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Agronomy, Volume 15, Issue 2 (February 2025) – 213 articles

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5 pages, 186 KiB  
Editorial
Effects of Abiotic Stresses on Horticultural and Cereal Crops at Physiological and Genetic Levels
by Rong Zhou
Agronomy 2025, 15(2), 465; https://doi.org/10.3390/agronomy15020465 (registering DOI) - 14 Feb 2025
Abstract
Various abiotic stresses (e [...] Full article
(This article belongs to the Special Issue Crop and Vegetable Physiology under Environmental Stresses)
15 pages, 4424 KiB  
Article
Chromium Pollution and Mitigation in a Sunflower Farmland System
by Renjing Yu, Liyan Yang, Huan Yu, Shuangzhe Li, Lin Wang and Yanbin Yin
Agronomy 2025, 15(2), 464; https://doi.org/10.3390/agronomy15020464 - 13 Feb 2025
Abstract
Chromium is a major heavy metal pollutant that affects the health of both plants and animals. In this study, sunflower seedlings were treated with K2Cr7O4 containing 50, 100, and 250 mg of pure chromium per kilogram of soil. [...] Read more.
Chromium is a major heavy metal pollutant that affects the health of both plants and animals. In this study, sunflower seedlings were treated with K2Cr7O4 containing 50, 100, and 250 mg of pure chromium per kilogram of soil. It was found that the chromium was absorbed by the roots and transported within plant tissues to the stems and leaves. Chromium affected sunflower photosynthesis, seen in increased the Fv/fm values as the chromium concentration rose. Metagenomic sequencing of rhizosphere microbial communities after treatment with 100 mg/kg pure chromium indicated that the rhizosphere microorganisms were resistant to chromium exposure; chromium was found to promote dopamine secretion and chromium complexation by the microorganisms. In addition, chromium was found to reduce microbial production of N2O reductase and increase the emission of the greenhouse gas N2O. In addressing the problem of chromium pollution in sunflower farmland, Bacillus sp. strain C8 was isolated and shown to effectively reduce soil chromium contents and chromium absorption by sunflower, thereby reducing the adverse effects of the metal. Furthermore, a gene associated with chromium resistance, LOC118480906, was identified by transcriptome sequencing of sunflower plants. In conclusion, the findings denonstrate: (1) the effect of chromium exposure on sunflower growth and development of sunflower; (2) the ecological effects of chromium exposure on sunflower farmland; (3) the regulation of soil microbes and the identification of resistance associated genes are effective ways to reduce chromium pollution. Full article
(This article belongs to the Section Farming Sustainability)
21 pages, 3171 KiB  
Article
Saline–Alkali Tolerance Evaluation of Giant Reed (Arundo donax) Genotypes Under Saline–Alkali Stress at Seedling Stage
by Yangxing Cai, Xiuming Cao, Bin Liu, Hui Lin, Hailing Luo, Fengshan Liu, Dewei Su, Shi Lv, Zhanxi Lin and Dongmei Lin
Agronomy 2025, 15(2), 463; https://doi.org/10.3390/agronomy15020463 - 13 Feb 2025
Abstract
Soil salinization and alkalization are serious global challenges that adversely affect crop growth and yield. In this study, six genotypes of giant reed (Arundo donax) seedlings (LvZhou_No.1, LvZhou_No.3, LvZhou_No.6, LvZhou_No.11, LvZhou_No.12 and LvZhou_Var.) originating from different regions of China and Rwanda were [...] Read more.
Soil salinization and alkalization are serious global challenges that adversely affect crop growth and yield. In this study, six genotypes of giant reed (Arundo donax) seedlings (LvZhou_No.1, LvZhou_No.3, LvZhou_No.6, LvZhou_No.11, LvZhou_No.12 and LvZhou_Var.) originating from different regions of China and Rwanda were utilized as experimental materials. This study aimed to investigate the physiological and biochemical responses of various genotypes to saline–alkali stress and to identify stress-tolerant resources. A mixture saline–alkali solution with a molar ratio of NaCl: Na2SO4: NaHCO3: Na2CO3 = 1:1:1:1 was prepared at three concentrations (75, 150 and 225 millimolar (mM)) for a 7-day pot experiment. Growth and physiological indices were measured at the seedling stage, and salt tolerance was evaluated accordingly. The results indicated the following: the growth indices were significantly reduced across seedlings of all genotypes when the concentration of stress exceeded 150 mM (p < 0.05). There was no significant difference in chlorophyll content (SPAD value) and maximum photochemical efficiency of PS II (Fv/Fm) with increasing saline–alkali stress. However, the photosynthetic rate (Pn), stomatal conductance (Gs) and transpiration rate (Tr) exhibited decreasing trends, reaching their lowest levels at 225 mM. In contrast, the intercellular CO2 concentration (Ci) value decreased to its lowest at 150 mM but increased at 225 mM. Relative electrical conductivity (REC) and the contents of malondialdehyde (MDA), proline (Pro) and soluble sugar (SS) increased progressively with higher stress concentrations. The activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) were significantly enhanced at stress concentrations above 150 mM. The saline–alkali tolerance of A. donax seedlings was comprehensively evaluated using principal component analysis and membership function analysis based on 15 parameters. The results indicate that Pn, Tr and Gs are effective physiological indicators for assessing saline–alkali tolerance of A. donax seedlings. The six genotypes were ranked for saline–alkali tolerance as follows: LZ_No.1 > LZ_No.11 > LZ_No.12 > LZ_Var. > LZ_No.3 > LZ_No.6. This indicates that LZ_No.1 shows the highest resistance to saline–alkali stress, whereas LZ_No.6 is the most severely affected, classifying it as a salinity-sensitive genotype. In conclusion, LZ_No.1 exhibits robust saline–alkali tolerance and represents a valuable germplasm resource for improving saline–alkali tolerance in A. donax propagation. The results not only support the development of resilient plants for saline–alkali environments but also offer insights into the mechanisms of salinity tolerance. Full article
(This article belongs to the Special Issue The Role of Phytobiomes in Plant Health and Productivity)
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16 pages, 546 KiB  
Article
The Influence of Planting Speed of a Maize Vacuum Planter on Plant Spacing Variability and Ear Parameters
by Igor Petrović, Filip Vučajnk, Stanislav Trdan, Rajko Bernik and Matej Vidrih
Agronomy 2025, 15(2), 462; https://doi.org/10.3390/agronomy15020462 - 13 Feb 2025
Abstract
Planting speed has an important impact on plant spacing variability and also grain yield. In a two-year study, the effects of planting speeds of 6, 9, and 12 km/h on maize plant spacing and, consequently, ear parameters were investigated. We wanted to determine [...] Read more.
Planting speed has an important impact on plant spacing variability and also grain yield. In a two-year study, the effects of planting speeds of 6, 9, and 12 km/h on maize plant spacing and, consequently, ear parameters were investigated. We wanted to determine whether increasing the planting speed increases the plant spacing parameters and what effects this has on ear parameters and grain yield. In both experimental years, no differences between the three planting speeds were found in terms of mean plant spacing, plant density, the multiple index, and the miss index. However, the standard deviation of reference spacings and precision increased with the increase in planting speed from 6 to 12 km/h. In 2022, the differences between plant spacings measured using UAV photogrammetry and manual measurements were smaller (<1 cm) than in 2023. The plant spacing data obtained from 3D point clouds show a strong correlation (r = 0.97) with the manual measurements for all three planting speeds. The proposed method is suitable for measuring plant spacing in maize. In 2022, no differences appeared in grain yield and ear parameters between the planting speeds; however, in 2023, the grain yield and kernel mass per ear were greater at planting speeds of 6 and 9 km/h than at a planting speed of 12 km/h in 2023. Individual ear analysis in 2023 showed an increase of 0.73 g in kernel mass per plant with a 1 cm increase in plant spacing, resulting in a 58 kg/ha yield increase. Full article
(This article belongs to the Section Precision and Digital Agriculture)
13 pages, 2421 KiB  
Article
ZmC2GnT Positively Regulates Maize Seed Rot Resistance Against Fusarium verticillioides
by Doudou Sun, Huan Li, Wenchao Ye, Zhihao Song, Zijian Zhou, Pei Jing, Jiafa Chen and Jianyu Wu
Agronomy 2025, 15(2), 461; https://doi.org/10.3390/agronomy15020461 - 13 Feb 2025
Abstract
Fusarium verticillioides can systematically infect maize through seeds, triggering stalk rot and ear rot at a later stage, thus resulting in yield loss and quality decline. Seeds carrying F. verticillioides are unsuitable for storage and pose a serious threat to human and animal [...] Read more.
