Abstract Camelina ( Camelina sativa L.) is a promising bioenergy crop with wide environmental adaptation, but nitrogen (N) requirements affect the sustainable production. Sixteen camelina genotypes were planted in 3 years in Sideny, MT at high and low N levels to evaluate nitrogen use efficiency (NUE) and yield in response to soil N. Results showed extensive variations among genotypes for plant height, seed yield, and seed oil and N concentrations at both N levels. The top‐yielding genotypes were MT143 (2122 kg ha −1 ) and MT229 (2119 kg ha −1 ) across years and N levels. Genotypes MT144 and MT229 had the highest oil concentrations independent of N levels with an average value of 407 g kg −1 for both genotypes. The nitrogen use efficiency based on oil yield (NUEOY) determined by (1) N uptake efficiency (NUpE) and (2) N transfer efficiency based on oil yield (NUtEOY) showed large genotypic variations. MT143 had the highest NUpE (2.38 kg kg −1 ), especially at low N, and MT229 and MT144 had the highest NUtEOY (8.67 and 8.58 kg kg −1 , respectively). Overall, especially in low N, MT229 had the highest NUEOY (19.47 kg oil kg N −1 ) followed by MT143 (18.12 kg oil kg N −1 ). High broad‐sense heritability ( H 2 b) values were observed for seed yield and oil concentration, but not for seed N concentration at low N. The genotype + genotype‐by‐environment interaction biplots demonstrated which genotype won low and high N environments, and the analysis of means showed genotypes that had traits significantly higher or lower than the group means. The information and genetic materials may be used for further plant breeding.
Abstract Efficient nitrogen (N) management in Florida's coarse, N‐leaching‐prone soils is challenging because high N rates are often used to avoid deficiency. This study evaluated whether controlled‐release (CRF) and slow‐release (SRF) fertilizers can improve maize ( Zea mays L.) yield and reduce NO 3 –N leaching compared with urea under varying climate. A previously calibrated crop environment resource synthesis‐Maize model for the maize hybrid Pioneer P1870 was re‐evaluated with 2 years of field data from Live Oak, FL. The 2023 experiment included an unfertilized control, CRF, and SRF at 235, 314, and 392 kg N ha − 1 . In 2024, the same CRF and SRF treatments were repeated, and split‐applied urea at the same rates was added. The model reproduced above‐ground biomass, grain yield, and N uptake well ( d = 0.81–0.99) and soil NO 3 –N with moderate skill ( d = 0.57). The evaluated model was then used to run a 30‐year simulation (1995–2024) for CRF, SRF, and urea applied at 0–400 kg N ha − 1 in 50 kg increments, and outputs were analyzed by growing‐season rainfall and temperature categories. Rainfall, not temperature, significantly affected all variables. Across rainfall regimes, CRF gave the highest agronomic and environmental performance. At its source‐specific optimum N rate, CRF increased grain yield by ∼6%–7% and cut NO 3 –N leaching by ∼40%–45% relative to urea, whereas SRF reduced leaching (∼25% under normal rainfall) with smaller yield gains. Optimal N rates were highest for CRF, intermediate for SRF, and lowest for urea.
Abstract Organic integrated crop–livestock systems (ICLSs) can improve nutrient cycling and soil cover, but subsurface nutrient dynamics in organic rotations that include small ruminants remain poorly characterized. This study evaluated nitrate–N (NO 3 –N) and phosphate–phosphorus (PO 4 –P) concentrations in subsoil water from a certified‐organic corn–soybean–goat pasture rotation in central Kentucky. Subsoil water was monitored at 1‐m depth for 5 years under seven treatments arranged in a randomized complete block design: corn–soybean no‐pasture treatment (CNP), ungrazed perennial pasture (PP), two crop phases (rotation corn phase [CS1] and rotation soybean phase [CS2]), and three goat‐grazed pasture phases (P1 [first‐year goat‐grazed pasture], P2 [second‐year goat‐grazed pasture], and P3 [third‐year goat‐grazed pasture]). NO 3 –N showed significant treatment, year, and treatment × year effects. Five‐year mean NO 3 –N ranged from 6.8 mg L − 1 in PP to 21.1 mg L − 1 in P3, with significantly high concentrations in CNP (19.4 mg L − 1 ). Peak seasonal NO 3 –N concentrations occurred mainly during annual crop phases and pasture‐to‐crop transition periods, whereas PP and early pasture phases generally maintained lower concentrations under continuous vegetative cover. Managed goat grazing did not consistently increase NO 3 –N relative to the ungrazed pasture. PO 4 –P responses differed from NO 3 –N, with a strong year effect but limited treatment separation. Five‐year mean PO 4 –P ranged from 0.6 mg L − 1 in CNP to 1.1 mg L − 1 in PP. Overall, maintaining continuous cover, minimizing soil disturbance during rotation transitions, and managing grazing to preserve vegetation may reduce nutrient movement into subsoil water in an organic ICLS.
