Agronomy

19 pages, 4434 KiB

Open AccessArticle

Monitoring of Heracleum sosnowskyi Manden Using UAV Multisensors: Case Study in Moscow Region, Russia

by Rashid K. Kurbanov, Arkady N. Dalevich, Alexey S. Dorokhov, Natalia I. Zakharova, Nazih Y. Rebouh, Dmitry E. Kucher, Maxim A. Litvinov and Abdelraouf M. Ali

Agronomy 2024, 14(10), 2451; https://doi.org/10.3390/agronomy14102451 - 21 Oct 2024

Viewed by 705

Abstract

Detection and mapping of Sosnowsky’s hogweed (HS) using remote sensing data have proven effective, yet challenges remain in identifying, localizing, and eliminating HS in urban districts and regions. Reliable data on HS growth areas are essential for monitoring, eradication, and control measures. Satellite [...] Read more.

Detection and mapping of Sosnowsky’s hogweed (HS) using remote sensing data have proven effective, yet challenges remain in identifying, localizing, and eliminating HS in urban districts and regions. Reliable data on HS growth areas are essential for monitoring, eradication, and control measures. Satellite data alone are insufficient for mapping the dynamics of HS distribution. Unmanned aerial vehicles (UAVs) with high-resolution spatial data offer a promising solution for HS detection and mapping. This study aimed to develop a method for detecting and mapping HS growth areas using a proposed algorithm for thematic processing of multispectral aerial imagery data. Multispectral data were collected using a DJI Matrice 200 v2 UAV (Dajiang Innovation Technology Co., Shenzhen, China) and a MicaSense Altum multispectral camera (MicaSense Inc., Seattle, WA, USA). Between 2020 and 2022, 146 sites in the Moscow region of the Russian Federation, covering 304,631 hectares, were monitored. Digital maps of all sites were created, including 19 digital maps (orthophoto, 5 spectral maps, and 13 vegetation indices) for four experimental sites. The collected samples included 1080 points categorized into HS, grass cover, and trees. Student’s t-test showed significant differences in vegetation indices between HS, grass, and trees. A method was developed to determine and map HS-growing areas using the selected vegetation indices NDVI > 0.3, MCARI > 0.76, user index BS1 > 0.10, and spectral channel green > 0.14. This algorithm detected HS in an area of 146.664 hectares. This method can be used to monitor and map the dynamics of HS distribution in the central region of the Russian Federation and to plan the required volume of pesticides for its eradication. Full article

(This article belongs to the Special Issue Site-Specific Weed Management (SSWM): Integrating Weed Population Dynamics with Information-Communications Technologies (ICTs))

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20 pages, 2263 KiB

Open AccessArticle

Response of Different Exogenous Phytohormones to Rice Yield Under Low-Temperature Stress at the Filling Stage

by Ke Li, Yunji Xu, Dalu Gu, Xiaodong Yin, Yanyan Jia, Tinggang Wen, Weiqing Jiang, Yang Che, Qisheng Li, Zhangrong Wen, Xiaofeng Du and Wenfei Yang

Agronomy 2024, 14(10), 2450; https://doi.org/10.3390/agronomy14102450 - 21 Oct 2024

Viewed by 637

Abstract

This paper aims to clarify the effects of different exogenous phytohormones on the physiological traits of rice (Oryza sativa L.) at the early stage of irrigation under low-temperature stress. In this study, two types of rice varieties with different temperature sensitivities screened [...] Read more.

This paper aims to clarify the effects of different exogenous phytohormones on the physiological traits of rice (Oryza sativa L.) at the early stage of irrigation under low-temperature stress. In this study, two types of rice varieties with different temperature sensitivities screened out previously, namely, a cold-tolerant variety (Nan Jing 9108) and a low-temperature-sensitive variety (Hui Liang You 898), were used in pots to simulate the process of low-temperature stress in rice at the early stage of grouting (6–9 days after anthesis) with artificial low-temperature treatments. The experimental treatments were 450 mg L⁻¹ Methyl jasmine acid (MJ), 46 mg L⁻¹ Melatonin (MT), 69 mg L⁻¹ Salicylate (SA), 40 mg L⁻¹ Erythromycin (GA₃), 25 mg L⁻¹ Zeatin (Z), 145 mg L⁻¹ Spermidine (SPD), and 5 mg L⁻¹ Abscisic acid (ABA) sprayed on rice before low-temperature stress, while low-temperature treatment without spraying (DK) and conventional planting without spraying (CK) were added as the control. The results showed that compared with the room temperature control (CK, sprayed with deionized water), the low-temperature control (DK, low-temperature treatment, and sprayed with deionized water) all significantly reduced the rice grain yield. Different exogenous hormones sprayed before low-temperature stress could increase rice yield, among which, Z and SPD spraying treatments had a better effect on the yield of Hui Liang You 898, while different exogenous hormone treatments increased the yield of Nan Jing 9108 in an average manner. The Z and SPD treatments increased the yield of Hui Liang You 898 by 24.87% and 26.16% and that of Nan Jing 9108 by 15.87% and 17.80%, respectively. This was mainly attributed to the significant increase in thousand-grain weight and fruiting rate, while there was no significant difference in the number of spikes and number of grains. The different exogenous hormone treatments were able to delay leaf senescence, enhance the photosynthetic production capacity of plants by increasing leaf chlorophyll content, and thus increase the accumulation of photosynthetic assimilation products and population growth rate after flowering. Among them, both Z and SPD treatments resulted in a population growth rate of more than 30% from spike flushing to maturity, which led to a higher dry matter accumulation of the plant at maturity. In addition, in the dry matter distribution of the plant at maturity, the seeds occupied a higher accumulation amount and proportion compared with the respective DK; the SPD treatment resulted in the maximum distribution rate of seeds at maturity of Hui Liang You 898, with an increase of 8.27%, and the Z treatment resulted in the maximum distribution rate of seeds at maturity of Nan Jing 9108, with an increase of 7.34%. At the same time, the Z treatment significantly increased the activities of adenosine diphosphate glucose phosphorylated enzyme (AGP) and starch branching enzyme (SBE) in the grains of both varieties, which resulted in the accumulation of more starch and ultimately increased the rice grain yield. The results verified that different exogenous phytohormones could be used to regulate the insufficiency of grouting caused by low-temperature stress during the grouting and fruiting stages of rice and enriched their agronomic and physiological traits in response at the same time. Full article