Fusarium verticillioides can systematically infect maize through seeds, triggering stalk rot and ear rot at a later stage, thus resulting in yield loss and quality decline. Seeds carrying F. verticillioides are unsuitable for storage and pose a serious threat to human and animal health due to the toxins released by the fungus. Previously, the candidate gene ZmC2GnT was identified, using linkage and association analysis, as potentially implicated in maize seed resistance to F. verticillioides; however, its disease resistance mechanism remained unknown. Our current study revealed that ZmC2GnT codes an N-acetylglucosaminyltransferase, using sequence structure and evolutionary analysis. The candidate gene association analysis revealed multiple SNPs located in the UTRs and introns of ZmC2GnT. Cloning and comparing ZmC2GnT showed variations in the promoter and CDS of resistant and susceptible materials. The promoter of ZmC2GnT in the resistant parent contains one extra cis-element ABRE associated with the ABA signal, compared to the susceptible parent. Moreover, the amino acid sequence of ZmC2GnT in the resistant parent matches that of B73, but the susceptible parent contains ten amino acid alterations. The resistant material BT-1 and the susceptible material N6 were used as parents to observe the expression level of the ZmC2GnT. The results revealed that the expression of ZmC2GnT in disease-resistant maize seeds was significantly up-regulated after infection with F. verticillioides. After treatment with F. verticillioides or ABA, the expression activity of the ZmC2GnT promoter increased significantly in the resistant material, but no discernible difference was detected in the susceptible material. When ZmC2GnT from resistant and susceptible materials was overexpressed in Arabidopsis thaliana, the seeds’ resistance to F. verticillioides increased, although there was no significant difference between the two types of overexpressed plants. Our study revealed that ZmC2GnT could participate in the immune process of plants against pathogenic fungus. ZmC2GnT plays a significant role in regulating the disease-resistance process of maize seeds, laying the foundation for future research into the regulatory mechanism and the development of new disease-resistant maize varieties. Full article
(This article belongs to the Section Crop Breeding and Genetics)
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17 pages, 4804 KiB  
Article
Indices to Identify Historical and Future Periods of Drought for the Maize Crop (Zea mays L.) in Central Mexico
by Alejandro Cruz-González, Ramón Arteaga-Ramírez, Ignacio Sánchez-Cohen, Alejandro Ismael Monterroso-Rivas and Jesús Soria-Ruiz
Agronomy 2025, 15(2), 460; https://doi.org/10.3390/agronomy15020460 - 13 Feb 2025
Abstract
Agricultural drought is a condition that threatens natural ecosystems, water security, and food security. The timely identification of an agricultural drought event is essential to mitigating its effects. However, achieving a reliable and accurate assessment is challenging due to the interannual variability of [...] Read more.
Agricultural drought is a condition that threatens natural ecosystems, water security, and food security. The timely identification of an agricultural drought event is essential to mitigating its effects. However, achieving a reliable and accurate assessment is challenging due to the interannual variability of precipitation in a region. Therefore, the objective of this study was to identify the months with drought during the agricultural cycle of the maize crop (Zea mays L.) in the Atlacomulco Rural Development District (ARDD) as a study area using the SPI and SPEI indices and their impact on each phenological stage. The results show that when analyzing the historical period (1985–2017), the ARDD is a region prone to agricultural droughts with a duration of one month. The stages of grain filling and ripening were the most vulnerable, since SPI and SPEI-1 quantify that 25% and 31% of the total months with drought occur during those stages, respectively. Towards the 2041–2080 horizon, the MCG ACCESS-ESM1-5 with the SSP2-4.5 scenario identified an occurrence of dry periods with 17% and 20% by SPI and SPEI, respectively, while for SSP5-8.5, 17% and 22% of the total number of periods corresponded to dry months with SPI and SPEI, respectively. Greater recurrence will be observed in the future, specifically after the year 2061, meaning an increase in the frequency of agricultural drought events in the region, causing difficult and erratic productive conditions for each agricultural cycle and threatening sustainable development. Therefore, it is necessary to take action to mitigate the effects of climate change in this sector. Full article
(This article belongs to the Section Farming Sustainability)
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14 pages, 2241 KiB  
Article
Comparative Effects of Fertilizer Efficiency Enhancers on Nitrogen Use Efficiency and Greenhouse Gas Emissions in Agriculture
by Xiaoyu Shi, Lingli Wang, Zhanbo Wei, Lei Zhang and Qiang Gao
Agronomy 2025, 15(2), 459; https://doi.org/10.3390/agronomy15020459 - 13 Feb 2025
Abstract
Nitrogen (N) fertilizer incorporation of efficiency enhancer is a well-established practice aiming at reducing N loss while enhancing crop yield. However, the effect of different kinds of fertilizer efficiency enhancer on N use efficiency (NUE) and gas loss are rarely compared and poorly [...] Read more.
Nitrogen (N) fertilizer incorporation of efficiency enhancer is a well-established practice aiming at reducing N loss while enhancing crop yield. However, the effect of different kinds of fertilizer efficiency enhancer on N use efficiency (NUE) and gas loss are rarely compared and poorly comprehended. Here, we conducted a field experiment involving the combination of urease and nitrification inhibitor (NI), the biological inhibitor eugenol (DE) and the bioploymer poly-glutamic acid (PG) and their combinations (NI + PG, NI + DE, PG + DE) to evaluate their effects on crop yield, NUE, NH3 volatilization and greenhouse gas emissions (GHGs). Results indicated that NI, DE, PG and their combinations significantly enhanced the crop yield, N uptake and NUE. NI, DE and PG are all effective in reducing NH3 volatilization and N2O emission, averagely decreased by 11.13%, 6.83%, 8.29%, respectively, and by 11.15%, 4.32%, 8.35%, respectively, while have no significant effects on CO2-C and CH4-C fluxes, except PG significantly increases CO2-C emission and thus global warming potential. The combination of these three efficiency enhancers has no multiply effect on maize yield, NUE and gas loss. These findings help to screen the fertilizer efficiency enhancer that can be more effectively utilized in agricultural practices and contribute to their application strategies within agricultural systems. Full article
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18 pages, 2871 KiB  
Article
Enhancing Soil Physical Quality with Compost Amendments: Effects of Particle Size and Additives
by Tomasz Głąb, Krzysztof Gondek and Monika Mierzwa-Hersztek
Agronomy 2025, 15(2), 458; https://doi.org/10.3390/agronomy15020458 - 13 Feb 2025
Abstract
This research investigates the impact of compost particle size, compost additives, and application rate on the physical properties of loamy sand soil, particularly focusing on water retention characteristics. Compost, enriched with additives like zeolite, biochar, and diatomite, was applied to soil in different [...] Read more.
This research investigates the impact of compost particle size, compost additives, and application rate on the physical properties of loamy sand soil, particularly focusing on water retention characteristics. Compost, enriched with additives like zeolite, biochar, and diatomite, was applied to soil in different rates: 1%, 2%, and 4%. Compost particles were divided into three particle size classes: 0–500 µm, 500–1000 µm, and 1000–2000 µm. The study revealed significant effects of compost on soil physical quality, including bulk density, porosity, and water retention. Zeolite-enriched compost showed the most pronounced improvements in soil water retention by modifying pore diameter. However, the effectiveness of compost additives varied depending on the type and rate of application. Compost with zeolite resulted in a decrease in the volume of large soil pores with diameters of 50–500 µm and above 500 µm. This resulted in higher water retention related to mesopores. Larger compost particles (1.0–2.0 mm) exhibited superior effects on soil physical quality compared to smaller particles (<1.0 mm), although finer particles (0.5–1.0 mm) were associated with higher water repellency. Compost with diatomite resulted in higher water repellency than other compost types. The findings underscore the importance of considering compost particle size, component type, and application rate to optimize soil hydraulic characteristics, particularly in agricultural practices where water management is crucial. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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13 pages, 401 KiB  
Article
Effects of Different Sowing Times and Harvesting Stages on Dry Matter Yield, Quality, and Mineral Content of Teff (Eragrostis teff [Zucc.] Trotter)
by Sebiha Erol Uyanik and Emine Budakli Carpici
Agronomy 2025, 15(2), 457; https://doi.org/10.3390/agronomy15020457 - 13 Feb 2025
Abstract
This study aimed to identify the effects of different sowing times and harvesting stages on the dry matter yield, quality, and mineral content of teff (Eragrostis teff [Zucc.] Trotter). The study was conducted in 2021 and 2022 using a randomized block-split plot [...] Read more.