Abstract Cotton ( Gossypium hirsutum L.) production is constrained by water scarcity, and sustainable strategies are needed to improve resilience and productivity. Seaweed extract–based biostimulants (SEBs) are natural materials with the potential to enhance stress tolerance and nutrient use efficiency. This study evaluated the effects of four foliar SEB application treatments on cotton under water restriction: an untreated control (T1), four foliar applications of SEB at early cotton growth stages (T2), foliar application every 15 days (T3), and monthly foliar application (T4) at two sites. SEB application improved macronutrient and micronutrient uptake (K, Ca, Fe, and Cu). It also reduced oxidative damage by decreasing hydrogen peroxide and malondialdehyde contents. Additionally, SEB enhanced water‐use efficiency, carboxylation efficiency, plant height, and productive parameters. Monthly application was the most effective, increasing seed fiber yield by 9.77% (371.14 kg ha − 1 ) and 6.0% (225.0 kg ha − 1 ) compared with the control in the first and second growing seasons, respectively. Monthly SEB application also improved fiber quality by increasing micronaire and reducing the short fiber index. Our findings indicate that SEB application is a sustainable strategy for enhancing cotton nutrition, physiology, productivity, and quality. A monthly application frequency offers a viable approach to maximizing the benefits of biostimulant use in cotton production and contributing to more sustainable agricultural practices.
Abstract In recent years, nanofertilizers have gained popularity as a means of enhancing maize ( Zea mays L.) yield. However, there is limited information on their effectiveness when maize is grown in succession to soybean ( Glycine max (L.) Merr.). Therefore, this study aimed to evaluate the effects of supplemental nitrogen nanofertilizer on the physiological, nutritional, biochemical, and agronomic variables of maize grown in succession to soybean cultivation. Field experiments were conducted in the Midwest region of Brazil from 2022 to 2024 in a randomized complete block design with six replications and five treatments corresponding to MIST‐N nanofertilizer doses (0‐control, 1.0, 2.0, 3.0, and 4.0 L ha − 1 ) on maize following soybean. The supplemental nitrogen nanofertilizer doses did not consistently and significantly affect most agronomic, physiological, or biochemical variables. The crop exhibited a major leaf area and grain yield in the crop year with favorable precipitation conditions (2024), without the effect of the nanofertilizer. In the crop year with less rainfall (2022), increasing the supplemental nanofertilizer doses up to 1.6 L ha − 1 of MIST‐N promoted lower plants, higher number of ears, grain protein content, and grain yield. The results of this study allow us to conclude that generalized recommendations for nitrogen nanofertilizer use should not be made when maize is grown after soybean crop.
Abstract This study sought to assess the impact of cover cropping and high rates of soil amendments on crop yield during organic transition. Compost, biochar, or a “50/50” mixture of the two on a C‐equivalent basis were applied at a rate of 8 Mg C ha −1 per varying application regimens, with and without cover crops, at two locations on the North Carolina Coastal Plain with sandy, low‐C soils. It was hypothesized that the treatments would increase crop yield due to soil organic carbon–driven improvements in soil health, such as enhanced nutrient availability. Rather than increase yield, however, cover cropping and compost additions resulted in 15%–20% yield reductions for cash crops following a legume cover crop. The results suggest that the treatments, which provided N in excess of crop needs, drove late‐season weed growth past the window for mechanical cultivation and led to subsequent yield reductions. Additionally, poor synchrony between cover crop N and cash crop demand was observed in a year where crimson clover was terminated late and its residue had a high C:N ratio (>30). These results were observed in a unique context, where organic management was implemented and N‐related best practices concerning cover crop termination timing and fertilizer rate adjustment were intentionally deviated from in order to maximize the C input and to avoid yield differences resulting from varying N fertilizer rates, respectively. This study highlights the negative consequences of suboptimal N management and weed dynamics on crop productivity in Southeastern organic management systems with no rescue herbicides.
