming. In a field trial, with two spring barley cultivars (Odilia, Marthe) as sole crops and in intercropping treatments of 4 intermediate mixing ratios with camelina (Camelina sativa), linseed (Linum usitatissimum) and pea (Pisum sativum), the effects on yield and malting quality were observed. The results from three growing seasons on a study site in north-western Germany showed an opposite protein response for mixtures with linseed and pea. However, sole stands of barley mostly performed as well as the mixtures. For mixtures with camelina, neither yield nor quality aspects were affected. Comparing the two cultivars, the well-established Marthe, from traditional conventional selection, showed the better overall performance with a 13% higher grain yield, a 3% higher hectoliter weight and 5% higher proportion of size fraction > 2.5 mm than Odilia, which was released later from an organic breeding program. However, the yield component analysis showed a consistent yield determination for Odilia regardless of intercropping partner or mixing ratios which might indicate its suitability in polycultures. The observed average land equivalent ratios (LER) of mixtures with linseed (1.04) and pea (1.13) showed the potential to increase land-use efficiency but were lower compared to the mean LER found in a recent meta-analysis. [Display omitted] • Two barley cultivars showed significantly different yield and quality performance. • Higher barley grain protein concentration with legume than with non-legume intercrop. • Two tested mixing ratios (75:75, 90:50) were not significantly different. • Smaller LERs observed than reported from global meta-analyses. • No influence of yield component composition for biodynamic barley cultivar. [ABSTRACT FROM AUTHOR]

Farmland species face many threats, including habitat loss and malnutrition during key periods of their life cycle. This is aggravated in conventionally managed monocultures, leading to nutrient deficiencies that impair the survival and reproduction of farmland wildlife. For instance, protein deficiencies in wheat or vitamin B3 deficiency in maize reduce by up to 87% the reproductive success of the critically endangered common hamster (Cricetus cricetus), a flagship species of European farmlands. It is urgent to identify and implement agricultural practices that can overcome these deficiencies and help restoring hamsters' reproductive success. As part of a conservation program to diversify farming habitats in collaboration with farmers, we tested whether associations between wheat or maize and three supplemental crops (soybean, sunflower and fodder radish) supported hamsters' performance during hibernation and reproduction. We observed that maize–sunflower, maize–radish and wheat–soybean associations minimized hamsters' body mass loss during hibernation. The wheat–soybean association led to the highest reproductive success (N = 2 litters of 4.5 ± 0.7 pups with a 100% survival rate to weaning), followed by maize–sunflower and maize–radish. These crop associations offer promising opportunities to overcome nutritional deficiencies caused by cereal monocultures. Their agronomic potential should promote their implementation on a large scale and benefit farmland biodiversity beyond the common hamster. [ABSTRACT FROM AUTHOR]

• The ecological niche space for nitrogen (N) use traits was defined via n -dimensional hypervolumes. • Trait space was influenced more by the cultivar identity than crop mixing. • High N uptake was associated with a reduced overlap in niche-space in the mixtures. • Initial seed N pools contributed to N accumulation, shoot and tiller production. More efficient resource use, especially nitrogen (N) in agricultural fields could considerably reduce the losses and spillover effects on the environment. Cereal-legume mixtures can lead to more efficient uptake of growth-limiting resources, and increase and stabilize yields, due to the variation in functional traits that facilitate partitioning of niche space. Here we identify crop mixtures with functional traits that facilitate optimal N resource use in two selected cereal-legume mixtures by using the multi-dimensional trait space concept. Combinations of pea-barley and faba bean-wheat crops were grown in the field as pure cultures and mixtures in Central Sweden, during two years with contrasting weather. The ecological niche space was defined via the n -dimensional hypervolumes represented by N pool, tiller/branch number, shoot biomass, and grain yield functional traits. Regressions and correlations allowed quantifying the relations between functional traits and plant N pools. Differences in trait space were not a result of crop mixing per se , as similar hypervolumes were found in the pure culture and mixture-grown crops. Instead, the trait space differences depended on the cultivar identities admixed. Furthermore, cereals increased their efficiency for N uptake and therefore benefitted more than the legumes in the mixtures, in terms of accumulated N and grain yields. Tiller and shoot biomass production in cereals was positively correlated to N pool accumulation during the season. Resource acquisition through increased N uptake in the mixture was associated with a reduced overlap in niche-space in the mixtures, and initial seed N pools significantly contributed to within-season N accumulation, shoot and tiller production. [ABSTRACT FROM AUTHOR]

Weeds remain a challenge in organic arable farming, as well as supply ecosystem services. The aim is to control weed densities while hosting a diverse and manageable weed community, preventing domination of few deleterious species. Therefore, we want to understand how specific species are stimulated, and which traits are selected for. This study focuses on crop diversity hypothesizing that (1) regions and (2) crop diversity function as filters for specific weed species traits. We conducted a weed monitoring in spring cereals over 2 years on organic farms in five northern European regions. Management and weed trait variables collected for the occurring species allowed an RLQ fourth-corner analysis. The weed communities were regionally specific, but trait selection was not observed, except in Latvia. Hence, the regional species pool provided different species with similar traits. Crop diversity within the management of spring cereals, such as undersowing and cereal frequency in the rotation, affected weed traits. The number of years under organic production selected no traits, although species numbers are known to increase. Hence, general weed species diversity increased, irrespective of traits. We conclude that organic management may support the agility within the weed community against selection of species and act as a buffer rather than as filter. [ABSTRACT FROM AUTHOR]