This study aimed to identify the effects of different sowing times and harvesting stages on the dry matter yield, quality, and mineral content of teff (Eragrostis teff [Zucc.] Trotter). The study was conducted in 2021 and 2022 using a randomized block-split plot design with three replications. According to the two-year averages, plant height increased on the 1 June sowing time compared to 15 May, and there was more dry matter yield (4962.94 kg ha−1) and crude protein yield (717.48 kg ha−1) per unit area. Additionally, the crude protein content of the teff (156.30 g kg−1) increased, whereas the NDF content (652.38 g kg−1) decreased in the 1 June sowing time. Dry matter accumulation increased depending on the progress of the plant development periods, and, as a result, the late heading stage yielded the highest dry matter (5610.00 kg ha−1) and crude protein (615.90 kg ha−1). The crude protein content reached the highest level in the early heading stage, and the crude protein yield peaked at the highest level in the late heading stage since the yield per unit area was higher. While sowing times changed the Mg and Zn contents of teff, the extended harvesting stages resulted in significant variations in the P, K, Zn, Fe, Cu, and Na contents of teff grass. The highest identified P, K, Zn, Fe, and Na contents were in the booting stage, whereas the highest Cu content was in the early heading stage. The amount of various mineral compounds was higher in the early development periods; however, they were still sufficient to meet the needs of sheep and cattle throughout the early and late heading stages. Based on the study findings regarding high yield and quality, it is reasonable to recommend sowing teff grass in June and harvesting in the early heading stage under Mediterranean climatic conditions. Full article
(This article belongs to the Special Issue Managing the Yield and Nutritive Value of Forage and Biomass Crops)
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17 pages, 3052 KiB  
Article
Estimation of Daylily Leaf Area Index by Synergy Multispectral and Radar Remote-Sensing Data Based on Machine-Learning Algorithm
by Minhuan Hu, Jingshu Wang, Peng Yang, Ping Li, Peng He and Rutian Bi
Agronomy 2025, 15(2), 456; https://doi.org/10.3390/agronomy15020456 - 13 Feb 2025
Abstract
Rapid and accurate leaf area index (LAI) determination is important for monitoring daylily growth, yield estimation, and field management. Because of low estimation accuracy of empirical models based on single-source data, we proposed a machine-learning algorithm combining optical and microwave remote-sensing data as [...] Read more.
Rapid and accurate leaf area index (LAI) determination is important for monitoring daylily growth, yield estimation, and field management. Because of low estimation accuracy of empirical models based on single-source data, we proposed a machine-learning algorithm combining optical and microwave remote-sensing data as well as the random forest regression (RFR) importance score to select features. A high-precision LAI estimation model for daylilies was constructed by optimizing feature combinations. The RFR importance score screened the top five important features, including vegetation indices land surface water index (LSWI), generalized difference vegetation index (GDVI), normalized difference yellowness index (NDYI), and backscatter coefficients VV and VH. Vegetation index features characterized canopy moisture and the color of daylilies, and the backscatter coefficient reflected dielectric properties and geometric structure. The selected features were sensitive to daylily LAI. The RFR algorithm had good anti-noise performance and strong fitting ability; thus, its accuracy was better than the partial least squares regression and artificial neural network models. Synergistic optical and microwave data more comprehensively reflected the physical and chemical properties of daylilies, making the RFR-VI-BC05 model after feature selection better than the others ( r = 0.711, RMSE = 0.498, and NRMSE = 9.10%). This study expanded methods for estimating daylily LAI by combining optical and radar data, providing technical support for daylily management. Full article
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25 pages, 3615 KiB  
Article
Impact of Polymer-Coated Controlled-Release Fertilizer on Maize Growth, Production, and Soil Nitrate in Sandy Soils
by Morgan Morrow, Vivek Sharma, Rakesh K. Singh, Jonathan Adam Watson, Gabriel Maltais-Landry and Robert Conway Hochmuth
Agronomy 2025, 15(2), 455; https://doi.org/10.3390/agronomy15020455 - 13 Feb 2025
Abstract
Polymer-coated controlled-release fertilizers’ (CRFs) unique nutrient release mechanism has the potential to mitigate the leaching of mobile soil nutrients, such as nitrate-nitrogen (NO3-N). The study aimed to evaluate the capacity of a polymer-coated CRFs to maintain maize (Zea mays L.) [...] Read more.
Polymer-coated controlled-release fertilizers’ (CRFs) unique nutrient release mechanism has the potential to mitigate the leaching of mobile soil nutrients, such as nitrate-nitrogen (NO3-N). The study aimed to evaluate the capacity of a polymer-coated CRFs to maintain maize (Zea mays L.) crop growth/health indicators and production goals, while reducing NO3-N leaching risks compared to conventional (CONV) fertilizers in North Florida. Four CRF rates (168, 224, 280, 336 kg N ha−1) were assessed against a no nitrogen (N) application and the current University of Florida Institute for Food and Agricultural Sciences (UF/IFAS) recommended CONV (269 kg N ha−1) fertilizer rate. All CRF treatments, even the lowest CRF rate (168 kg N ha−1), produced yields, leaf tissue N concentrations, plant heights, aboveground biomasses (AGB), and leaf area index (LAI) significantly (p < 0.05) greater than or similar to the CONV fertilizer treatment. Additionally, in 2022, the CONV fertilizer treatment resulted in increases in late-season movement of soil NO3-N into highly leachable areas of the soil profile (60–120 cm), while none of the CRF treatments did. However, back-to-back leaching rainfall (>76.2 mm over three days) events in the 2023 growing season masked any trends as NO3-N was likely completely flushed from the system. The results of this two-year study suggest that polymer-coated CRFs can achieve desirable crop growth, crop health, and production goals, while also having the potential to reduce the late-season leaching potential of NO3-N; however, more research is needed to fully capture and quantify the movement of NO3-N through the soil profile. Correlation and Principal Component Analysis (PCA) revealed that CRF performance was significantly influenced by environmental factors such as rainfall and temperature. In 2022, temperature-driven nitrogen release aligned with crop uptake, supporting higher yields and minimizing NO3-N movement. In 2023, however, rainfall-driven variability led to an increase in NO3-N leaching and masked the benefits of CRF treatments. These analyses provided critical insights into the relationships between environmental factors and CRF performance, emphasizing the importance of adaptive fertilizer management under varying climatic conditions. Full article
(This article belongs to the Special Issue Conventional and Alternative Fertilization of Crops)
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20 pages, 2385 KiB  
Article
Disentangling Taxonomic Complexity in the Native Range: Morphological and Genetic Differentiation Among Subspecies of Taeniatherum caput-medusae (Poaceae)
by Morgan L. Hinkle, René F. H. Sforza, James F. Smith, Marcelo D. Serpe and Stephen J. Novak
Agronomy 2025, 15(2), 454; https://doi.org/10.3390/agronomy15020454 - 13 Feb 2025
Abstract
The timely and accurate identification of invasive species is a critical first step in recognizing the threats that they present in their new habitats. The accurate identification of an invasive species, however, can prove difficult if that species displays taxonomic complexity in its [...] Read more.