Abstract In recent years, the growing demand for automation in grape harvesting has highlighted the need for efficient, reliable methods to reduce labor requirements and improve harvesting operations. Manual grape picking is labor‐intensive and time‐consuming, driving demand for automated solutions. This study presents the design and implementation of a machine vision‐based image processing approach for detecting red grape ( Vitis vinifera ) clusters in outdoor vineyard environments using standard red–green–blue (RGB) images. A dataset of 500 images was collected under natural lighting conditions, with 200 selected for quantitative performance evaluation. Using RGB color space analysis, two algorithms were developed to extract and segment grape clusters based on their color characteristics, effectively distinguishing them from background noise. The first algorithm (Algorithm 1) achieved a detection accuracy of 96.84%, calculated as the ratio of correctly detected grape clusters to the total number of grape clusters in the evaluated images. After enhanced preprocessing and adaptive thresholding, the improved Algorithm 2 achieved 98.11% accuracy using the same evaluation criterion, reducing missed detections to 15 clusters and lowering the average processing time by 0.34 s per image. Both algorithms demonstrate strong performance and adaptability under variable lighting conditions. The results confirm their potential for real‐time integration into automated harvesting systems, offering a practical and efficient solution for reliable fruit detection. This study contributes to the development of practical precision viticulture technologies by providing an accessible alternative for field‐based grape detection.
Abstract In recent years, rising paddy ( Oryza sativa L.) production in India has increased residue production, yet its sustainable utilization remains limited. In situ straw incorporation is an effective residue management practice, but its field‐scale applications on crop performance remain uncertain. Hence, this study was aimed at evaluate the influence of in situ straw incorporation and various nitrogen management options on productivity and nutrient dynamics in rice‐based cropping systems. A preliminary survey across three agro‐climatic zones of Telangana revealed that residue burning, use as cattle feed/sale, incorporation, and composting were the predominant practices with Garrett's scores of 65.4, 59.7, 47.2, and 27.6, respectively. Following survey results, a 2‐year field study was conducted in rice–rice and rice–maize ( Zea mays L.) cropping systems with various paddy straw (straw burning, straw incorporation, cutting, and removal) and nitrogen management options at 100%, 115%, and 130% RDN (recommended dose of nitrogen) Lower N rates were excluded to avoid N deficiency. Results revealed that in situ straw incorporation has significantly improved SPAD values (5% in rice, 4.6% in maize), dry matter accumulation (14.2% in rice, 6.6% in maize), returns net (12.6% in rice, 3.6% in maize) as compared to straw burning (control). Furthermore, in situ straw incorporation with 130% RDN enhanced grain yield, nitrogen uptake, and returns net compared to straw burning, which was statistically comparable with in situ straw incorporation with 115% RDN. Overall, in situ straw incorporation combined with optimized N management significantly enhanced crop productivity and N uptake in rice‐based systems of Telangana, indicating its potential for sustainable intensification.
Abstract Soybean ( Glycine max [L.] Merr.) seed prices have increased by more than 190% from 1998 to 2018 in the US, making seeding rate one of the most cost‐sensitive management decisions. While soybean can maintain maximum seed yield across a wide range of plant populations due to their morphological and reproductive plasticity, the decreasing commodity prices and increased seed cost necessities re‐evaluation of economic optimum seeding rates. This study aimed to evaluate soybean yield responses and economic return across a wide range of seeding rates and environments in Iowa, as well as seed quality. Across site‐years, the agronomic optimum seeding rate (AOSR) was 234,300 seeds ha −1, where seed yield plateaued at 4.7 Mg ha −1 . Results showed a higher number of pods and seeds at seeding rates lower than 234,300 seeds ha −1 ; however, at higher seeding rates, the number of pods and seeds were consistently lower. There was no relationship between individual seed weight, oil and protein content, and seeding rates. Seeding rates above the AOSR resulted in no benefit under favorable conditions, since higher plant populations mostly benefit environments exposed to weather events that reduce population (e.g., hail). The economic optimum seeding rate (EOSR) averaged approximately 90.8% of the AOSR. Seed yields are maximized by targeting the AOSR; however, the additional yield from the difference between AOSR and EOSR did not bring financial gains.