(This article belongs to the Special Issue Molecular Regulatory Network of Plant Nutrition Signaling)

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19 pages, 1431 KiB

Open AccessArticle

Multispecies Trichoderma in Combination with Hydrolyzed Lignin Improve Tomato Growth, Yield, and Nutritional Quality of Fruits

by Stefania Lanzuise, Gelsomina Manganiello, Cono Vincenzo, Petronia Carillo, Vito Macchia, Suvi Pietarinen, Giovanna Marta Fusco, Rosalinda Nicastro, Matteo Lorito and Sheridan Lois Woo

Agronomy 2024, 14(10), 2449; https://doi.org/10.3390/agronomy14102449 - 21 Oct 2024

Viewed by 620

Abstract

The application of biological pesticides as alternatives to chemical phytosanitary products is a natural and innovative method to improve environmental protection and sustainable agricultural production. In this work, the compatibility between Trichoderma spp. and a commercial lignin extract was assessed in vitro and [...] Read more.

The application of biological pesticides as alternatives to chemical phytosanitary products is a natural and innovative method to improve environmental protection and sustainable agricultural production. In this work, the compatibility between Trichoderma spp. and a commercial lignin extract was assessed in vitro and in vivo. The beneficial effects of lignin in combination with different Trichoderma consortia were evaluated in terms of improved growth and quantitative and qualitative tomato productivity. T. virens GV41 + T. asperellum + T. atroviride + lignin formulation was the most effective in growth promotion and increased root and stem dry weight compared to control (45.4 and 43.9%, respectively). This combination determined a 63% increase in tomato yield compared to the control, resulting in the best-performing treatment compared to each individual constituent. Consistent differences in terms of lycopene, GABA, ornithine, total, essential, and branched-chain amino acids were revealed in fruits from tomato plants treated with Trichoderma–lignin formulations (T. asperellum + T. virens GV41 + lignin) or with the microbial consortia (T. asperellum + T. virens GV41, T. atroviride + T. virens GV41). The developed bioformulations represent a sustainable biological strategy to increase yield and produce nutritional compound-enriched vegetables. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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14 pages, 2036 KiB

Open AccessArticle

Effects of GroMore^® Program on Rice Yield and GHG Emissions in a Korean Paddy Rice

by Sung Yung Yoo, Jun-Ki Son, Kyoung-Sik Jun and Hyun-Hwoi Ku

Agronomy 2024, 14(10), 2448; https://doi.org/10.3390/agronomy14102448 - 21 Oct 2024

Viewed by 715

Abstract

The agronomic benefits of pesticides combined with amino acid application to increase rice production have been recognized, but they are still not well-known for greenhouse gas (GHG) emissions and mitigation in irrigated paddy fields. Thus, this study was conducted to investigate the combined [...] Read more.

The agronomic benefits of pesticides combined with amino acid application to increase rice production have been recognized, but they are still not well-known for greenhouse gas (GHG) emissions and mitigation in irrigated paddy fields. Thus, this study was conducted to investigate the combined effects of pesticide and amino acid application on rice yield and methane (CH₄) emissions in a Korean rice paddy. A field experiment was conducted with five levels: none (no pesticide application, T1), different conventional practices (combined application of insecticides and fungicide, T2 and T3), and GroMore^® programs (combined application of insecticides, fungicides, and amino acids, T4 and T5). Rice grain yield and yield components were obtained using agronomic measurements. To determine the greenhouse gas intensity (GHGI) of each treatment, CH₄ emissions were measured throughout the rice growing period. Results showed that the chemical applications in combination with amino acids in T4 obtained a higher grain yield and number of panicles per plant compared to T1, T2, and T3, while T4 and T5 showed no difference on filled spikelets except for T2. T3 and T5 showed lower respective cumulative CH₄ emissions by 30% and 32% during the entire rice growing season, compared to no chemical application (T1). Meanwhile, N₂O emissions were negligible in all treatments because the paddy field was flooded most of the growing season. The results of the impact of GroMore^® programs on relatively higher grain yield and lower GHG emissions are presented. In conclusion, the application of pesticides combined with amino acids obtained lower GHGI values. Full article

(This article belongs to the Special Issue Sustainable Agricultural Systems: Enhancing Efficiency and Reducing Environmental Impact)

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23 pages, 9352 KiB

Open AccessArticle

Innovative Design and Optimization of High-Quality Peanut Digging-Inverter

by Haiyang Shen, Man Gu, Hongguang Yang, Jie Ling, Feng Wu, Fengwei Gu, Liang Pan, Zhaoyang Yu and Zhichao Hu

Agronomy 2024, 14(10), 2447; https://doi.org/10.3390/agronomy14102447 - 21 Oct 2024

Viewed by 515

Abstract

To rapidly dry peanut pods and effectively address mold issues resulting from rainy weather, this article provides an analysis of the current research status of global peanut digging, inverting, and harvesting technologies. Based on a two-stage peanut harvesting model, the operating principles of [...] Read more.

