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        <title>Frontiers in Agronomy | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/agronomy</link>
        <description>RSS Feed for Frontiers in Agronomy | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-05-03T17:12:41.477+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1817915</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1817915</link>
        <title><![CDATA[Can high resolution UAV-derived weed maps replace camera-based targeted spray application?]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Madhusudhan Adhikari</author><author>Sudhir Payare</author><author>Ricardo Pinto</author>
        <description><![CDATA[Efficient weed mapping is critical for enabling site-specific weed management (SSWM) and ensuring effective targeted herbicide application in no-till dryland cropping systems. Producers are increasingly interested in using UAV (Unmanned Aerial Vehicle) based weed mapping to generate prescription maps as a lower-cost alternative to camera-based systems, yet the accuracy and operational feasibility of these UAV-derived methods remain uncertain. This study compared three UAV-based weed detection approaches, RGB Excess Green (ExG) index, NIR band thresholding, and a YOLOv11 deep learning model against a ground-based camera reference system across three mapping dates in a summer fallow field. UAV imagery was collected using RGB and multispectral sensors, and YOLO was trained on annotated RGB image tiles. Key performance metrics evaluated were prediction accuracy (MAE, RMSE, and R2), omission rates (%) and Bland-Altman analysis (bias and Limits of Agreement-LoA). Results showed that all UAV methods systematically underpredicted weeds compared to camera-based, with bias and variability increasing with weed density and from early season (April 24) to late season (June 24). RGB consistently provided the lowest errors and most stable agreement, YOLO tracked spatial patterns but had the largest underestimation, and NIR performance varied according to soil and residue conditions. Weed omission rates ranged from 41–65% for RGB, 48–73.5% for NIR, and 78–85% for YOLO. These findings demonstrate that the effectiveness of UAV-based maps is constrained by image spatial resolution, which can limit the detection of small weeds that are more vulnerable to management practices. In contrast, real-time camera-based systems improve the detection of small weeds at application, increasing herbicide application efficiency in large-scale operations. Future research should focus on refining UAV image acquisition protocols and integrating advanced sensing technologies to improve weed detection reliability across the growing season and support more effective site-specific weed management.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1798511</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1798511</link>
        <title><![CDATA[Evaluation of maize (Zea mays L.) genotypes for yield and yield components and carbon storage]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Maltase Mutanda</author><author>Sandiswa Figlan</author><author>Asande Ngidi</author><author>Seltene Abady Tesfamariam</author><author>Vincent Chaplot</author><author>Hussein Shimelis</author>
        <description><![CDATA[IntroductionMaize is a global commodity crop cultivated under monocropping systems and diverse environmental conditions. While different genotypes exist with various abilities to store carbon into tissues and into the soil to mitigate against climate change and soil degradation, the links with grain yield remains uncertain.MethodsTherefore, the present study aimed to screen a series of maize germplasm planted in southern Africa for carbon storage and agronomic performance to assess the link between these and identify superior genotypes. We evaluated as a first attempt, forty-five genotypes using a 5 x 9 alpha lattice design across two South African sites during the 2022/23 growing season. The recorded agronomic traits include plant height (PH), grain yield (GY), total plant biomass (PB), shoot biomass (SB) and root biomass (RB) together with total plant carbon stocks (PCs), shoot carbon stock (SCs), root carbon stock (RCs), root to shoot carbon stock ratio (RCs/SCs), and grain carbon stock (GCs).ResultsSignificant (p< 0.05) genetic variations were recorded for all the assessed agronomic traits. The high yielding maize genotypes were TZECOMP3DT-C2, TZE(OMP3DT/WHITEDTSTRSYN)CZ and DT-STR-Y-SYN14. The maize genotypes which sequestered more carbon were TZE(OMP3DT/WHITEDTSTRSYN)CZ, 9022–13 and ZDIPLOBC4-C3-W. High phenotypic and genotypic coefficient of variations were recorded for PB and GY, respectively. The GY showed significant positive correlation with PH, SB, RB and PB. The principal component analysis highlighted that RCs, RCs/SCs, PCs, SCs, and GCs as key contributors to carbon sequestration.DiscussionGenotypes TZECOMP3DT-C2, TZE(OMP3DT/WHITEDTSTRSYN)CZ, TZECOMP5C7/ TZECOMP39TCZ and 9022–13 were selected for their high GY production and carbon storage capacity. The selected genotypes are recommended for production and future breeding.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1814520</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1814520</link>
        <title><![CDATA[Combination of nitrogen reduction and algae-based biostimulants: a sustainable strategy for processing tomato]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Maria Eleonora Pelosi</author><author>Ida Di Mola</author><author>Lucia Ottaiano</author><author>Eugenio Cozzolino</author><author>Mohamed Houssemeddine Sellami</author><author>Mauro Mori</author>