Abstract Diverse crop rotations can enhance productivity and yield stability, perhaps by promoting soil microbial communities or increasing carbon sequestration and soil water availability. We used a decade of maize ( Zea mays L.) yield data from the Minnesota Long‐Term Agricultural Research Network to investigate legacy effects of crop‐rotation diversity on total and yearly maize grain productivity and stability. Cropping systems evaluated included a maize–soybean [ Glycine max (L.) Merr.] rotation (MS), a maize–soybean–wheat ( Triticum aestivum L.) rotation (MSW), and a maize–soybean rotation plus a fall‐planted rye ( Secale cereale L.) cover crop (MS + CC). Average maize yield over a 10‐year period was greatest in the MSW, followed by MS and then MS + CC rotation at the Waseca and Lamberton sites, while there was no difference in yield among systems at the Grand Rapids site. During drought years, however, maize yield was significantly lower in the MSW rotation at the Waseca and Lamberton sites. Maize yield stability was lower in the MSW compared to the MS with or without a cover crop at the Waseca and Lamberton sites. Only some of the results from this research support the general hypothesis that crop productivity and stability benefit from systems with greater crop rotational diversity. Our findings show the importance of long‐term, multi‐location research for understanding how cropping systems respond to increasingly variable weather and how strategies for diversification need to be site‐specific.
Abstract Soil organic carbon (SOC) dynamics and greenhouse gas (GHG) emissions in dry (arid and semi‐arid) agroecosystems are regulated by low and variable moisture, episodic wet–dry cycles, and limited organic inputs. Although process‐based biogeochemical models are widely used to quantify these processes, a comprehensive assessment of their performance in dryland agroecosystems is lacking. Therefore, we evaluated four widely used models, Agricultural Production Systems sIMulator (APSIM), daily century model (DayCent), DeNitrification‐DeComposition (DNDC), and decision support system for agrotechnology transfer (DSSAT), across dry regions defined by the United Nations Environment Program aridity index (AI < 0.65). Peer‐reviewed studies published between 2010 and 2026 were assessed using reported quantitative metrics, including R 2 , Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE), for SOC, CO 2, and N 2 O emissions, and crop yields. DayCent and APSIM consistently simulate long‐term SOC dynamics under input‐constrained conditions (DayCent R 2 ≤ 0.99; APSIM R 2 = 0.92, RMSE = 3.33 Mg C ha − 1 ). DNDC performed well for SOC in residue‐incorporated systems (NSE ≤ 0.84) but underestimated surface‐applied residue SOC by 5%–12%. DSSAT reliably simulated yields (normalized root mean square error [nRMSE] ≤ 19%–22%) but underestimated SOC gains under organic amendments by 5%–22%. For GHGs, DayCent and APSIM captured cumulative N 2 O emissions reasonably ( R 2 ≈ 0.7–0.8), whereas DNDC resolved management‐driven contrasts. Shared limitations across models include difficulty in estimating emission pulses following wetting events and in representing yield–soil feedbacks. Overall, model performance in dryland systems can be improved by representing agroecosystem processes and improving calibration, irrespective of the parameters simulated or the model selection.