To rapidly dry peanut pods and effectively address mold issues resulting from rainy weather, this article provides an analysis of the current research status of global peanut digging, inverting, and harvesting technologies. Based on a two-stage peanut harvesting model, the operating principles of a high-quality peanut digging-inverter are elaborated upon, and the design of key machine components is discussed. The evaluation metrics for the operation of a high-quality peanut digging-inverter include the rate of vine inverting, the soil content rate, the rate of fallen pods, and the rate of buried pods. Utilizing theoretical analysis, the Box–Behnken experimental design is employed to investigate the operating parameters of these machines, with the tractor’s running speed, the linear speed of the inverting roller, and the linear speed of the conveyor chain serving as the experimental factors in a three-factor, three-level experimental study. A regression model is established to analyze the impact of each factor on operational quality and to comprehensively optimize the influencing factors. The experimental results indicate that all factors significantly affect the rate of vine inverting. The tractor’s running speed (X₁) and the linear speed of the inverting roller (X₃) significantly influence the rate of buried pods, while the linear speed of the conveyor chain (X₂) does not have a significant effect on this rate. Similarly, the tractor’s running speed (X₁) and the linear speed of the inverting roller (X₃) significantly affect the rate of fallen pods, whereas the linear speed of the conveyor chain (X₂) does not. Furthermore, the linear speed of the conveyor chain (X₂) and the linear speed of the inverting roller (X₃) significantly impact the soil content rate, while the tractor’s running speed (X₁) does not. The optimal combination of operating parameters is a tractor running speed of 1 m/s, a conveyor chain linear speed of 1.3 m/s, and an inverting roller linear speed of 2.1 m/s. Under these conditions, the high-quality peanut digging-inverter achieves a vine inverting rate of 89.29%, a buried pod rate of 0.31%, a fallen pod rate of 0.74%, and a soil content rate of 8.11%. The experimental values for each evaluation index exhibit relative errors of 1.14%, 6.45%, 1.35%, and 0.13% compared to the optimized values provided by the Design-Expert software. The findings of this research will facilitate the development of hardware conditions for the future intelligent and information-based harvesting of peanuts, thereby establishing a solid foundation for the high-quality initial processing of oilseeds. Full article

(This article belongs to the Section Farming Sustainability)

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23 pages, 7974 KiB

Open AccessArticle

Maize Phenotypic Parameters Based on the Constrained Region Point Cloud Phenotyping Algorithm as a Developed Method

by Qinzhe Zhu, Miaoyuan Bai and Ming Yu

Agronomy 2024, 14(10), 2446; https://doi.org/10.3390/agronomy14102446 - 21 Oct 2024

Viewed by 557

Abstract

As one of the world’s most crucial food crops, maize plays a pivotal role in ensuring food security and driving economic growth. The diversification of maize variety breeding is significantly enhancing the cumulative benefits in these areas. Precise measurement of phenotypic data is [...] Read more.

As one of the world’s most crucial food crops, maize plays a pivotal role in ensuring food security and driving economic growth. The diversification of maize variety breeding is significantly enhancing the cumulative benefits in these areas. Precise measurement of phenotypic data is pivotal for the selection and breeding of maize varieties in cultivation and production. However, in outdoor environments, conventional phenotyping methods, including point cloud processing techniques based on region growing algorithms and clustering segmentation, encounter significant challenges due to the low density and frequent loss of point cloud data. These issues substantially compromise measurement accuracy and computational efficiency. Consequently, this paper introduces a Constrained Region Point Cloud Phenotyping (CRPCP) algorithm that proficiently detects the phenotypic traits of multiple maize plants in sparse outdoor point cloud data. The CRPCP algorithm consists primarily of three core components: (1) a constrained region growth algorithm for effective segmentation of maize stem point clouds in complex backgrounds; (2) a radial basis interpolation technique to bridge gaps in point cloud data caused by environmental factors; and (3) a multi-level parallel decomposition strategy leveraging scene blocking and plant instances to enable high-throughput real-time computation. The results demonstrate that the CRPCP algorithm achieves a segmentation accuracy of 96.2%. When assessing maize plant height, the algorithm demonstrated a strong correlation with manual measurements, evidenced by a coefficient of determination R² of 0.9534, a root mean square error (RMSE) of 0.4835 cm, and a mean absolute error (MAE) of 0.383 cm. In evaluating the diameter at breast height (DBH) of the plants, the algorithm yielded an R² of 0.9407, an RMSE of 0.0368 cm, and an MAE of 0.031 cm. Compared to the PointNet point cloud segmentation method, the CRPCP algorithm reduced segmentation time by more than 44.7%. The CRPCP algorithm proposed in this paper enables efficient segmentation and precise phenotypic measurement of low-density maize multi-plant point cloud data in outdoor environments. This algorithm offers an automated, high-precision, and highly efficient solution for large-scale field phenotypic analysis, with broad applicability in precision breeding, agronomic management, and yield prediction. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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18 pages, 3943 KiB

Open AccessArticle

Comparison of Single-Trait and Multi-Trait GBLUP Models for Genomic Prediction in Red Clover

by Johanna Osterman, Lucia Gutiérrez, Linda Öhlund, Rodomiro Ortiz, Cecilia Hammenhag, David Parsons and Mulatu Geleta

Agronomy 2024, 14(10), 2445; https://doi.org/10.3390/agronomy14102445 - 21 Oct 2024

Viewed by 1400

Abstract

Red clover (Trifolium pratense) is a perennial forage legume wildly used in temperate regions, including northern Europe. Its breeders are under increasing pressure to obtain rapid genetic gains to meet the high demand for improved forage yield and quality. One solution [...] Read more.