        <description><![CDATA[Processing tomato (Solanum lycopersicum L.) is a key crop in the Mediterranean, where farmers are increasingly required to balance high yields with reduced inputs. In response to the EU Farm to Fork strategy, which targets a 20% reduction in fertilizer use by 2030, the aim of this study was to evaluate the potential of algae-based biostimulants to sustain crop performance under reduced nitrogen (N) supply. In this context, we carried out a two-year field trial (2023–2024) in Acerra, Southern Italy testing three N levels (100%, 90% and 80% of the optimal dose in 2023; 100%, 80% and 70% in 2024) and two commercial formulations (BIO1: Auximar + Procalcium; BIO2: Enerleaf + Pentacalcium), applied as foliar sprays. Reducing N dose led to a proportional decline in yield compared to the optimal dose (–16% in 2023, mean value of N80% and N90% and –30% in 2024 with N70%). In both years, all biostimulants increased marketable yield (+21% and +36%), mainly by raising fruit number. The N80% treatment combined with biostimulants maintained yields comparable to the full nitrogen dose, pointing to a more efficient use of fertilizer. Biostimulant treatments enhanced fruit firmness (+19% in 2023) and soluble solids total (+14% and +10% in 2023 and 2024, respectively), and boosted nutritional parameters such as ascorbic acid (12% in 2023 and 15% in 2024) and carotenoids. Lycopene was not influenced by biostimulants, but showed instead a strong dependence on seasonal conditions and N dose, with higher values recorded in 2024. Although main effects of nitrogen and biostimulants were largely independent, significant year × nitrogen × biostimulant interactions were detected for fruit nitrogen and nutraceutical compounds. The results indicate that algae-based products with a moderate (≥20%) N reduction appears to be a practical way to cut fertilizer inputs while safeguarding both yield and fruit quality in processing tomato.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1795832</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1795832</link>
        <title><![CDATA[Quantification and mapping of maize crop evapotranspiration using the surface energy balance algorithm for land model and medium-resolution satellite data]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Gourav Sabharwal</author><author>Kandasamy Vaiyapuri</author><author>Selvaraj Selvakumar</author><author>Ramasamy Jagadeeswaran</author><author>Marimuthu Raju</author><author>Sellaperumal Pazhanivelan</author><author>Pavithran Periyasamy</author><author>Sakthivel Sivakumar</author>
        <description><![CDATA[Evapotranspiration (ET) is a key variable in the hydrologic cycle that directly affects the redistribution of precipitation and surface balance. ET measurements with high temporal resolution are required for coupling with models of highly dynamic processes, e.g., hydrological and land surface processes. The Amaravathi River Basin is the focus of Tamil Nadu, as its major water resource for industry and major grain producing regions. However, this area is facing serious water resource shortages and water pollution problems. The present study used Landsat 8 satellite remote sensing data, in situ meteorological observations, and the surface energy balance algorithm for land (SEBAL) model with daily vegetative indices and energy fluxes in the River Basin. Moreover, factors influencing ET were also identified based on the results of this study. ET varies with land cover type and physical and chemical properties of the underlying surface. Furthermore, ET is also controlled by water availability, radiation, and other atmospheric weather factors conditions, whereas the CROPWAT model, based on the FAO 56 Penman-Monteith method, was employed to estimate seasonal water requirements and comparison was done with the SEBAL model. The root mean square error (RMSE) for ETa exhibited an RMSE of 0.65 mmd−1 and demonstrated an R2 exceeding 0.93. Finally, based upon crop cutting experiments (CCE), yield data and SEBAL-derived ET spatial water productivity maps were obtained by mathematical operations of the yield and ETa raster maps. The average maize yield of the study area was 7,567 kg ha−1, which was close to official agricultural marketing department data. The seasonal maize crop water requirement based upon SEBAL was 470 mm and that based upon CROPWAT was 506.3 mm, indicating that the SEBAL model shows good capability to detect CWR demand under study at the Amaravathi River basin scale. The average physical and economic maize water productivity was 1.61 kg m−3 and Rs. 40 m−3 across the Amaravathi River Basin, respectively. This study identifies high-performing and low-performing water productivity regions across the Amaravathi River Basin.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1795286</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1795286</link>
        <title><![CDATA[Sowing methods and early-season weed interference duration as key drivers of yield loss reduction in canola]]></title>
        <pubdate>2026-04-29T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Muhammad Awais Arshad</author><author>Rana Nadeem Abbas</author><author>Usman Zulfiqar</author><author>Ali Ahmad</author><author>Go’zal Burxonova</author><author>Mayank Anand Gururani</author>
        <description><![CDATA[Canola is a major oilseed crop of semiarid regions throughout the world. The productive performance of canola is influenced by different sowing methods and durations of weed–crop interference. Appropriate sowing methods combined with timely weed management during the early growth stages can significantly improve canola productivity. A field experiment was conducted to evaluate the effect of different sowing methods and durations of early-season weed interference on growth and yield components of canola crop at the Agronomy Research Area, Department of Agronomy, University of Agriculture, Faisalabad, during 2021–2022. The experiment consisted of three different sowing methods (flat, bed, and ridge) with five different weed–crop competition periods [weed-free control, weedy up to 30, 40, and 50 days after sowing (DAS), and full-season weed competition]. The design of the experiment was a randomized complete block design (RCBD) with a split-plot arrangement. Each treatment was replicated three times. The results showed that the lowest weed density and fresh and dry weights of weeds were observed in ridge sowing, followed by bed sowing, while the highest were recorded under the flat sowing method. Results for leaf area index, grain yield, biological yield, number of pods, number of grains/pod, harvest index, number of branches, plant height, 1,000-grain weight, and oil content showed the highest values in ridge sowing followed by bed sowing, while the lowest values were recorded under the flat sowing method. Among weed–crop competition periods, the weed-free control (season-long weed removal) produced the highest yield and quality parameters, whereas full-season weed competition resulted in the lowest crop performance. Yield and related traits progressively declined as the duration of weed competition increased from 30 days after sowing. In conclusion, the results showed that sowing method significantly influences canola yield and quality, and prolonged early-season weed interference substantially reduces crop productivity. Based on the results of this study, the ridge sowing method combined with weed-crop competition up to 30 DAS is recommended for canola cultivation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1749285</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1749285</link>