Abstract Coffea canephora is a species of major economic and social importance, and the identification of superior genotypes is essential for sustainable crop improvement. This study evaluated the performance of 42 C. canephora genotypes over six consecutive harvests (2016–2021) to estimate genetic parameters and assess the efficiency of multi‐harvest selection. The experiment was conducted in Nova Venécia, Espírito Santo, Brazil, using a randomized complete block design with three replications. Yield data were analyzed using restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) mixed models. Significant genotypic, permanent environmental, and genotype × measurement interaction variance components were detected, supporting the use of repeated evaluations for reliable genetic inference. The broad‐sense heritability of the genotype mean was 0.596, while repeatability (0.409) and the mean genotypic correlation across harvests (0.602) indicated moderate temporal consistency in genotype performance. Temporal selection accuracy exceeded 0.70 from the third harvest onward, demonstrating the feasibility of early selection. Predicted genetic gains reached 19.16 bags ha −1 when selecting the single best genotype and remained substantial at 15.97, 14.11, and 12.49 bags ha −1 when selecting the top three, five, and eight genotypes, respectively, confirming the effectiveness of the REML/BLUP approach for identifying superior materials and accelerating genetic progress in C. canephora breeding programs.
Abstract In Ethiopia, mungbean [ Vigna radiata L. (Wilczek)] is an emerging crop with low productivity. Although blended fertilizer containing nitrogen phosphorus sulfur boron (NPSB) fertilizer is effective for many crops, evidence on its effect on mungbean in West Belesa, Northern Ethiopia, is limited. Consequently, a field experiment was conducted during the 2021 and 2022 cropping seasons to evaluate the effect of different NPSB fertilizer rates on mungbean growth, yield, and yield components in the district. Five fertilizer rates (0, 50, 100, 150, and 200 kg ha − 1 ) were arranged in a randomized complete block design with three replications. Data on phenology, plant height, primary branches, pods plant −1 , total biomass and seed yield, hundred‐seed weight, and harvest index were collected and analyzed using a mixed‐model analysis of variance in R software version 4.2. Pearson's correlations were calculated to examine the relationships between the variables. The results showed that blended NPSB fertilizer rates significantly influenced mungbean growth, yield, and yield attributes. The highest seed yield (1473.75 kg ha − 1 ) was obtained at 150 kg ha − 1 , followed by 200 kg ha − 1 (1389.97 kg ha − 1 ), while the lowest yield (892.77 kg ha − 1 ) was recorded from the unfertilized plots. A higher seed yield was recorded in 2021 (1461.0 kg ha − 1 ) than in 2022 (977.75 kg ha − 1 ). A partial budget analysis showed that 150 kg ha − 1 of NPSB fertilizer provided the highest net return with a marginal rate of return (240%) exceeding the minimum acceptable level (100%). Therefore, applying 150 kg ha − 1 of blended NPSB fertilizer is recommended for sustainable and profitable mungbean production under the soil and climatic conditions of West Belesa district and similar arid areas.
Abstract The selection of superior genotypes in common bean ( Phaseolus vulgaris L.) breeding is challenging due to the broad genetic variability in segregating populations. In this context, machine learning (ML) has emerged as a promising tool to support decision‐making in plant breeding. This study aimed to evaluate the potential of ML to classify common bean genotypes according to their selection value. A total of 5136 plants, including inbred lines, cultivars, and segregating generations (F 2 to F 10 ), were field‐evaluated. Traits analyzed included plant height, stem diameter (SD), number of pods (NP), first pod insertion height, and grain weight per plant (GWPP). The Random Forest classifier algorithm was applied to the dataset, split into training (70%) and testing (30%) sets. Genotypes were categorized based on GWPP quartiles as follows: poor (<4.99 g), fair (5.00–8.50 g), good (8.51–13.93 g), and excellent (>13.93 g). The model achieved an accuracy of 0.68, with high precision for “excellent” (0.78) and “poor” (0.77) classes. Strong correlations were observed between GWPP and NP ( r = 0.93) and SD ( r = 0.64), supporting indirect selection strategies. Top‐ranked individuals, such as the BAF07 accession and BRS Embaixador cultivar, were identified as potential parents. These findings reinforce the usefulness of supervised ML models in common bean breeding, particularly for selecting genotypes with extreme performance, and highlight their potential to enhance efficiency, precision, and speed in breeding programs.