Red clover (Trifolium pratense) is a perennial forage legume wildly used in temperate regions, including northern Europe. Its breeders are under increasing pressure to obtain rapid genetic gains to meet the high demand for improved forage yield and quality. One solution to increase genetic gain by reducing time and increasing accuracy is genomic selection. Thus, efficient genomic prediction (GP) models need to be developed, which are unbiased to traits and harvest time points. This study aimed to develop and evaluate single-trait (ST) and multi-trait (MT) models that simultaneously target more than one trait or cut. The target traits were dry matter yield, crude protein content, net energy for lactation, and neutral detergent fiber. The MT models either combined dry matter yield with one forage quality trait, all traits at one cut, or one trait across all cuts. The results show an increase with MT models where the traits had a genetic correlation of 0.5 or above. This study indicates that non-additive genetic effects have significant but varying effects on the predictive ability and reliability of the models. The key conclusion of this study was that these non-additive genetic effects could be better described by incorporating genetically correlated traits or cuts. Full article

(This article belongs to the Special Issue Multi-omic Integration for Applied Prediction Breeding)

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12 pages, 3652 KiB

Open AccessArticle

Effects of the Radicle Sheath on the Rhizosphere Microbial Community Structure of Seedlings in Early Spring Desert Species Leontice incerta

by Xiaolan Xue and Jannathan Mamut

Agronomy 2024, 14(10), 2444; https://doi.org/10.3390/agronomy14102444 - 21 Oct 2024

Viewed by 483

Abstract

Most research on plant–microbe interactions emphasize the effects of micronutrients on the rhizosphere microbial community structure. However, the influence of seed structures, particularly the radicle sheath, on microbial diversity at the seedling root tips under varying temperatures and humidity has been less explored. [...] Read more.

Most research on plant–microbe interactions emphasize the effects of micronutrients on the rhizosphere microbial community structure. However, the influence of seed structures, particularly the radicle sheath, on microbial diversity at the seedling root tips under varying temperatures and humidity has been less explored. This study conducted controlled indoor experiments in the northern desert of Xinjiang to assess the radicle sheath’s impact on microbial community composition, diversity, and function. The results indicated no significant changes in the Chao1 index for bacteria and fungi, but notable differences were observed in the Shannon and Simpson indices (p < 0.05). Under drought conditions, the radicle sheath significantly reduced bacterial infections without affecting fungi. Genus-level analysis showed an increased abundance of specific dominant bacterial groups when the radicle sheath was retained. NMDS analysis confirmed its significant effect on both bacterial and fungal community structures. LEfSe analysis identified 34 bacterial and 15 fungal biomarkers, highlighting the treatment’s impacts on microbial taxonomic composition. Functional predictions using PICRUSt 2 revealed that the radicle sheath facilitated the conversion of CH₄ to CH₃OH and various nitrogen cycle processes under drought. Overall, the radicle sheath plays a crucial role in maintaining rhizosphere microbial community stability and enhancing the functions of both bacteria and fungi under drought conditions. Full article

(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)

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15 pages, 614 KiB

Open AccessArticle

Agronomic Performance and Resistance to Maize Lethal Necrosis in Maize Hybrids Derived from Doubled Haploid Lines

by Kassahun Sadessa, Yoseph Beyene, Beatrice E. Ifie, Manje Gowda, Lingadahalli M. Suresh, Michael S. Olsen, Pangirayi Tongoona, Samuel K. Offei, Eric Danquah, Boddupalli M. Prasanna and Dagne Wegary

Agronomy 2024, 14(10), 2443; https://doi.org/10.3390/agronomy14102443 - 21 Oct 2024

Viewed by 704

Abstract

Maize (Zea mays L.) is one of the most widely cultivated grain crops globally. In sub-Saharan Africa (SSA), it plays an important role in ensuring both food and income security for smallholder farmers. This study was conducted to (i) assess the performances [...] Read more.

Maize (Zea mays L.) is one of the most widely cultivated grain crops globally. In sub-Saharan Africa (SSA), it plays an important role in ensuring both food and income security for smallholder farmers. This study was conducted to (i) assess the performances of testcross hybrids constituted from maize lethal necrosis (MLN) tolerant doubled haploid (DH) lines under various management conditions; (ii) estimate the combining ability effects and determine the nature of gene action in the DH lines; and (iii) identify DH lines and testcross hybrids for resistance to MLN, high grain yield, and other important traits. Eleven DH lines were crossed with 11 single-cross testers using the line-by-tester mating design, and 115 successful testcross hybrids were generated. These hybrids, along with five commercial check hybrids, were evaluated across four optimum management conditions, two MLN artificial inoculations, and one managed drought environment in Kenya. Under each management condition, the effects of genotypes, environments, and genotype-by-environment interactions were significant for grain yield (GY) and most other traits. Hybrids T1/L3, T10/L3, and T11/L3 exhibited higher grain yields under at least two management conditions. A combining ability analysis revealed that additive gene effects were more important than non-additive effects for GY and most other traits, except for leaf senescence (SEN) and MLN disease severity score. DH line L3 exhibited a desirable general combining ability (GCA) effect for GY, while L5 was the best general combiner for anthesis date (AD) and plant height (PH) across all management conditions. DH lines L2, L6, and L7 showed negative GCA effects for MLN disease severity. Single-cross testers T11 and T10 were good general combiners for GY under all management conditions. Hybrids T2/L11, T9/L10, and T2/L10 demonstrated high specific combining ability (SCA) effects for GY under all conditions. This study identified DH lines and testers with favorable GCA effects for grain yield, MLN resistance, and other agronomic traits that can be used in breeding programs to develop high-yielding and MLN-resistant maize varieties. Better-performing testcross hybrids identified in the current study could be verified through on-farm testing and released for commercial production to replace MLN-susceptible, low-yield hybrids grown in the target ecologies. Full article