The timely and accurate identification of invasive species is a critical first step in recognizing the threats that they present in their new habitats. The accurate identification of an invasive species, however, can prove difficult if that species displays taxonomic complexity in its native range, i.e., it consists of morphologically similar subspecies. Across its native range, the grass Taeniatherum caput-medusae (medusahead) exhibits taxonomic complexity: three subspecies have been recognized. As part of our ongoing research to better understand the invasion of T. caput-medusae in the western United States, the accurate identification of these three subspecies is a requisite first step. Plants from each native population were grown in a greenhouse common garden, harvested at maturity, and measured using five previously described morphological characteristics. Three characteristics, glume length, glume angle, and palea length, were found to be statistically significant, and are diagnostic in differentiating the three subspecies. The results for the two other characteristics were not significantly different, although conical cell prominence was only slightly non-significant (p = 0.0532). Genetic differentiation among native populations of T. caput-medusae was assessed using allozymes as molecular markers. Results of an UPGMA cluster diagram based on allozyme data indicate that subspecies crinitum is genetically differentiated from the other two, some populations of subspecies caput-medusae and asperum co-occur within a cluster, and subspecies asperum is the most variable. Results of the analysis of multilocus genotypes are generally consistent with the UPGMA diagram (e.g., subspecies caput-medusae and asperum share six multilocus genotypes). Our findings confirm the need for a better understanding of the taxonomic complexity that can be found within the native ranges of invasive species. Full article
(This article belongs to the Section Crop Breeding and Genetics)
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20 pages, 11693 KiB  
Article
Long-Term Annual Changes in Agricultural Carbon Footprints and Associated Driving Factors in China from 2000 to 2020
by Xingyuan Xiao, Xuanming Hu, Yaqun Liu and Changhe Lu
Agronomy 2025, 15(2), 453; https://doi.org/10.3390/agronomy15020453 - 13 Feb 2025
Abstract
China is one of the world’s largest agricultural producers, and its agricultural carbon footprint (CF) is a major contributor to global warming. However, the long-term annual changes in its agricultural CF and the underlying driving factors remain largely unknown, compromising the scientific basis [...] Read more.
China is one of the world’s largest agricultural producers, and its agricultural carbon footprint (CF) is a major contributor to global warming. However, the long-term annual changes in its agricultural CF and the underlying driving factors remain largely unknown, compromising the scientific basis for effective carbon reduction and sustainable agriculture management. To this end, we used the life cycle assessment (LCA) method and statistical data to calculate long-term annual agricultural CFs in China. We then adopted the linear regression slope and the Moran’s I method to analyze the temporal trends and spatial clustering characteristics and revealed the correlations between the main drivers and agricultural CFs. The results showed that the total (TCF) and farmland-averaged carbon footprint (FCF) of crop production both increased first and then decreased in China from 2000 to 2020, with a turning point in 2015. Overall, the TCF increased by 6.82% (3022.16 × 104 t CO2 eq), while the FCF slightly decreased by 0.004% (0.01 t CO2 eq/ha). Both the TCF and the FCF showed spatial heterogeneity, with high values in the east and low values in the west, and the spatial clustering of the TCF and its components has weakened over time. Fertilizer (39.26%) and paddy (27.38%) were the main contributors to TCF. Driver analysis found that grain yield was positively correlated with TCF in most provinces, indicating that the continuous yield increase has brought greater pressure on agricultural carbon emission reduction in China. Agricultural stakeholders should optimize crop planting structures and patterns and improve resource-use efficiencies through technological and management innovation to adapt to these threats and achieve low-carbon agriculture. The findings of our research can aid the scientific research on spatiotemporal estimation and driver analysis of agricultural CFs and provide decision-making support for sustainable agricultural practices. Full article
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15 pages, 1572 KiB  
Article
Characterization of Olive-Resistant Genes Against Spilocaea oleagina, the Causal Agent of Scab
by Cristina Estudillo, Adrián Pérez-Rial, Francisco Abel Guerrero-Páez, Concepción M. Díez, Juan Moral and José V. Die
Agronomy 2025, 15(2), 452; https://doi.org/10.3390/agronomy15020452 - 12 Feb 2025
Abstract
The olive tree (Olea europaea subsp. europaea L.) is one of the most important perennial crops in the Mediterranean Basin. Olive Scab, caused by the fungal species Spilocaea oleagina, a member of the Venturiaceae family, is among the most significant diseases [...] Read more.
The olive tree (Olea europaea subsp. europaea L.) is one of the most important perennial crops in the Mediterranean Basin. Olive Scab, caused by the fungal species Spilocaea oleagina, a member of the Venturiaceae family, is among the most significant diseases affecting olive cultivation, prompting farmers to spend millions of euros annually on fungicides for its control. The fungal genus Venturia includes highly specialized species responsible for diseases in other crops, such as Apple Scab, caused by V. inaequalis. One of the most effective control strategies for Apple Scab has been developing and using resistant varieties. However, in the case of Olive Scab, genetic resistance remains relatively underexplored. In apples, breeders have identified approximately 20 resistance genes against V. inaequalis, known as Rvi genes, over recent decades. In this study, we identified and characterized four homologous genes to the Rvi family in olive, analyzing their genomic organization and expression profiles in silico. A total of 14 homologous sequences were identified in the olive genome, all sharing conserved domains typical of the leucine-rich repeat (LRR) superfamily, widely associated with plant immune responses. Functional annotation using gene ontology indicated enrichment in categories related to stimulus response and diverse biological processes. Notably, homologous sequences corresponding to apple proteins linked to V. inaequalis resistance exhibited high expression levels in response to biotic and abiotic stresses. These results indicate that olive trees may harbor resistance mechanisms analogous to those observed in apples, providing a foundation for further research into olive disease resistance and breeding programs. Full article
(This article belongs to the Section Pest and Disease Management)
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45 pages, 1708 KiB  
Review
The Role of Ligninolytic Enzymes in Sustainable Agriculture: Applications and Challenges
by Agnieszka Gałązka, Urszula Jankiewicz and Sławomir Orzechowski
Agronomy 2025, 15(2), 451; https://doi.org/10.3390/agronomy15020451 - 12 Feb 2025
Abstract
The most important ligninolytic enzymes in lignin degradation include laccases and peroxidases (lignin peroxidase, manganese peroxidase, versatile peroxidase). White-rot fungi (e.g., Cerrena sp., Phlebia sp. or Trametes sp.) are their main source in nature. The ability of ligninolytic enzymes to degrade both phenolic [...] Read more.
The most important ligninolytic enzymes in lignin degradation include laccases and peroxidases (lignin peroxidase, manganese peroxidase, versatile peroxidase). White-rot fungi (e.g., Cerrena sp., Phlebia sp. or Trametes sp.) are their main source in nature. The ability of ligninolytic enzymes to degrade both phenolic and non-phenolic compounds has found its application in sustainable agriculture. In recent years, ligninolytic enzymes’ important role has been demonstrated in the biodegradation of lignin, a poorly degradable component of plant biomass, and in removing hazardous environmental pollutants that threaten human health. These enzymes can be successfully used in waste management, composting, improving soil health and fertility, or bioremediation. The challenges of applying lignin-degrading enzymes such as laccases and peroxidases include their stability and resistance to harsh conditions. Still, the rapid development of biotechnological technologies offers the tools to overcome them. Applying biological solutions in agricultural systems involving microorganisms and their metabolic products will significantly reduce the environmental impact and develop a circular economy. Full article
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21 pages, 7131 KiB  
Article
High-Throughput 3D Rice Chalkiness Detection Based on Micro-CT and VSE-UNet
by Zhiqi Cai, Yangjun Deng, Xinghui Zhu, Bo Li, Chenglin Xu and Donghui Li
Agronomy 2025, 15(2), 450; https://doi.org/10.3390/agronomy15020450 - 12 Feb 2025
Abstract
Rice is a staple food for nearly half the global population and, with rising living standards, the demand for high-quality grain is increasing. Chalkiness, a key determinant of appearance quality, requires accurate detection for effective quality evaluation. While traditional 2D imaging has been [...] Read more.