Abstract Information on soil benefits and biomass production of spring‐planted grass cover crops (CCs) that are terminated late (planting green) is limited. We quantified the impact of spring‐planted oat ( Avena sativa L.) and barley ( Hordeum vulgare L.) CCs, terminated about 3 weeks after soybean [ Glycine max (L.) Merr.] planting on CC aboveground and root biomass production, soil properties, and soybean yield in the eastern US Great Plains for 3 years. Oat (2.80 ± 1.01 Mg ha −1 ) produced more aboveground biomass than barley (1.54 ± 0.44 Mg ha −1 ), while total root biomass production was 1.40 ± 0.26 Mg ha −1 for oat, 1.16 ± 0.19 Mg ha −1 for barley, and 0.27 ± 0.15 Mg ha −1 for no CC in the 0‐ to 30‐cm soil depth. CCs did not affect soil bulk density, sorptivity, particulate organic matter, organic matter, C, N, available P, exchangeable K, and microbial properties in any year but increased the proportion of 0.25–0.5 mm aggregates by 7%–8% and reduced the proportion of <0.25 mm aggregates 8%–10% in Year 3. The latter suggests that at least two seasons may be needed for CCs to improve soil aggregation. Soybean yield remained unaffected. Short experimental duration (3 years), long‐term no‐till management, and fine‐textured and high‐organic‐matter soil at the site likely limited CC effects on soils. Overall, planting green of spring‐planted CCs for 3 years increases biomass input, but soil benefits may not be fully realized in early years.
Abstract North Carolina is a major poultry‐producing region, generating quantities of poultry litter (PL), a cost‐effective organic fertilizer. Because PL nutrient release must be synchronized with crop demand, application timing is important, and PL is applied before planting. Timely application can be limited by the busy planting season, wet spring conditions, and litter hauling. Although interest in in‐season nitrogen (N) application is increasing, research on in‐season PL application remains limited due to concerns about crop damage. Therefore, this study evaluated the effects of PL rate and timing on soybean ( Glycine max (L.) Merr.) yield and seed N concentration. Field experiments were conducted at 3 site‐years in North Carolina in 2023 and 2024 using PL rates of 0, 73, 146, 292, and 585 kg plant‐available N ha −1 at planting, V2, and R1. Soybean response varied by site‐year. At 1 site‐year with low initial soil fertility and unfavorable early growing conditions, PL at 73 kg N ha −1 increased yield by 71% relative to the control, whereas higher rates provided no benefit. Within each site‐year, yield did not differ among application timings. Seed N concentration varied only by site‐year. Compared with PL at a similar rate applied at R1, urea ammonium nitrate (UAN) increased leaf N concentration at the reproductive stage by 13%, but yield and seed N concentration did not differ between PL and UAN. These results indicate that PL can be an effective alternative to UAN under low fertility conditions and that application timing from planting to R1 had little influence on soybean yield when applied at agronomically appropriate rates.
Abstract This review explores how organomineral fertilizers (OMFs)—produced by combining manure and crop residues with mineral fertilizers—are formulated, what they contain, and how effectively they perform. It outlines the contributions of OMFs to increasing crop productivity, improving soil fertility, and reducing climate change impacts. Although OMFs show considerable promise, their adoption remains limited due to issues of accessibility, economic uncertainty at the farm level and amid ongoing global challenges, and weak integration into current farming systems. This paper synthesizes existing research, identifies key knowledge gaps, and proposes future research directions aimed at optimizing agricultural waste materials for use in OMF formulations that support sustainable production systems. Reviewed papers demonstrate that OMF can enhance soil nutrient availability, improve soil organic matter content, reduce greenhouse gas release, and increase microbial activity and moisture retention. In many cases these improvements were shown to maintain or improve crop yield and quality relative to mineral‐only fertilizers (MOF) and may have been greater were studies longer than 1–2 years in duration. Key knowledge gaps remain; reduced greenhouse gas emissions and heavy metal accumulation were measured in relatively few studies and require further scrutiny. Realizing the potential of OMF will require long‐term research that draws on expertise from agronomy, biology, engineering, marketing, and economics to develop reliable agricultural biproduct‐based OMF products compared with MOF. Evaluation protocols suggested in this review would document OMF's performance and guide safe, effective, and profitable adaptation for use in agricultural systems.