(This article belongs to the Section Crop Breeding and Genetics)

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24 pages, 3842 KiB

Open AccessReview

Unravelling the Current Status of Rice Stripe Mosaic Virus: Its Geographical Spread, Biology, Epidemiology, and Management

by Md. Atik Mas-ud, Md. Rayhan Chowdhury, Sadiya Arefin Juthee, Muhammad Fazle Rabbee, Mohammad Nurul Matin and Sang Gu Kang

Agronomy 2024, 14(10), 2442; https://doi.org/10.3390/agronomy14102442 - 21 Oct 2024

Viewed by 1047

Abstract

Rice stripe mosaic virus (RSMV) belongs to the Cytorhabdovirus species in the Rhabdoviridae family. Recently, RSMV was widely spread in East Asia and caused severe yield losses. RSMV is transmitted by the planthopper vectors, Recilia dorsalis, Nephotettix virescens, and Nilaparvata lugens [...] Read more.

Rice stripe mosaic virus (RSMV) belongs to the Cytorhabdovirus species in the Rhabdoviridae family. Recently, RSMV was widely spread in East Asia and caused severe yield losses. RSMV is transmitted by the planthopper vectors, Recilia dorsalis, Nephotettix virescens, and Nilaparvata lugens, that mostly affect rice. The adult vectors can hibernate, transmit the virus, lay eggs on rice plants, and, finally, multiply in subsequent generations, resulting in new infection outbreaks. RSMV-infected rice varieties display striped mosaicism, mild dwarfism, stiff and twisted leaves, delayed heading, short panicles with large unfilled grains, and yield reduction. In nature, the infection of multiple pathogens in the same host is widespread, which is defined as co-infection. It can be antagonistic or synergistic. Pathological synergistic effects between RSMV and other viruses can generate strains with new genetic characteristics, leading to unpredictable epidemiological consequences. After the first identification of RSMV in 2015, significant advancements in understanding the disease’s characteristics, symptoms, cycles, geographic distribution, potential vectors, and synergistic interaction, as well as its management strategies, were developed. To reduce the damage due to RSMV infection, many scientists have recommended pest control techniques to target adult vectors. It is also essential to confirm the actual time of monitoring, development of resistant varieties, and changes in cultivation systems. Due to the limitations of the conventional plant disease control technologies, improvements in efficiency and safety are in high demand. Therefore, to find efficient and environmentally safe controls to mitigate these challenges, reviews of research are the foremost step. In this review, we summarize the basic epidemiological information about the origin of RSMV and its infection symptoms in the field, synergistic interaction with viruses during co-transmission, yield losses, formulation of the disease cycle, and control strategies from several case studies. Finally, we recommend the formulation of the disease cycle and management strategies of RSMV infection. Full article

(This article belongs to the Special Issue Decoding Plant–Pathogen Interactions: Unraveling Signaling and Defense Mechanisms)

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18 pages, 4062 KiB

Open AccessArticle

Altitude Distribution Patterns and Driving Factors of Rhizosphere Soil Microbial Diversity in the Mountainous and Hilly Region of Southwest, China

by Yanlin Li, Yonggang Wang, Yunpeng Liu, Yangyang Chen and Shuangrong Yang

Agronomy 2024, 14(10), 2441; https://doi.org/10.3390/agronomy14102441 - 21 Oct 2024

Viewed by 510

Abstract

The distribution characteristics of the microbial community in rhizosphere soils of different altitudinal gradients were explored to uncover ecological factors affecting microbial community composition. In this study, the community variations of bacteria and fungi in the rhizosphere soil of Chrysanthemum indicum L. were [...] Read more.

The distribution characteristics of the microbial community in rhizosphere soils of different altitudinal gradients were explored to uncover ecological factors affecting microbial community composition. In this study, the community variations of bacteria and fungi in the rhizosphere soil of Chrysanthemum indicum L. were analyzed. Samples were distributed along an altitudinal gradient of 300–1500 m above sea level in the Fuling watershed of the Three Gorges Reservoir area, China. The analysis was conducted using Illumina MiSeq high-throughput sequencing and bioinformatics analyses. Through correlation analysis with ecological factors, the altitude distribution pattern and driving factors of soil microbial diversity in the mountainous and hilly region of Chongqing were explored. According to the results, the richness and diversity of rhizosphere soil bacteria increased with altitude, while fungi were the richest and most diverse at an altitude of 900 m. The composition of the microbial community differed among different altitudes. Actinobacteria, Proteobacteria, Acidobacteriota, Chloroflexi, Bacteroidota, Ascomycota, unclassified_k_Fungi, Basidiomycota, and Mortierellomycota dominated the microbial community in rhizosphere soil. Correlation analysis showed that the distribution of rhizosphere soil microbial communities correlated with soil ecological factors at different altitudes. Moisture, pH, total nitrogen, total potassium, available potassium, urease, and catalase were significantly positively correlated with rhizosphere soil bacterial α-diversity, while their correlations with fungi were not significant. Variation partition analysis showed that the combined effects of soil physical and chemical factors, enzyme activity, and microbial quantity regulated bacterial community structure and composition. Their combined contributions (19.21%) were lower than the individual effects of soil physical and chemical factors (48.49%), enzyme activity (53.24%), and microbial quantity (60.38%). The effects of ecological factors on fungal communities differed: While the soil physical and chemical factors (44.43%) alone had a clear effect on fungal community structures, their combined contributions had no apparent effect. The results of this study not only contribute to a deeper understanding of the impact mechanism of altitude gradient on the diversity of rhizosphere soil microbial communities, but also provide a scientific basis for the protection and management of mountainous and hilly ecosystems. It lays a foundation for the future exploration of the relationship between microbial communities and plant–soil interactions. Full article