Rice is a staple food for nearly half the global population and, with rising living standards, the demand for high-quality grain is increasing. Chalkiness, a key determinant of appearance quality, requires accurate detection for effective quality evaluation. While traditional 2D imaging has been used for chalkiness detection, its inherent inability to capture complete 3D morphology limits its suitability for precision agriculture and breeding. Although micro-CT has shown promise in 3D chalk phenotype analysis, high-throughput automated 3D detection for multiple grains remains a challenge, hindering practical applications. To address this, we propose a high-throughput 3D chalkiness detection method using micro-CT and VSE-UNet. Our method begins with non-destructive 3D imaging of grains using micro-CT. For the accurate segmentation of kernels and chalky regions, we propose VSE-UNet, an improved VGG-UNet with an SE attention mechanism for enhanced feature learning. Through comprehensive training optimization strategies, including the Dice focal loss function and dropout technique, the model achieves robust and accurate segmentation of both kernels and chalky regions in continuous CT slices. To enable high-throughput 3D analysis, we developed a unified 3D detection framework integrating isosurface extraction, point cloud conversion, DBSCAN clustering, and Poisson reconstruction. This framework overcomes the limitations of single-grain analysis, enabling simultaneous multi-grain detection. Finally, 3D morphological indicators of chalkiness are calculated using triangular mesh techniques. Experimental results demonstrate significant improvements in both 2D segmentation (7.31% improvement in chalkiness IoU, 2.54% in mIoU, 2.80% in mPA) and 3D phenotypic measurements, with VSE-UNet achieving more accurate volume and dimensional measurements compared with the baseline. These improvements provide a reliable foundation for studying chalkiness formation and enable high-throughput phenotyping. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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19 pages, 1787 KiB  
Article
Genetic Trends in Seven Years of Maize Breeding at Mozambique’s Institute of Agricultural Research
by Pedro Fato, Pedro Chaúque, Constantino Senete, Egas Nhamucho, Clay Sneller, Samuel Mutiga, Lennin Musundire, Dagne Wegary, Biswanath Das and Boddupalli M. Prasanna
Agronomy 2025, 15(2), 449; https://doi.org/10.3390/agronomy15020449 - 12 Feb 2025
Abstract
Assessing genetic gains from historical data provides insights to improve breeding programs. This study evaluated the Mozambique National Maize Program’s (MNMP’s) genetic gains using data from advanced germplasm trials conducted at 21 locations between 2014 and 2020. Genetic gains were calculated by regressing [...] Read more.
Assessing genetic gains from historical data provides insights to improve breeding programs. This study evaluated the Mozambique National Maize Program’s (MNMP’s) genetic gains using data from advanced germplasm trials conducted at 21 locations between 2014 and 2020. Genetic gains were calculated by regressing the genotypic best linear unbiased estimates of grain yield and complementary agronomic traits against the initial year of genotype evaluation (n = 592). The annual genetic gain was expressed as a percentage of the trait mean. While grain yield, the primary breeding focus, showed no significant improvement, significant gains were observed for the plant height (0.67%), ear height (1.74%), ears per plant (1.31%), ear position coefficient (1.22%), and husk cover (4.7%). Negative genetic gains were detected for the days to anthesis (−0.5%), the anthesis–silking interval or ASI (−9.31%), and stalk lodging (−5.01%). These results indicate that while MNMP did not achieve the desired positive genetic gain for grain yield, progress was made for traits related to plant resilience, particularly the ASI and stalk lodging. MNMP should seek to incorporate new breeding technologies and human resources to enhance genetic gains for grain yield and other key traits in the maize breeding program, while developing and deploying high-yielding, climate-resilient maize varieties to address emerging food security challenges in Mozambique. Full article
(This article belongs to the Special Issue Maize Germplasm Improvement and Innovation)
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14 pages, 1045 KiB  
Article
Screening of Sugarcane Genotypes for Smut (Sporisorium scitamineum) Resistance Under Greenhouse Conditions
by Lucélia de Fátima Santos, Felipe Brussolo da Silva, Luciana Oliveira Souza Anjos, Laudecir Lemos Raiol Júnior, Ivan Antônio dos Anjos, Tanuza de Carvalho Fernandes, Marcel Fernando da Silva, Dilermando Perecin, Antônio de Goes and Luciana Rossini Pinto
Agronomy 2025, 15(2), 448; https://doi.org/10.3390/agronomy15020448 - 12 Feb 2025
Abstract
Sugarcane is one of the most economically important crops, particularly in Brazil, which is the largest sugarcane producer globally. Sugarcane smut, caused by the fungus Sporisorium scitamineum (Syd.), is a major disease of this crop. This study investigated the response of 165 sugarcane [...] Read more.
Sugarcane is one of the most economically important crops, particularly in Brazil, which is the largest sugarcane producer globally. Sugarcane smut, caused by the fungus Sporisorium scitamineum (Syd.), is a major disease of this crop. This study investigated the response of 165 sugarcane genotypes to smut infection under greenhouse conditions using the needle-bud puncture method. The disease incidence, the Area Under the Disease Progress Curve (AUDPC), and the relative Area Under the Disease Progress Curve (rAUDPC) were calculated, along with broad-sense heritability (h2) and the genotype’s effects. Spearman’s correlation coefficient (r2) was used to determine the correlation between the number of corresponding genotypes with smut incidence in both the greenhouse and the field. The incidence of smut ranged from 0% to 88%, and AUDPC values varied from 0 to 500 for 131 of the 165 genotypes. Based on the rAUDPC, 54 genotypes were classified as highly resistant. The correlation between greenhouse and field disease expression was positive and moderately strong (r² = 61%), and the h2 value in greenhouse conditions was 74%. The needle-bud puncture method combined with the rAUDPC values was promising for identifying susceptible genotypes and highlighting potential smut-resistant genotypes. Full article
(This article belongs to the Section Crop Breeding and Genetics)
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27 pages, 3862 KiB  
Article
Research on Remote Sensing Monitoring of Key Indicators of Corn Growth Based on Double Red Edges
by Ying Yin, Chunling Chen, Zhuo Wang, Jie Chang, Sien Guo, Wanning Li, Hao Han, Yuanji Cai and Ziyi Feng
Agronomy 2025, 15(2), 447; https://doi.org/10.3390/agronomy15020447 - 12 Feb 2025
Abstract
The variation in crop growth provides critical insights for yield estimation, crop health diagnosis, precision field management, and variable-rate fertilization. This study constructs key monitoring indicators (KMIs) for corn growth based on satellite remote sensing data, along with inversion models for these growth [...] Read more.
The variation in crop growth provides critical insights for yield estimation, crop health diagnosis, precision field management, and variable-rate fertilization. This study constructs key monitoring indicators (KMIs) for corn growth based on satellite remote sensing data, along with inversion models for these growth indicators. Initially, the leaf area index (LAI) and plant height were integrated into the KMI by calculating their respective weights using the entropy weight method. Eight vegetation indices derived from Sentinel-2A satellite remote sensing data were then selected: the Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI), Soil-Adjusted Vegetation Index (SAVI), Red-Edge Inflection Point (REIP), Inverted Red-Edge Chlorophyll Index (IRECI), Pigment Specific Simple Ratio (PSSRa), Terrestrial Chlorophyll Index (MTCI), and Modified Chlorophyll Absorption Ratio Index (MCARI). A comparative analysis was conducted to assess the correlation of these indices in estimating corn plant height and LAI. Through recursive feature elimination, the most highly correlated indices, REIP and IRECI, were selected as the optimal dual red-edge vegetation indices. A deep neural network (DNN) model was established for estimating corn plant height, achieving optimal performance with an R2 of 0.978 and a root mean square error (RMSE) of 2.709. For LAI estimation, a DNN model optimized using particle swarm optimization (PSO) was developed, yielding an R2 of 0.931 and an RMSE of 0.130. KMI enables farmers and agronomists to monitor crop growth more accurately and in real-time. Finally, this study calculated the KMI by integrating the inversion results for plant height and LAI, providing an effective framework for crop growth assessment using satellite remote sensing data. This successfully enables remote sensing-based growth monitoring for the 2023 experimental field in Haicheng, making the precise monitoring and management of crop growth possible. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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24 pages, 7672 KiB  
Review
Turning Waste Wool into a Circular Resource: A Review of Eco-Innovative Applications in Agriculture
by Francesca Camilli, Marco Focacci, Aldo Dal Prà, Sara Bortolu, Francesca Ugolini, Enrico Vagnoni and Pierpaolo Duce
Agronomy 2025, 15(2), 446; https://doi.org/10.3390/agronomy15020446 - 11 Feb 2025
Abstract
Agriculture significantly impacts the environment in terms of greenhouse gas emissions, soil nutrient depletion, water consumption, and pollution and waste produced by intensive farming. Wool has great potential and can be a valuable resource for agriculture due to its high nitrogen, carbon, and [...] Read more.