        <title><![CDATA[Crop modeling and multivariate analysis of some bread wheat genotypes under drought stress]]></title>
        <pubdate>2026-04-28T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Naheif E. Mohamed</author><author>Abdel-rahman A. Mustafa</author><author>Mohamed S. Shokr</author><author>Hala A. M. El-sayed</author><author>Nazih Y. Rebouh</author>
        <description><![CDATA[One important abiotic factor affecting wheat yield and endangering global food security is drought stress. Thus, to evaluate these genotypes based on their water usage efficiency and drought susceptibility index, the current study used 10 extremely diverse bread wheat genotypes over the winter seasons of 2023/2024 and 2024/2025. Additionally, the correlation coefficients between grain yield and its components are broken down into direct and indirect impacts, and the fitted model for grain yield and its components in both normal and drought-stressed environments was evaluated. For every variable examined, there were very significant differences between the genotypes under both favorable and stressful conditions. The genotypes G3, G6, and G8, which are distinguished by a high yield index (YI: >1), low drought susceptibility index (<1), and high yielding stability index, were more adaptive in both environments. While genotypes G2 and G9 were suited to normal conditions in both seasons, genotypes G4 and G7 were adapted to drought stress. Grain yield was directly positively impacted by the characteristics of number of tillers (NT), thousand kernel weight (TKW), and harvest index (HI). Under drought stress, spike length (SL) via TKW and HI, NT via number of spikes (NS) and HI, and TKW via HI had the greatest beneficial indirect effects. The fitted models of grain yield and its components under drought stress comprised biological yield (BYLD), NT, NS, HI, and plant height (PH), TKW, BYLD, HI, which contributed more to grain yield in the first and second seasons at 91.5% and 96.7%, respectively. According to the graphical genotype and environmental interaction (GGE-bioplot) focused scaling for comparison, G3 was the best and most promising genotype under these circumstances, followed by G6, G8, and G4. As a result, these genotypes are thought to be highly advantageous in wheat breeding studies.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1724816</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1724816</link>
        <title><![CDATA[The effects of long-term fertilization on rice yields in the red soil region, China: a field meta-analysis]]></title>
        <pubdate>2026-04-28T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xian Tang</author><author>Xiaolin He</author><author>Dao Liu</author><author>Yitian Liu</author><author>Feng Li</author><author>Shuai Lan</author><author>Zhangjie Qin</author><author>Xiulong Chen</author><author>Jianrong Zhao</author><author>Feng Liang</author>
        <description><![CDATA[BackgroundRice is the primary grain crop produced in red paddy soil. However, the effects of different fertilization treatments, inherent soil productivity on rice yield and also the factors that influence the rice yield and inherent soil productivity in this region remain unclear.MethodsWe here selected 196 cultivated land quality monitoring sites to assess the effects of no fertilizer (CK), chemical fertilizer plus straw return (NPKS) and chemical fertilizer plus manure (NPKM) on rice yield. We also evaluated the soil properties on the rice yield, basic soil productivity contribution rate to rice yield (BSPCR) and fertilizer contribution rate to yield (FCR); furthermore, we assessed the impacts of specific soil properties on BSPCR and FCR.ResultsThe results showed that NPKM and NPKS significantly increased rice grain and straw yield by 82.63% and 83.05%, respectively, compared to CK. NPKM was found to increase yield more than NPKS did. Rice straw and grain yield both increased along with increases in nitrogen fertilizer application and the available nitrogen (AN) content of the soil. In the NPKM and NPKS plots, higher pH levels were associated with a gradual decrease in the rate of yield increase. Compared with CK plots, increased soil organic matter (SOM), available phosphorus (AP), and available potassium (AK) contents in NPKM and NPKS plots were each associated with initial increases in rice grain and straw yield. Soil pH and SOM contents were determined to be the main factors affecting the BSPCR and FCR.ConclusionThis study indicated that rice yield benefited more from the application of manure than of returned straw. In the future, improving the acidification and SOM contents of red soil paddy would be the most important measures to improve basic soil fertility, the fertilizer utilization rate, and also the rice yield.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1757848</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1757848</link>
        <title><![CDATA[Integrated pest and disease management for banana crops in East and Central Africa: addressing the challenges of co-occurring biotic threats]]></title>
        <pubdate>2026-04-27T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Guy Blomme</author><author>Elizabeth Kearsley</author><author>Walter Ocimati</author>