(This article belongs to the Special Issue Nutrient Cycling and Microorganisms in Agroecosystems)

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12 pages, 4096 KiB

Open AccessArticle

Quantifying Stream Return Flow of Agricultural Water Using SWAT-MODFLOW-PADDY Model in Korean Paddy Fields

by Jeongho Han, Seoro Lee and Jonggun Kim

Agronomy 2024, 14(10), 2440; https://doi.org/10.3390/agronomy14102440 - 21 Oct 2024

Viewed by 643

Abstract

In many countries, the irrigation return flow focuses only on surface and subsurface flows. In contrast, South Korea adopts a broader approach, defining the stream return flow as encompassing both quick and delayed return flows, which include subsurface flow and deep percolation. This [...] Read more.

In many countries, the irrigation return flow focuses only on surface and subsurface flows. In contrast, South Korea adopts a broader approach, defining the stream return flow as encompassing both quick and delayed return flows, which include subsurface flow and deep percolation. This study proposes redefining the stream return flow to include only the subsurface return flow, excluding deep percolation. We quantified the subsurface return flow and deep percolation using the SWAT-MODFLOW-PADDY (SMP) model, confirming that the current definition overestimated the stream return flow in Korea. The results show that the subsurface return flow accounted for 20% to 60% of the total infiltration, with the remaining 40% to 80% contributing to deep percolation and groundwater recharge. These findings reveal significant regional variations in the subsurface return flow rates, underscoring the limitations of applying a uniform stream return flow rate. We propose that allocated management water, subsurface, and quick return flows should be the primary components considered in stream return flow calculations, as the current practice of including delayed return flow leads to overestimated results. This study highlights the challenges in monitoring the subsurface return flow and the need for region-specific models that account for local conditions such as topography, soil characteristics, and climate. Our findings provide a more accurate approach to estimating the subsurface return flow, which is crucial for improving the efficiency and sustainability of agricultural water management in Korea. Full article

(This article belongs to the Special Issue Water Saving in Irrigated Agriculture: Series II)

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17 pages, 6452 KiB

Open AccessArticle

Optimal Water and Nitrogen Regimes Increased Fruit Yield and Water Use Efficiency by Improving Root Characteristics of Drip-Fertigated Greenhouse Tomato (Solanum lycopersicum L.)

by Hanlong Feng, Zhiyao Dou, Wenhui Jiang, Hemat Mahmood, Zhenqi Liao, Zhijun Li and Junliang Fan

Agronomy 2024, 14(10), 2439; https://doi.org/10.3390/agronomy14102439 - 21 Oct 2024

Viewed by 1076

Abstract

The growth of root system directly affects the absorption and utilization of soil water and nitrogen, and understanding the responses of root characteristics to water and nitrogen regimes is thus crucial for optimizing water and nitrogen management. The root characteristics of each soil [...] Read more.

The growth of root system directly affects the absorption and utilization of soil water and nitrogen, and understanding the responses of root characteristics to water and nitrogen regimes is thus crucial for optimizing water and nitrogen management. The root characteristics of each soil layer, i.e., root length, root surface area, and root volume, as well as fruit yield and water use efficiency of greenhouse tomato under drip fertigation in response to different irrigation levels and nitrogen rates were explored in northwest China. There were four irrigation levels, i.e., 50% ET_C (W1), 75% ET_C (W2), 100% ET_C (W3), and 125% ET_C (W4), where ET_C is the crop evapotranspiration, and four nitrogen rates, i.e., 0 kg ha⁻¹ (N1), 150 kg ha⁻¹ (N2), 250 kg ha⁻¹ (N3), and 350 kg ha⁻¹ (N4). The results showed that reasonable irrigation and nitrogen regimes (W3N3) significantly increased fruit yield by 31.64% and root length, root surface area, and root volume by 45.03%, 61.24%, and 148.21% compare to W3N1, respectively. The promoting effect of increasing irrigation level on root characteristics increased with soil depth and had the greatest increases in root volume by 27.07%, 123.43%, and 211.47% for the 0–10, 10–20, and 20–30 cm soil layers, respectively. In addition, reducing irrigation level significantly increased the percentages of roots in the top soil by 29.71%, 26.77%, and 18.53% for root length, root surface area, and root volume, respectively. The reasonable nitrogen rate (N3) significantly increased fruit yield by 41.11%, water use efficiency by 34.42%, and root length, root surface area, and root volume by 40.42%, 41.44%, and 112.76%, respectively. The over-application of nitrogen (N4) reduced root characteristics of all soil layers, fruit yield, and water use efficiency. The promoting effect of increasing nitrogen rate on root length of each soil layer decreased with soil depth, by 71.01%, 48.96%, and 15.71% for 0–10, 10–20, and 20–30 cm soil layers, respectively. Irrigation level was the main factor dominating the root growth of each soil layer. The correlation analysis showed that fruit yield had significantly positive correlations with root characteristics in all soil layers, while water use efficiency had significantly positive correlations with the percentages of root length and root surface area in the 0–10 cm soil layer. In conclusion, rational water and nitrogen regimes achieved better fruit yield by promoting root growth of greenhouse tomato, and the water use efficiency of greenhouse tomato was improved by increasing the root percentage in the topsoil layer to alleviate the adverse effects under water stress conditions. This study reveals how irrigation volume and nitrogen application can enhance tomato yield and water use efficiency by regulating root characteristics and vertical root distribution, providing support for understanding the response of root systems to changes in soil water and nitrogen conditions. Full article