Agriculture significantly impacts the environment in terms of greenhouse gas emissions, soil nutrient depletion, water consumption, and pollution and waste produced by intensive farming. Wool has great potential and can be a valuable resource for agriculture due to its high nitrogen, carbon, and sulfur content and good water absorption and retention properties, benefiting soil carbon storage and fertility, as well as decreasing the risk of water contamination due to the slow decomposition and nitrogen release. This review aims to provide an overview of bio-based solutions that can benefit agroecosystems as a circular bioeconomy practice. Raw wool and wool hydrolysate are the most common applications, but also wool pellets, wool compost, and wool mats are interesting treatments for plant growing. Waste wool showed positive effects on soil fertility by primarily increasing nitrogen and sulfur content. Improved water retention capacity and microbial activity were also recorded in several studies. The use of wool as mulching is effective for weed control. Attention to the plant species tested aimed at identifying the most promising cultivations in terms of treatment efficiency, possibly lowering environmental impact on the agroecosystem. To eco-design and scale-up processes that strengthen the circular use of wool into widespread practices, further research should be encouraged in conjunction with environmental impact assessments and economic evaluations. Full article
(This article belongs to the Special Issue Organic Improvement in Agricultural Waste and Byproducts)
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19 pages, 6474 KiB  
Article
Improved Lightweight YOLOv8 Model for Rice Disease Detection in Multi-Scale Scenarios
by Jinfeng Wang, Siyuan Ma, Zhentao Wang, Xinhua Ma, Chunhe Yang, Guoqing Chen and Yijia Wang
Agronomy 2025, 15(2), 445; https://doi.org/10.3390/agronomy15020445 - 11 Feb 2025
Abstract
In response to the challenges of detecting rice pests and diseases at different scales and the difficulties associated with deploying and running models on embedded devices with limited computational resources, this study proposes a multi-scale rice pest and disease recognition model (RGC-YOLO). Based [...] Read more.
In response to the challenges of detecting rice pests and diseases at different scales and the difficulties associated with deploying and running models on embedded devices with limited computational resources, this study proposes a multi-scale rice pest and disease recognition model (RGC-YOLO). Based on the YOLOv8n network, which includes an SPPF layer, the model introduces a structural reparameterization module (RepGhost) to achieve implicit feature reuse through reparameterization. GhostConv layers replace some standard convolutions, reducing the model’s computational cost and improving inference speed. A Hybrid Attention Module (CBAM) is incorporated into the backbone network to enhance the model’s ability to extract important features. The RGC-YOLO model is evaluated for accuracy and inference time on a multi-scale rice pest and disease dataset, including bacterial blight, rice blast, brown spot, and rice planthopper. Experimental results show that RGC-YOLO achieves a precision (P) of 86.2%, a recall (R) of 90.8%, and a mean average precision at Intersection over Union 0.5(mAP50) of 93.2%. In terms of model size, the parameters are reduced by 33.2%, and GFLOPs decrease by 29.27% compared to the base YOLOv8n model. Finally, the RGC-YOLO model is deployed on an embedded Jetson Nano device, where the inference time per image is reduced by 21.3% compared to the base YOLOv8n model, reaching 170 milliseconds. This study develops a multi-scale rice pest and disease recognition model, which is successfully deployed on embedded field devices, achieving high-accuracy real-time monitoring and providing valuable reference for intelligent equipment in unmanned farms. Full article
(This article belongs to the Section Pest and Disease Management)
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17 pages, 1495 KiB  
Article
Optimized Phosphorus Application Under Water Stress Enhances Photosynthesis, Physiological Traits, and Yield in Soybean During Flowering Stage
by Qu Chen, Tangzhe Nie, Yang Li, Hao Li, Yubo Sun, Yuzhe Wu, Yuxian Zhang and Mengxue Wang
Agronomy 2025, 15(2), 444; https://doi.org/10.3390/agronomy15020444 - 11 Feb 2025
Abstract
Phosphorus application is widely regarded as a key measure for improving crop resistance to drought. This study investigated the effect of appropriate phosphorus fertilization on photosynthesis, physiological traits, and yield under water stress during the soybean flowering stage and selected the drought-sensitive soybean [...] Read more.
Phosphorus application is widely regarded as a key measure for improving crop resistance to drought. This study investigated the effect of appropriate phosphorus fertilization on photosynthesis, physiological traits, and yield under water stress during the soybean flowering stage and selected the drought-sensitive soybean variety “Sui Nong 26” as the pot experiment object under a completely randomized design. The experiment was designed with three irrigation lower limits, corresponding to 70%, 60%, and 50% of the field capacity (FC), referred to as T1, T2, and T3. Four phosphorus fertilizer applications were also included: 0, 40, 50, and 60 mg·kg (designated as P0, P1, P2, and P3), resulting in a total of 12 treatments. Photosynthetic parameters, antioxidant enzyme activities, membrane lipid peroxidation, osmotic adjustment substances, yield, and yield components were measured to assess the effects of phosphorus fertilization on drought resistance. Results showed that under water stress, moderate phosphorus application (P1 and P2) enhanced photosynthetic capacity, antioxidation, osmotic adjustment, and yield, particularly by scavenging excess reactive oxygen species, protecting cells from oxidative damage, and maintaining metabolic balance, leading to increased yield. The average net photosynthetic rate and yield per plant under P1 and P2 levels increased by 33.53% and 37.67%, and 20.7% and 15.6%, respectively, compared to P0. In contrast, excessive phosphorus application (P3) improved the above parameters but had a significantly lower effect than moderate phosphorus application. Thus, appropriate phosphorus application is crucial for soybeans under water stress. Moderate application not only alleviates drought stress but also boosts soybean yield. This study highlights the importance of appropriate phosphorus use for mitigating water stress, offering scientific evidence for its practical application in agriculture. At the same time, with the increasing severity of climate change and water scarcity, phosphorus fertilizer application strategies under varying water conditions provide critical support for the application of precision agriculture technologies and ensuring food security. Full article
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18 pages, 5797 KiB  
Article
Prediction and Impact Analysis of Soil Nitrogen and Salinity Under Reclaimed Water Irrigation: A Case Study
by Zeyu Liu, Kai Fang, Xiaoqin Sun, Yandong Wang, Zhuo Tian, Jing Liu, Liying Bai and Qilin He
Agronomy 2025, 15(2), 443; https://doi.org/10.3390/agronomy15020443 - 11 Feb 2025
Abstract
Reclaimed water irrigation is increasingly being applied to address global water scarcity, yet its long-term effects on soil nitrogen cycling and salinity dynamics, particularly in agricultural and agroforestry systems, remain complex and insufficiently understood. Understanding these impacts is crucial for developing sustainable practices [...] Read more.