        <description><![CDATA[Smallholder subsistence farmers dominate banana (Musa spp.) production across East and Central Africa, yet their yields are constrained by a suite of co-occurring biotic threats. Three major diseases, Xanthomonas wilt (XW), Fusarium wilt (FW), and banana bunchy top disease (BBTD) threaten productivity. These are compounded by two established pests (black weevil, plant-parasitic nematodes) and an emerging pest (banana thrips). Integrated pest and disease management (IPDM) protocols aim to mitigate these challenges by coupling disease-specific interventions with broader agronomic practices. While individual IPDM packages share core components, including biosecurity, accurate diagnosis, roguing, clean planting material, resistant cultivars, vector avoidance, and judicious chemical control, their efficacy can be compromised when multiple threats coexist. Synergistic or antagonistic interactions may arise under these conditions. Part 1 of this review synthesizes current literature on the core components of IPDM strategies for these six biotic stresses, highlighting commonalities and divergences among the recommended packages. In Part 2, it further evaluates the role of standard cultural and agronomic practices in disease-pest management outcomes. These include crop diversification, weed management, planting density, sucker and leaf removal, tillage, mineral and organic fertilization, biocontrol, mulching, pest suppression, and irrigation. By identifying compatibilities and incompatibilities in management when biotic constraints co-occur, and by addressing knowledge gaps across the various protocols, the review provides actionable insights for designing holistic extension programs that harmonize prevention and control measures. As such, IPDM programs should be better equipped to avoid unintended trade-offs and enhancing resilience in banana systems where these threats co-occur.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1805940</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1805940</link>
        <title><![CDATA[Evaluation of UV-C light for control of Tetranychus urticae and Eotetranychus lewisi (Acari: Tetranychidae) on strawberry]]></title>
        <pubdate>2026-04-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Colin T. Koubek</author><author>Mohammad Amir Aghaee</author>
        <description><![CDATA[Twospotted spider mite, Tetranychus urticae Koch, is a major arthropod pest of strawberry production in California, while Lewis mite, Eotetranychus lewisi McGregor, has emerged as an occasional but increasingly problematic pest in recent decades. Management of both species relies heavily on miticides and biological control, but resistance to miticides in T. urticae and limited biological control options for E. lewisi highlight the need for alternative management tools. Ultraviolet-C (UV-C) light is currently used in commercial strawberry production to manage powdery mildew, yet its efficacy against mite pests under California field conditions is not clear. This study evaluated the ovicidal and lethal effects of UV-C exposure on T. urticae and E. lewisi through laboratory and open-field evaluations, along with dose–response bioassays. Laboratory ovicide assays demonstrated near complete suppression of egg hatch for both species following UV-C exposure at 600, 1200, and 1800 J/m2. Field assays conducted across multiple seasons showed consistent and substantial reductions in egg hatch for T. urticae and E. lewisi, though efficacy varied among trials. Dose–response analyses indicated that larvae were more susceptible than adults, but lethal dose estimates for adults of both species exceeded 9,000 J/m2, a UV-C dose currently not advisable under field conditions. Reported LD50 values confirmed that UV-C is unlikely to provide meaningful direct control of motile life stages at commercially viable exposure levels. To our knowledge, this study is the first to report ovicidal activity and lethal dose estimates for E. lewisi in response to UV-C light. These findings indicate that UV-C applications primarily function as an ovicidal tool for mite pests in strawberry production systems and may complement existing integrated pest management programs by targeting early developmental stages.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1719143</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1719143</link>
        <title><![CDATA[Response of acidic silt loam soil properties to biochar application under soybean cultivation]]></title>
        <pubdate>2026-04-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Binaya Baral</author><author>Deepak Khatri</author><author>Sudip Poudel</author><author>Lalit Pun Magar</author><author>Atanu Mukherjee</author><author>Anuj Chiluwal</author>
        <description><![CDATA[Biochar is widely recognized for its potential to stabilize soil acidity and enhance carbon sequestration, yet its functional effects in temperate acidic silt loam soils remain insufficiently quantified. A two-year field study was conducted in Kentucky to evaluate changes in soil physicochemical properties following annual application of 12 t ha-1 of pine (Pinus spp.) sawdust biochar (pyrolyzed at 650 °C) under continuous soybean (Glycine max) cultivation. Composite soil samples (0–15 cm) were collected pre-planting (May) and post-harvest (October) to monitor acidity indices, organic reserves, fertility indices, and hydrological properties. Biochar acted primarily as a chemical and carbonaceous stabilizer rather than an immediate fertility enhancer. The amendment significantly maintained higher post-harvest pH levels compared to the control, effectively buffering against the seasonal acidification observed in unamended plots. Soil organic carbon (SOC) and buffer pH exhibited a distinct “lag effect,” with significant increases emerging only after two years of cumulative application; at the final October 2024 sampling, SOC in the biochar-treated plots had increased to 1.96% from a 1.74% baseline, whereas the control plots declined to 1.66%. Conversely, soil fertility and hydrological parameters showed no significant treatment effects, being driven instead by seasonal environmental factors and crop uptake. These findings suggest that an annual application of 12 t ha−¹ of pine biochar serves as an effective benchmark for mitigating acidification and building organic reserves in temperate silt loams, though further multi-rate studies are required to optimize application dosages for long-term agronomic use.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1749362</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1749362</link>