(This article belongs to the Special Issue Optimal Water Management and Sustainability in Irrigated Agriculture—2nd Edition)

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19 pages, 1665 KiB

Open AccessArticle

Analysis of the Physiological Parameters of Cold Resistance in Core Winter and Spring Wheat Cultivars

by Yunhe Wang, Cunyao Bo, Xiaohua Wang, Xincheng Yang and Hongwei Wang

Agronomy 2024, 14(10), 2438; https://doi.org/10.3390/agronomy14102438 - 21 Oct 2024

Viewed by 543

Abstract

We selected 46 core winter–spring wheat cultivars from China’s main wheat-producing areas as experimental materials to clarify the differences in the physiological parameters of their cold resistance and provide a theoretical basis and high-quality germplasm for cold resistance breeding. We investigated differences in [...] Read more.

We selected 46 core winter–spring wheat cultivars from China’s main wheat-producing areas as experimental materials to clarify the differences in the physiological parameters of their cold resistance and provide a theoretical basis and high-quality germplasm for cold resistance breeding. We investigated differences in their cold resistance under field conditions for two consecutive years, and determined the physiological parameters of the cold resistance, yield, and quality indicators of different winter–spring wheat cultivars. Our results showed that the cold resistance of winter wheat cultivars was higher than that of spring wheat cultivars. The chlorophyll (Chl), soluble sugar (SS), soluble protein (SP), and free proline (Pro) contents of different winter–spring wheat cultivars were positively correlated with cold resistance, and malondialdehyde (MDA) content was negatively correlated with cold resistance. The five physiological parameters can be used as physiological indicators for the breeding of cold-resistant cultivars. The cold resistance, yield, and quality indicators of different spring and winter wheat cultivars were comprehensively evaluated by using the average membership value and comprehensive score. It was found that the average membership value and comprehensive score of winter wheat cultivars were higher than those of spring wheat cultivars. Through classification using the K-means method, the cold-resistant, high-yield, and high-quality cultivars were screened out, namely, Jimai23 (JM23), Jimai44 (JM44), Shannong57 (SN57), and Jinmai 919 (JM919). Full article

(This article belongs to the Special Issue Genetic Identification and Characterisation of Crop Agronomic Traits and Stress Resistance—2nd Edition)

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14 pages, 635 KiB

Open AccessReview

The Use of Anaerobic Digestate for Greenhouse Horticulture

by Julė Jankauskienė, Kristina Laužikė and Samanta Kaupaitė

Agronomy 2024, 14(10), 2437; https://doi.org/10.3390/agronomy14102437 - 21 Oct 2024

Viewed by 790

Abstract

Agricultural crop production practices are being developed for organic, sustainable, and environmentally friendly farming systems. Developing efficient and resourceful crop fertilizers is significantly important for future agriculture. Various biofertilizers, such as animal manures, composts, and vegetable byproducts, have been successfully applied in agriculture. [...] Read more.

Agricultural crop production practices are being developed for organic, sustainable, and environmentally friendly farming systems. Developing efficient and resourceful crop fertilizers is significantly important for future agriculture. Various biofertilizers, such as animal manures, composts, and vegetable byproducts, have been successfully applied in agriculture. Anaerobic digestate, organic matter obtained from animal or plant waste processing during anaerobic digestion into biomass, has become popular due to its versatility, multiple purposes, and facile application methods. Digestate has recently been widely used in agriculture to enrich the soil with nutrients and thus increase crop yields. Several studies have shown that anaerobic digestate is a valuable fertilizer that can be used as a biofertilizer in field and greenhouse horticulture. Also, research has been carried out on the use of digestate in hydroponic horticulture. This review presents the research results and discusses the possibilities of using anaerobic digestate in greenhouse horticulture. Its objective is to provide a comprehensive understanding of the application of digestate from various sources and its impact on the growth, progress, yield, and quality of greenhouse-grown vegetables. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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11 pages, 4980 KiB

Open AccessArticle

Study on Spatiotemporal Characteristics and Influencing Factors of High-Resolution Single-Season Rice

by Yang Han, Peng Zhou, Youyue Wen, Jian Yang, Qingzhou Lv, Jian Wang and Yanan Zhou

Agronomy 2024, 14(10), 2436; https://doi.org/10.3390/agronomy14102436 - 21 Oct 2024

Viewed by 589

Abstract

Single-season rice describes the area under rice cultivation from May–October of the year. Many scholars have used lower-resolution data to study single-season rice in different regions, but using high-precision and high-resolution single-season rice data can reveal new phenomena. This paper uses a long-time-series, [...] Read more.