Abstract Biofumigation with brassica cover crops (BCCs) is gaining momentum in the United States as an ecologically sound alternative to chemical pest suppression in agricultural systems. This review critically evaluates the impacts of Brassica species on soil health, weed suppression, disease mitigation, and control of plant‐parasitic nematodes (PPNs) across US agroecosystems over the last decade (2014–2024). Synthesizing data from over 50 peer‐reviewed studies, we found that brassicas, particularly mustard ( Brassica juncea ), radish ( Raphanus sativus ), and canola ( Brassica napus ), exert a significant biofumigation effect due to the release of allelochemicals, notably isothiocyanates, during residue decomposition. BCCs exhibit mixed effects on soil physical and chemical health, with certain species, such as turnip ( Brassica rapa ) and mustard, alleviating soil compaction and improving organic carbon under specific conditions. In contrast, others, such as canola, may reduce soil water content or microbial diversity due to high biomass demand or the release of allelochemicals. While 87.5% of the studies observed disease suppression and 60% reported nematode control, weed suppression showed variable outcomes, depending on Brassica species and management practices. Mustard was notably effective in pathogen control, while daikon radish consistently suppressed soybean cyst and reniform nematodes. However, some Brassica species acted as hosts to certain nematodes under specific conditions, highlighting the complexity of plant‐nematode interactions. Additionally, limited data exist on long‐term soil structural and chemical changes, particularly under arid or saline conditions prevalent in the western United States. This review identifies critical research gaps, including the need for integrated, multi‐functional assessments; long‐term trials; and innovative tools such as spatial‐spectral sensing, modeling approaches, and microbial functional profiling. Future research should prioritize exploring brassica performance under abiotic stress, assessing region‐specific impacts, and developing decision‐support tools to optimize biofumigation practices.
Abstract Intercropping is an ancient agricultural practice in which two or more crops are grown in the same field in space and/or time. Evidence shows intercropping can increase whole‑system yields per unit land (often expressed as land‑equivalent ratio), improve resource capture (light, water, and nutrients), and enhance agroecosystem functions, but outcomes are strongly context‑dependent. In many smallholder, low‑input systems (which dominate the available literature, particularly across Asia and Africa), diverse canopies and rooting patterns buffer against climatic and market shocks. Furthermore, integrating legumes improves nitrogen use efficiency through biological nitrogen N fixation. However, intercropping does not guarantee higher yields for all crops. Certain combinations and environments may lead to lower yields, increased labor demands, greater management complexity, and in dense canopies potentially higher disease pressure. This review explores the benefits and trade‐offs of intercropping as a sustainable agricultural practice, contrasting it with traditional monoculture systems as a growing pathway to scaling diversification. The review concludes that intercropping is a viable tool for sustainable intensification. However, success depends on matching designs to local biophysical and socioeconomic conditions, alongside supporting mechanization, markets, extension, and enabling policy.
Abstract Intercropping cereals with non‐food intercrops (NFICs) provides a means to enhance cereal productivity while providing additional benefits such as improved soil health or forage production. We conducted a meta‐analysis to investigate the effect of NFICs on cereal yields, cereal nitrogen uptake, and striga ( Striga spp.) infestation, using 874 observations from 97 peer‐reviewed studies across tropical and subtropical regions. Results showed that maize ( Zea mays L.) grain yield increased by 7% and decreased by 10% when intercropped with Fabaceae and Poaceae, respectively, compared to sole cropping. Sorghum ( Sorghum bicolor (L.) Moench.) grain yield was significantly reduced by an average of 47% under intercropping with Fabaceae NFICs (mostly perennial woody species) compared with sole cropping, likely due to competition for nutrients, light, and particularly water, as most sorghum trials included in this review were conducted under semi‐arid climatic conditions. In general, higher rainfall and higher soil organic matter content increased the performance of intercropping relative to sole cropping. Performing intercropping for multiple consecutive years favored positive yield responses. NFICs had limited effect on nitrogen content in cereal biomass. Striga density in maize fields was significantly reduced (−130%) under intercropping with Desmodium spp. compared to sole cropping. Overall, intercropping maize with Fabaceae NFICs emerges as a promising strategy for enhancing maize yields in tropical and subtropical regions, though its effectiveness depends on factors such as NFIC category and climate. While caution is warranted when intercropping sorghum with perennial Fabaceae NFICs in semi‐arid climates, the limited number of published studies on sorghum intercropping with annual Fabaceae NFICs suggests that further investigation is warranted.