        <title><![CDATA[Deep learning-based quantification of tall fescue abundance in pastures]]></title>
        <pubdate>2026-04-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ross E. Binkley</author><author>Samuel R. Revolinski</author><author>Echo E. Gotsick</author><author>Ray S. Smith</author><author>Zeya Wang</author><author>Katsutoshi Mizuta</author>
        <description><![CDATA[Accurate and rapid measurement of tall fescue abundance is essential for efficient forage management and mitigating livestock exposure to potential endophyte-related toxicity. Traditional visual estimation methods are labor-intensive and are subject to change depending on the observer doing the calculations, which limits their scalability and consistency. This study explores the application of deep learning techniques to automate and improve the classification of tall fescue abundance across pasture systems in Kentucky. Ground-truth abundance classes were evaluated using one of the traditional methods with occupancy grid and compared against estimates derived from red-green-blue images. Two convolutional neural network architectures, YouOnlyLookOnce (YOLO) and ResNet were employed for image-based classification. Among the models tested, YOLOv8x achieved a classification accuracy of 96% across three abundance classes, effectively distinguishing tall fescue from other vegetation and bare soil. Results demonstrated the potential of artificial intelligence in detecting spatial distribution of tall fescue, thereby supporting risk assessment of toxicity. Compared to the traditional methods, the deep learning approach improves efficiency and reduces manual labor efforts while maintaining highly accurate prediction performance for continuous monitoring applications.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1726240</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1726240</link>
        <title><![CDATA[Surfactant-enhanced fertilizer coating improves nutrient use efficiency and yield in potato]]></title>
        <pubdate>2026-04-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Pooja Mankar</author><author>Sanjay Rawal</author><author>Mayur Kankale</author><author>Sushilkumar Bahuguna</author><author>Jeferson Naue</author><author>Sanjeev Sharma</author><author>Jagdev Sharma</author><author>Rajesh Kumar Singh</author><author>Brajesh Singh</author>
        <description><![CDATA[Global potato production exceeds 380 million tons annually and continues to expand due to rising food demand and growth of the processing sector, increasing pressure on production systems to improve resource-use efficiency while minimizing environmental impacts. In India, where production is expected to increase further, improved nutrient management is essential to sustain productivity under climatic and environmental constraints. Potato production relies heavily on chemical fertilizers, raising concerns about nutrient-use efficiency (NUE) and environmental sustainability. This study evaluated the effects of a non-ionic surfactant soil adjuvant, Silwet Power, combined with varying NPK fertilizer levels on potato growth, tuber yield, nutrient efficiency, and carbon footprint. A 2-year field experiment (2021–2023) was conducted at ICAR–Central Potato Research Institute, Regional Station, Modipuram, India, using a randomized block design with eleven treatments and three replications. Treatments included full, reduced, and zero NPK fertilizer rates applied with or without Silwet Power. Data were analyzed using ANOVA with mean separation at P ≤ 0.05. Application of 75% of the recommended fertilizer dose (270–80–150 kg N–P2O5–K2O ha−1) combined with Silwet Power significantly improved plant growth, tuber yield, and Nutrient Use Efficiency compared to the recommended fertilizer dose alone. This treatment produced a 10.4% higher total tuber yield, enhanced agronomic efficiency and uptake of N, P, and K, increased process-grade tuber yield and size uniformity, and reduced the proportion of oversized and deformed tubers. The yield-scaled carbon footprint was reduced by 11.1%–25.3% relative to the recommended fertilizer dose owing to lower fertilizer input. The results indicate that surfactant-assisted fertilization can enhance fertilizer efficiency and sustain potato productivity under reduced NPK application, offering a promising strategy for sustainable potato production and contributing to climate-resilient nutrient management in intensifying potato-based systems in the future.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1732106</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1732106</link>
        <title><![CDATA[Methane production potential, soil health and rice yields under inorganic and organic management in the Brahmaputra Valley of Assam, India]]></title>
        <pubdate>2026-04-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Bedabati Kalita</author><author>Leena Borah</author>