Reclaimed water irrigation is increasingly being applied to address global water scarcity, yet its long-term effects on soil nitrogen cycling and salinity dynamics, particularly in agricultural and agroforestry systems, remain complex and insufficiently understood. Understanding these impacts is crucial for developing sustainable practices that optimize resource use while ensuring the long-term health and viability of agricultural and agroforestry systems. This study employs genetic-algorithm-optimized random forest models (GA-RF1 and GA-RF2) to examine the dynamics of nitrogen indicators (NO3-N, NH4+-N, and TN) and salinity indicators (EC and Cl) under reclaimed water irrigation. The models achieved high predictive accuracy, with NSE values of 0.918, 0.946, 0.936, 0.967, and 0.887 for NO3-N, NH4+-N, TN, EC, and Cl, respectively, demonstrating their robustness. Key drivers of nitrogen indicators were identified as irrigation duration (years), fecal coliform levels, and soil depth, while salinity indicators were primarily influenced by land use type and the chemical composition of reclaimed water, including chemical oxygen demand, total phosphorus, and total nitrogen. Spatial analysis revealed significant nitrogen and salinity accumulation in surface soils with extended irrigation, particularly in farmland, where NO3-N and NH4+-N peaked at 25 mg/kg and 15 mg/kg, respectively. EC exceeded 700 µS/cm during early irrigation stages but remained within crop tolerance levels. Conversely, grassland and woodland exhibited minimal nitrogen and salinity accumulation. These findings underscore the need for targeted management strategies to mitigate nitrogen and salinity buildup, particularly in farmland, to ensure long-term soil health and productivity under reclaimed water irrigation systems. Full article
(This article belongs to the Section Water Use and Irrigation)
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18 pages, 1804 KiB  
Article
Effects of Biostimulant Foliar Applications on Morphological Traits, Yield, Antioxidant Capacity, and Essential Oil Composition of Thymus vulgaris L. Under Field Conditions
by Loriana Cardone, Flavio Polito, Michele Denora, Donato Casiello, Donato Castronuovo, Nunzia Cicco, Michele Perniola, Vincenzo De Feo and Vincenzo Candido
Agronomy 2025, 15(2), 442; https://doi.org/10.3390/agronomy15020442 - 11 Feb 2025
Abstract
Plant biostimulants are used to promote plant growth by increasing tolerance to abiotic stressors and improving the efficiency of natural resource use. In the present two-year research (2022–2023 and 2023–2024), the effects of biostimulant foliar applications on the morphological parameters, fresh and dry [...] Read more.
Plant biostimulants are used to promote plant growth by increasing tolerance to abiotic stressors and improving the efficiency of natural resource use. In the present two-year research (2022–2023 and 2023–2024), the effects of biostimulant foliar applications on the morphological parameters, fresh and dry yields, antioxidant capacity, total phenolic content, and chemical composition of the essential oil of thyme (Thymus vulgaris L.) were studied. For this purpose, four commercial biostimulants, Biostimol Plus + Peptamin-V Plus®, Acadian MPE®, Megafol®, and BlueN®, were evaluated on thyme cultivated in field conditions. The experiment was laid out in a randomized block design with five treatments and with three replications. During the second growing season, the plants treated with BlueN®, composed of the bacteria Methylobacterium symbioticum SB23, showed the highest plant weight (152.1 g plant−1), fresh biomass yield (501.9 g m−2), and dry yield (172.2 g m−2). BlueN® was the biostimulant that also obtained the highest essential oil yield in both years (0.47 and 0.53%), and for all biostimulants, the amount of thymol and carvacrol increased in the second year, especially with Megafol® (63.75 and 3.16%). The antioxidant capacity was enhanced in the second year by all biostimulants, according to the ABTS assay, but in particular, by BlueN® and BPPVP (26.97 μmol/g and 25.01 μmol/g), while the phenolic content was higher in the first year, especially with BlueN® (65.98 mg GAE/g Extract). The other biostimulants had less intense effects. In conclusion, the biostimulants influenced some characteristics of the essential oil, but the greatest influencers were BlueN®, Megafol®, and BPPVP. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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17 pages, 6994 KiB  
Article
Integrative Transcriptomic and Metabolomic Analysis Reveals Regulatory Networks and Metabolite Dynamics in Gastrodia elata Flower Development
by Hongyu Chen, Ying Yu, Jiehong Zhao and Jian Zhang
Agronomy 2025, 15(2), 441; https://doi.org/10.3390/agronomy15020441 - 11 Feb 2025
Abstract
Flower development, a vital phase in the plant life cycle, involves intricate physiological and morphogenetic processes driven by dynamic molecular and metabolic processes. However, the specific molecular mechanisms and metabolite accumulation patterns during Gastrodia elata flower development remain largely unknown. This study utilized [...] Read more.
Flower development, a vital phase in the plant life cycle, involves intricate physiological and morphogenetic processes driven by dynamic molecular and metabolic processes. However, the specific molecular mechanisms and metabolite accumulation patterns during Gastrodia elata flower development remain largely unknown. This study utilized Illumina’s next-generation sequencing to analyze the G. elata flower transcriptome across three critical developmental stages, capturing gene expression changes, particularly those related to transcription factors that regulate flower formation and metabolite accumulation. FPKM analysis showed significant transcriptomic changes during G. elata flower development, while targeted metabolomics identified key metabolites with stage-specific variations via widely targeted metabolic profiling. Here, integrative transcriptome and metabolome analyses were performed to investigate floral genes and compounds in G. elata flowers at three different developmental stages. The differentially expressed genes (DEGs) and significant changes in metabolites (SCMs) involved in key biological pathways were identified. This approach aimed to identify functional genes or pathways jointly enriched in metabolites, thereby defining pathways linked to crucial biological phenotypes. By mapping DEGs and SCMs to KEGG pathways, the comprehensive network was constructed, uncovering functional relationships between gene expression and metabolite accumulation. This study proposes dynamic models of transcriptomic and metabolite changes, revealing key regulatory networks that govern G. elata flower development and potential applications. Full article
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20 pages, 1829 KiB  
Article
Selenium Biofortification with Se-Enriched Urea and Se-Enriched Ammonium Sulfate Fertilization in Different Common Bean Genotypes
by Filipe Aiura Namorato, Patriciani Estela Cipriano, Stefânia Barros Zauza, Pedro Antônio Namorato Benevenute, Suellen Nunes de Araújo, Raphael Felipe Rodrigues Correia, Ivan Célio Andrade Ribeiro, Everton Geraldo de Morais, Fábio Aurélio Dias Martins, Maria Ligia de Souza Silva and Luiz Roberto Guimarães Guilherme
Agronomy 2025, 15(2), 440; https://doi.org/10.3390/agronomy15020440 - 11 Feb 2025
Abstract
Common beans are an essential food source worldwide, particularly in developing countries, and are grown in soils poor in selenium (Se), a mineral essential for human health. Adding Se to fertilizers is a promising technique; however, more studies are needed on the efficacy [...] Read more.
Common beans are an essential food source worldwide, particularly in developing countries, and are grown in soils poor in selenium (Se), a mineral essential for human health. Adding Se to fertilizers is a promising technique; however, more studies are needed on the efficacy of this technique on common beans. This study aimed to evaluate the biofortification utilizing Se-enriched nitrogen fertilizers on common bean seeds’ agronomic, physiological, and nutritional characteristics. The pot experiment used a randomized block design with five treatments (urea, Se-enriched urea, ammonium sulfate, Se-enriched ammonium sulfate, and without N and Se), four genotypes (BRS Cometa, BRS Estilo, BRSMG Madrepérola and Pérola), and three replicates. The highest seed yield was 28.31 g pot−1 with Pérola genotype fertilized Se-enriched ammonium sulfate. Photosynthetic rates ranged from 30.37 to 39.06 µmol m−2 s−1 for Pérola and BRSMG Madrepérola, both with Se-enriched ammonium sulfate. The highest seed Se concentration was 11.17 µg g−1, with BRSMG Madrepérola fertilized with Se-enriched urea being 22.02%, 17.64%, and 22.47% higher than BRS Cometa, BRS Estilo, and Pérola, respectively. Se-enriched nitrogen fertilizers boost seed yield and alter physiological responses based on genotypes and Se-fertilizer interactions. Se-enriched fertilizers applied to soil can increase the Se concentration in common beans. Full article
(This article belongs to the Special Issue Agronomic Biofortification Practices on Crops)
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12 pages, 228 KiB  
Article
The Effects of Organic Fertilizer Applications on the Nutrient Elements Content of Eggplant Seeds
by Sevinç Başay, Saliha Dorak and Barış Bülent Aşik
Agronomy 2025, 15(2), 439; https://doi.org/10.3390/agronomy15020439 - 11 Feb 2025
Abstract
This research was carried out to investigate the effectiveness of using organic fertilizers in improving the organic seed production process and increasing the seed quality needed in organic agriculture production. The experiment was established with organic fertilizers (farmyard manure—FYM, leonardite—L, vermicompost—VC) and the [...] Read more.