        <description><![CDATA[Methane (CH4), a powerful greenhouse gas emitted from flooded rice soils is a major contributor to climate change. Its production is significantly influenced by on-farm nutrient management practices. The present study compared the effects of long-term inorganic and organic management practices on methane production potentials, selected soil health indicators, and grain yields in farmers’ rice fields of Assam. We hypothesized that long-term organic nutrient management increases soil CH4 production potential due to enhanced carbon availability, but simultaneously improves soil health and rice productivity compared to inorganic fertilization. Considering both the years of study, CH4 production potential ranged between ~133 and ~236 CH4 g-1 day-1, organic carbon between 0.38 and 0.70%, microbial biomass carbon between 400 and 547 µg g-1, and grain yield between ~2809 and ~5684 kg ha-1 in the inorganic fields. Similarly, in the organic fields, CH4 production potential, organic carbon, microbial biomass carbon and grain yield ranged between ~167 and 344 CH4 g-1 day-1; 0.50 and 0.91%; 300 and 890 µg g-1; ~5267 and ~7731 kg ha-1 respectively. Comparatively higher CH4 production rates in organic fields may be due to enrichment of the soil organic carbon pool via decomposition of applied organic amendments, leading to enhanced microbial biomass and activity. CH4 production under organic management showed good association with soil pH, organic carbon, and microbial biomass carbon. However, higher CH4 production in organic fields was partly compensated by improved soil properties and rice yields than inorganic fields. Higher grain carbohydrate in organic fields indicate efficient carbohydrate partitioning to the grains and better nutrient utilization by the crop. Vermicompost and vermiwash applied fields recorded lower CH4 production among the organic treatments and higher yield among all the studied treatments. Cow manure and Azolla application also significantly reduced CH4 production but improved yield to a comparatively lesser extent. Our findings suggest that appropriate organic management practices could reduce CH4 production rates in rice soils while enhancing soil health and crop yield.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1786084</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1786084</link>
        <title><![CDATA[Agronomic and morphological characterization of Medicago intertexta L. for sustainable forage production in Mediterranean environments]]></title>
        <pubdate>2026-04-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Lucia Dinolfo</author><author>Simona Prestigiacomo</author><author>Nicoletta Lala</author><author>Alessandro Albano</author><author>Davide Farruggia</author><author>Giuseppe Di Miceli</author>
        <description><![CDATA[Medicago intertexta L., a self-reseeding annual legume native to the Mediterranean Basin, shows high potential for sustainable forage production in semi-arid environments. This study investigated its presence in Sicilian forage–livestock systems, characterized the morphological variability of a local ecotype (“Monreale”), and evaluated seed yield under two plant densities across two growing seasons. Field surveys confirmed its natural abundance and agronomic value, as farmers recognized its persistence, palatability, and self-regeneration ability. Morphological characterization revealed notable intraspecific diversity, revealing distinct phenotypic groups with different agronomic performance and adaptive traits. Higher seeding density enhanced total seed yield per unit area but reduced individual plant productivity, while climatic variability between years significantly affected performance. The species’ strong hardseededness ensures regeneration under adverse conditions, confirming its resilience to Mediterranean climatic stress. Overall, M. intertexta represents a valuable resource for developing low-input and climate-adapted forage systems. Further research should focus on optimizing seeding rates and exploiting morphological variability to select improved cultivars.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1782966</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1782966</link>
        <title><![CDATA[Canopy density modifies leaf predisposition to Plasmopara viticola but does not affect downy mildew epidemics in grapevine]]></title>
        <pubdate>2026-04-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Giorgia Fedele</author><author>Vittorio Rossi</author><author>Margherita Furiosi</author><author>Tito Caffi</author>
        <description><![CDATA[Certain agricultural practices may influence the susceptibility of the plant tissue to pathogens, including practices that influence the canopy density, which in turn may favor disease development through changes in the canopy microclimate. This relationship has previously been demonstrated for downy mildew (DM), caused by Plasmopara viticola, through comparisons of different trellising systems. In this work, we investigated the extent to which grapevine canopy density affects the susceptibility of leaves to P. viticola and the development of DM epidemics during the season in a single VSP system subjected to different canopy densities through modulating agronomic interventions, including variations in bud load, fertilization, and irrigation. Leaf susceptibility was investigated through artificial inoculation of P. viticola sporangia on leaf discs excised from the leaves of plants with different canopies. DM progress in the vineyard was periodically assessed as disease severity and then expressed as AUDPC. Infection on leaves from plants with denser canopies was more severe than that in leaves from plants with sparser canopies; however, neither changes in leaf predisposition to infection nor differences in microclimatic conditions (with higher moisture levels at nighttime in denser canopies) significantly affected DM progress in field. These findings confirm that DM epidemics are driven by complex interactions among host plant components, pathogen infection cycle, and microclimate factors. Although denser grapevine canopies increase the predisposition of leaves to P. viticola and enhance the moistness of the within-canopy microclimate, canopy density alone does not necessarily favor more severe epidemic development within uniform VSP systems.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1811115</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1811115</link>
        <title><![CDATA[Impact of rice field drone applications on canopy dynamics of rice planthopper populations]]></title>
        <pubdate>2026-04-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Weicai Qin</author><author>Xiaotuo Wang</author><author>Xiaolan Lv</author><author>Junrong Gu</author>
        <description><![CDATA[The downwash airflow from plant protection UAVs disturbs rice planthoppers. This study investigated airflow-induced pest distribution by testing two UAV models (large-rotor N-3, small-rotor HYB-15L) and four flight heights (0.8–5 m), spraying only pure water to isolate airflow impacts. Field experiments integrated short-term (30 min) and long-term (1, 3, 7 d) monitoring, aerodynamic measurements, and statistical analyses. Results showed significant (P < 0.001) planthopper redistribution: spray swath densities reduced by 41–74%, adjacent 2–10 m zones exhibited density decreases at 2 m (P < 0.05), baseline recovery at 5 m (P > 0.05), and 24–58% increases at 10 m (P < 0.01). Vertically, airflow shifted pests from the lower to upper canopy and ground (P < 0.001), driven by downwash (2.5–3.8 m/s) and rebound airflow (1.2–2.0 m/s). The effect was transient, stabilizing 3 d post-operation. The optimal trade-off was the N-3 UAV at 3 m, achieving 73.9% spray swath reduction and 0.48 ha/h work rate. These findings clarify UAV parameter impacts on planthopper dispersion, guiding optimized integrated pest management in rice.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1797143</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1797143</link>
        <title><![CDATA[Mechanized establishment and integrated nutrient management drive productivity, profitability, and energy efficiency in rice–groundnut cropping systems]]></title>
        <pubdate>2026-04-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Debesh Kumar Panda</author><author>Chandramani Khanda</author><author>Anshuman Nayak</author><author>Ipsita Kar</author><author>Prasanna Kumar Samant</author><author>Bijay Kumar Mohapatra</author><author>Abhiram Dash</author>
        <description><![CDATA[Rice–groundnut cropping systems are widely practiced in coastal regions of Eastern India due to their potential for enhancing system productivity and profitability. However, the sustainability of these systems is increasingly challenged by inappropriate establishment methods, imbalanced nutrient management, and declining soil health. A field experiment was conducted during the wet and dry seasons of 2022–23 and 2023–24 at the Central Farm of Regional Research & Technology Transfer Station (RRTTS), Coastal Zone, OUAT, Bhubaneswar to study the effect of establishment methods and nutrient management practices on the growth, yield, nutrient dynamics, and economics of rice-groundnut cropping system. The experiment was performed in strip plot design with sixteen treatment combinations, which were replicated thrice. The design consisted of four types of establishment methods (viz., direct seeded rice (DSR), puddled manual transplanted rice (PTR), puddled machine transplanted rice (PMTR) and non- puddled machine transplanted rice (NMTR)) allocated to the main plot and four nutrient management practices (Soil test-based fertilizer recommendation (STBFR), Nutrient recommendation by Rice Crop Manager (RCM), 75% STBFR + farm yard manure and 75% STBFR + in situ green manuring with dhaincha) allocated to the subplot in wet season for rice. In dry season, STBFR + Rhizobium + Phosphate-solubilizing bacteria (PSB) was applied to groundnut in all the plots. PMTR recorded the highest rice equivalent yield (REY) of 11166 kg ha-1 which was at par with NMTR (11140 kg ha-1). Among the integrated nutrient management practices, 75% STBFR + GM achieved the highest pooled REY (11,363 kg ha−1). The 75% STBFR + GM practice recorded the highest system NPK uptake (211.62, 35.55, and 193.98 kg ha−1, respectively), enhancing the system N uptake by 4.35, 5.78 and 18.23%, P uptake by 1.25, 5.08 and 19.21%, and K uptake by 2.08, 5.16 and 15.67% over RCM, 75% STBFR + FYM and 100% STBFR, respectively. Among the establishment methods, PMTR recorded the highest system NPK uptake (204.95, 35.96, and 192.32 kg ha−1, respectively). Application of 75% STBFR + GM gave the the most promising results, recording the highest benefit cost ratio (1.88) and energy ratio (8.60). Correlation and principal component analysis revealed strong positive associations between rice equivalent yield and nitrogen, phosphorus, and potassium uptake, indicating that system productivity was primarily driven by improved nutrient acquisition. The application of 75% STBFR + GM in PMTR sustained productivity and sustainability in rice-groundnut by enhancing soil quality in Eastern India.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1682252</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1682252</link>
        <title><![CDATA[Strengthening cover crop seed value chains to scale agroecology in Cambodia: a Battambang case study]]></title>
        <pubdate>2026-04-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Quentin Theiva à Hauariki</author><author>Alessandra Giuliani</author><author>Veng Sar</author><author>Sophal Koun</author><author>Sreymom Sieng</author><author>Vira Leng</author><author>Setha Rath</author><author>Florent Tivet</author>
        <description><![CDATA[IntroductionIn Cambodia, cover crops (CC) are being explored as an agroecological practice to improve soil health, sustain crop productivity, and enhance land profitability over time. Since 2004, initiatives have introduced CC into rubber production systems during the immature period, later extending their use to annual rainfed crops and rice-based systems. In recent years, private companies, cooperatives, and non-profit organizations have become increasingly involved in developing the CC sector.MethodThis shift toward commercial operations prompted us to investigate the CC seed value chain and analyse the stakeholder network, aiming to identify key challenges, opportunities, and address the research gap. This case study in Battambang Province used a mixed-methods approach. Data collection included: (i) an agroeconomic assessment (2023–2024); (ii) a qualitative survey of 23 seed producers; (iii) four focus group discussions with rice farmers using CC; (iv) 26 key informant interviews; and (v) value chain analysis, including participatory elements such as a multi-stakeholder workshop.ResultsFindings indicate rapid expansion in CC seed production, from 2 ha in 2017 to 177 ha in 2023, mainly involving Crotalaria ochroleuca and Crotalaria juncea. Seed producers reported an additional mean net profit of $314.6/ha/year from CC seeds, compared to $438.5/ha/year from a single Maize production system. Fifty percent of seed producers cited soil fertility improvement and profitability as main incentives. In 2023, seed production was expected to reach 288.5 ha, but this target was not met due to lack of equipment and unfavourable climate. While 90% of rice farmers observed notable improvements in soil fertility, the same proportion identified economic and climatic constraints as barriers to scaling-up the use of cover crops.DiscussionStakeholder mapping revealed a diverse landscape with varying influence and interest. The study examines how stakeholder recommendations could support the scaling of CC, highlighting short-term economic incentives but also practice and results-based reward mechanisms as promising strategies.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1764269</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1764269</link>