This research was carried out to investigate the effectiveness of using organic fertilizers in improving the organic seed production process and increasing the seed quality needed in organic agriculture production. The experiment was established with organic fertilizers (farmyard manure—FYM, leonardite—L, vermicompost—VC) and the eggplant plant ’Pala-49’ variety and conducted for two years. As a result of the study, vegetative growth height varied between 52.65 and 68.06 cm, plant diameter width ranged from 51.85 to 61.20 cm, fruit height ranged from 14.67 to 21.90 cm, and fruit diameter varied between 4.73 and 6.73 cm. These differences were observed among farmyard manure (FYM), leonardite (L), and vermicompost (VC) organic fertilizer applications. In general, it was determined that the first year gave better results. In terms of parameters, the best result in all parameters was obtained from farmyard manure (FYM) organic fertilizer application. In addition, the nutrient element contents of the seed samples were found to be statistically significant. Organic applications significantly increased the nutrient element content of the seed samples according to the control. The nitrogen content varied between 0.242% and 0.271%, and the phosphorus content ranged between 0.274% and 0.456%. The highest K content was determined in farmyard manure (FYM) application in both years (0.272% and 0.309%). In contrast, Fe, Zn, and Mn contents were 35.1 mg kg−1, 63.7 mg kg−1, and 200.7 mg kg−1 in vermicompost (VC) application in the second year, respectively. The effect of the treatments on soil available nutrient content was also found to be significant. The amount of soil available for plant nutrients was higher in the second year. Full article
(This article belongs to the Section Soil and Plant Nutrition)
16 pages, 1673 KiB  
Article
The Effects of Dried Apple Pomace on Fermentation Quality and Proteolysis of Alfalfa Silages
by Tongtong Dai, Jiangyu Long, Guanjun Zhang, Xianjun Yuan and Zhihao Dong
Agronomy 2025, 15(2), 438; https://doi.org/10.3390/agronomy15020438 - 11 Feb 2025
Abstract
This work aimed to evaluate the effects of dried apple pomace (DAP) on the fermentation characteristics and proteolysis of alfalfa silages. The alfalfa was ensiled with (1) no additives (control), (2) 5% DAP, (3) 10% DAP and (4) 15% DAP based on fresh [...] Read more.
This work aimed to evaluate the effects of dried apple pomace (DAP) on the fermentation characteristics and proteolysis of alfalfa silages. The alfalfa was ensiled with (1) no additives (control), (2) 5% DAP, (3) 10% DAP and (4) 15% DAP based on fresh weight (FW) for 1, 3, 7, 14, 30 and 60 days, respectively. With the increasing proportion of DAP, lactic acid bacteria (LAB) count, lactic acid (LA) and dry matter (DM) content linearly (p < 0.05) increased, while the pH, the content of acetic acid (AA), propionic acid (PA), butyric acid (BA) and ammonia nitrogen (NH3-N) linearly (p < 0.05) decreased during ensiling. The 10% and 15% DAP silages had significantly (p < 0.05) lower aerobic bacteria (AB), yeast and enterobacteria counts than the control during ensiling. The contents of nonprotein nitrogen (NPN), peptide nitrogen (peptide-N) and free amino acid nitrogen (FAA-N) and activities of carboxypeptidase, aminopeptidase and acid proteinase linearly (p < 0.05) decreased as DAP proportion increased during ensiling. On day 60, the addition of DAP significantly (p < 0.05) decreased the contents of tryptamine, phenylethylamine, putrescine, cadaverine, histamine, tyramine, spermidine, spermine and total biogenic amines compared with the control. As the DAP ratio increased, the contents of threonine, valine, isoleucine, leucine, phenylalanine, lysine, histidine, arginine, aspartic acid, serine, glutamic, total amino acids, crude protein (CP) and water-soluble carbohydrates (WSCs) linearly (p < 0.05) increased, while the contents of glycine, alanine, cysteine, and proline linearly (p < 0.05) decreased on day 60. Overall, the addition of 15% DAP was optimal as indicated by better fermentation quality and less proteolysis than other treatments. Full article
(This article belongs to the Section Grassland and Pasture Science)
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14 pages, 5789 KiB  
Article
Simulating Pasture Yield Under Alternative Environments and Grazing Management in Wisconsin, USA
by Elissa Chasen, Eric Booth and Claudio Gratton
Agronomy 2025, 15(2), 437; https://doi.org/10.3390/agronomy15020437 - 11 Feb 2025
Abstract
Pasture yield is crucial to the economic viability of grass-based livestock enterprises, yet the difficulty in predicting yields under various environmental and management conditions prevents effective planning. We used USDA-SSURGO data to create a random forest model that predicts pasture yield potential based [...] Read more.
Pasture yield is crucial to the economic viability of grass-based livestock enterprises, yet the difficulty in predicting yields under various environmental and management conditions prevents effective planning. We used USDA-SSURGO data to create a random forest model that predicts pasture yield potential based on soil properties for the state of Wisconsin (USA). This model is highly accurate (RMSE = 0.11 tons/acre, or 4% of the average yield), predicting pasture yields in Wisconsin grasslands to range from 1.0 to5.3 tons/acre, with an average yield of 2.6 tons/acre. We then integrated this model with guidelines from a USDA-NRCS grazing planning tool to adjust pasture yield potential for different levels of grazing intensity. The adjustments were multiplied to the random forest model output and ranged from 0.65 for continuously grazed pasture to 1.2 for pastures rotated more than once per day. The model is available to use within an online decision support tool through an R-shiny interface and can be easily replicated for other states in the Midwest US. The tool is easy to use and can support farmer analysis of the costs and benefits of grass-based agriculture. Full article
(This article belongs to the Section Grassland and Pasture Science)
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13 pages, 4064 KiB  
Article
High-Throughput Sequence Analysis of Microbial Communities of Soybean in Northeast China
by Yuanyuan Wang, Qingyao Bai, Fanqi Meng, Wei Dong, Haiyan Fan, Xiaofeng Zhu, Yuxi Duan and Lijie Chen
Agronomy 2025, 15(2), 436; https://doi.org/10.3390/agronomy15020436 - 10 Feb 2025
Abstract
Soybean, an essential oil crop in China, has witnessed accelerated seed transfer domestically and abroad in recent years. Seed carriage has emerged as a major route for the dissemination of soybean diseases. In this study, 14 soybean cultivars from three northeastern provinces were [...] Read more.
Soybean, an essential oil crop in China, has witnessed accelerated seed transfer domestically and abroad in recent years. Seed carriage has emerged as a major route for the dissemination of soybean diseases. In this study, 14 soybean cultivars from three northeastern provinces were collected and examined for seed-borne microorganisms using traditional detection technology and high-throughput sequencing technology. Through traditional detection techniques, a total of six genera of bacteria and seventeen genera of fungi were isolated from the test varieties. The quantity and types of microorganisms on the seed surface were greater than those on the seed coat and within the seed, while the seed coat and internal seed contained fewer microorganisms. The dominant fungal genera were Cladosporium, Fusarium, Aspergillus, and Alternaria, accounting for 21.23%, 17.45%, 15.57%, and 11.56% of the genera, respectively. The dominant bacterial genera were Pseudomonas, Sphingomonas, and Pantoea, accounting for 37.46%, 17.29%, and 15.27% of the genera, respectively. The dominant genera obtained through traditional seed-carrying assay techniques were also dominant in high-throughput sequencing. However, some dominant genera obtained through high-throughput sequencing were not isolated by traditional methods. High-throughput sequencing analysis revealed that soybean seeds from Jilin Province had the highest abundance of seed-borne fungi, followed by seeds from Liaoning Province and Heilongjiang Province. Jilin Province also had the highest abundance of seed-borne bacteria, followed by Heilongjiang Province and Liaoning Province. The isolation and identification of microorganisms on soybean seeds provide a scientific basis for seed quarantine treatment and disease control, which is of great significance for soybean production in China. Full article
(This article belongs to the Special Issue Recent Advances in Legume Crop Protection)
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