        <title><![CDATA[Population response of Helicoverpa armigera and Frankliniella occidentalis to air temperature, humidity, and adult density in arid regions of Northwestern China: a statistical association and threshold analysis]]></title>
        <pubdate>2026-04-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jian-Guo Mu</author><author>Yan Jiang</author><author>Xue-Qin Zhang</author><author>Ning-Ning Yan</author><author>Nan Cao</author><author>Jiao Lin</author><author>Peng Wang</author><author>Su-Mei Wan</author>
        <description><![CDATA[IntroductionThis study investigates the influence of key meteorological factors—air temperature, relative humidity, and near-surface (5 cm) soil temperature—on population fluctuations of Frankliniella occidentalis (western flower thrips) and Helicoverpa armigera (cotton bollworm) in sunflower cultivation zones of arid Northwestern China.MethodsField data were collected from 2023 to 2024 in Beitun City and surrounding sites in Xinjiang, aligning pest occurrence records with localized meteorological monitoring. Statistical frameworks included partial correlation analysis, principal component analysis (PCA), and both linear and nonlinear regression modeling.ResultsThe study revealed distinct stage-specific ecological responses. F. occidentalis density during the budding stage showed a strong positive correlation with air temperature (r = 0.7300, p < 0.05), fitting the Robust Index Increment Model (R² = 0.9577) within a temperature-sensitive range of 23–30°C. Conversely, H. armigera populations were predominantly driven by humidity during early stages (r = 0.7400, p < 0.05), with later stages influenced by combined thermal and moisture thresholds. The H. armigera population exhibited strong positive correlations with both air temperature and relative humidity, with a maximum partial correlation coefficient of r = 0.8400. At the flowering stage, air temperature and humidity accounted for 57.89–60.42% and 23.61–29.26% of ecological variation, respectively (regression analysis). Threshold analysis indicated that during the sowing period, the combined condition of air temperature ≥ 24°C and relative humidity ≥ 40–50% is the key ecological threshold range leading to a significant increase in H. armigera populations. This threshold is a statistical correlation range based on observational data from specific years and locations; its specific boundary values (especially the humidity lower limit) may carry a confidence interval.DiscussionThis threshold provides an important reference for early warning in this region, though its universality and stability require further validation under broader climatic conditions, soil types, and cultivation management practices. Moreover, the influence of meteorological factors on pest population dynamics shows obvious interspecific differences and stage-specific effects. Air temperature emerged as the primary limiting factor for F. occidentalis, whereas H. armigera populations were synergistically influenced by both air temperature and relative humidity.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1783823</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1783823</link>
        <title><![CDATA[Resistance to groundnut rosette disease and yield performance of advanced groundnut lines in northern Mozambique]]></title>
        <pubdate>2026-04-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Cristovão Bolacha</author><author>Paola Silva</author><author>Marcela Opazo</author><author>Amade Muitia</author><author>Maria Carvalho</author>
        <description><![CDATA[Groundnut rosette disease (GRD) is a major constraint to groundnut production in sub-Saharan Africa, causing severe yield losses, particularly under low-input smallholder farming systems with limited access to external inputs. Because resistance to this pathogen is strongly influenced by environmental factors, quantifying genotype-by-environment (G×E) interactions is essential for identifying GRD-resistant varieties and optimal testing locations. This study analyzed the effects of genotype (G), environment (E), and their interaction (G×E) on GRD resistance and grain yield of groundnut in northern Mozambique. Twenty advanced groundnut lines (Arachis hypogaea L.) were assessed across 11 environments from 2014 to 2018 using an alpha-lattice design with two replications under low-input conditions. Measured traits included phenology, number of emerged plants, number of plants at harvest, yield components, grain yield, and GRD incidence. General and mixed linear models, stability analysis, AMMI and SREG models, and Pearson correlations were applied. Significant G×E interaction was observed, indicating a strong environmental influence on trait expression. GRD incidence was highest in the NPL_15 environment, where the susceptible cultivar JL-24 reached 56% and SREG analysis identified this site as a suitable hotspot for resistance screening. Genotypes ICGV-SM 7508, ICGV-SM 7510, ICGV-SM 7518, ICGV-SM 7533, ICGV-SM 7558, ICGV-SM 7566, ICGV-SM 8530 and ICG 405 showed resistance. No consistent relationship was observed between GRD incidence and grain yield; however, yield reductions were mainly associated with plant losses during the growing season. Genotypes ICGV-SM 7518 and ICGV-SM 7510 showed broad adaptation, combining high yield and GRD resistance across environments.]]></description>
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