Single-season rice describes the area under rice cultivation from May–October of the year. Many scholars have used lower-resolution data to study single-season rice in different regions, but using high-precision and high-resolution single-season rice data can reveal new phenomena. This paper uses a long-time-series, high-precision, and high-resolution single-season rice cultivation dataset to conduct an in-depth analysis of the spatial–temporal variability characteristics of single-season rice in Jiangsu Province, China, from 2017 to 2021. It explores the correlation between meteorological factors and greenhouse gasses for single-season rice. It analyzes the driving role of social factors on single-season rice. The results showed that single-season rice was mainly grown in the central and northeastern regions of the study area. The single-season rice cultivation was significantly reduced in 2020 due to the impact of COVID-19. Single-season rice strongly correlates with meteorological factors in time but shows a weak spatial correlation. This is because human factors largely dominate the area under single-season rice cultivation. Methane emissions in the study area are mainly influenced by anthropogenic activities rather than single-season rice. Social factors are essential in controlling single-season rice cultivation in the study area. This study was conducted in Jiangsu Province, China. Still, the methodology and results have important implications for agricultural production and environmental management studies in other regions, and some findings have general applicability. Full article

(This article belongs to the Special Issue Intelligent Remote Sensing in Smart Agriculture: From Early Identification to Yield Prediction—A Comprehensive Solution)

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23 pages, 3700 KiB

Open AccessArticle

Nutrient Mass in Winter Wheat in the Cereal Critical Window Under Different Nitrogen Levels—Effect on Grain Yield and Grain Protein Content

by Witold Grzebisz and Maria Biber

Agronomy 2024, 14(10), 2435; https://doi.org/10.3390/agronomy14102435 - 20 Oct 2024

Viewed by 1043

Abstract

The mass of nutrients accumulated in the vegetative parts of winter wheat (WW) in the period from the beginning of booting to the full flowering stage (Critical Cereal Window, CCW) allows for the reliable prediction of the grain yield (GY) and its components, [...] Read more.

The mass of nutrients accumulated in the vegetative parts of winter wheat (WW) in the period from the beginning of booting to the full flowering stage (Critical Cereal Window, CCW) allows for the reliable prediction of the grain yield (GY) and its components, and the grain protein content (GPC) and its yield. This hypothesis was verified in a one-factor field experiment carried out in the 2013/2014, 2014/2015, and 2015/2016 growing seasons. The field experiment included seven nitrogen-fertilized variants: 0, 40, 80, 120, 160, 200, and 240 kg N ha⁻¹. The N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu content in wheat vegetative parts (leaves, stems) was determined in two growth stages: (i) beginning of booting (BBCH 40) and (ii) full flowering (BBCH 65). We examined the response of eight WW traits (ear biomass at BBCH 65, EAB; grain yield, GY; grain protein content, GPC; grain protein yield, GPY; canopy ear density, CED; number of grains per ear, GE; number of grains per m⁻²—canopy grain density, CGD; and thousand grain weight, TGW) to the amount of a given nutrient accumulated in the given vegetative part of WW before flowering. The average GY was very high and ranged from 7.2 t ha⁻¹ in 2016 to 11.3 t ha⁻¹ in 2015. The mass of ears in the full flowering stage was highest in 2016, a year with the lowest GY. The highest N mass in leaves was also recorded in 2016. Only the biomass of the stems at the BBCH 65 stage was the highest in 2015, the year with the highest yield. Despite this variability, 99% of GY variability was explained by the interaction of CGD and TGW. Based on the analyses performed, it can be concluded that in the case of large yields of winter wheat, GE is a critical yield component that determines the CGD, and in consequence the GY. The leaf nutrient mass at the BBCH 40 stage was a reliable predictor of the GPC (R² = 0.93), GPY (0.92), GE (0.84), and CED (0.76). The prediction of the GY (0.89), CGD (0.90), and TGW (0.89) was most reliable based on the leaf nutrient mass at the BBCH 65 stage. The best EAB prediction was obtained based on the mass of nutrients in WW stems at the BBCH 65 stage. The magnesium accumulated in WW parts turned out to be, with the exception of TGW, a key predictor of the examined traits. In the case of the TGW, the main predictor was Ca. The effect of Mg on the tested WW traits most often occurred in cooperation with other nutrients. Its presence in the developed stepwise regression models varied depending on the plant part and the WW trait. The most common nutrients accompanying Mg were micronutrients, while Zn, Fe, Mn, and Ca were the most common macronutrients accompanying Mg. Despite the apparently small impact of N, its yield-forming role was indirect. Excessive N accumulation in leaves in relation to its mass in stems, which appeared in the full flowering phase, positively impacted the EAB and GPC, but negatively affected the GE. Increasing the LE/ST ratio for both Mg and Ca resulted in a better formation of the yield components, which, consequently, led to a higher yield. This study clearly showed that nutritional control of WW during the CCW should focus on nutrients controlling N action. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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21 pages, 10967 KiB

Open AccessArticle

Estimation of the Weight and Volume of Lime (Citrus aurantifolia (Christm.) Swingle) Fruit Using Computer Vision Based on Traditional Machine Learning and Deep Learning

by Jiraporn Onmankhong, Pasu Poonpakdee and Ravipat Lapcharoensuk

Agronomy 2024, 14(10), 2434; https://doi.org/10.3390/agronomy14102434 - 20 Oct 2024

Viewed by 878

Abstract

The post-harvest process is important to increasing the market value of limes and requires focus. During this process, limes are graded and categorized based on size, weight, and volume. Therefore, identifying efficient means of estimating these properties is very important and remains an [...] Read more.

The post-harvest process is important to increasing the market value of limes and requires focus. During this process, limes are graded and categorized based on size, weight, and volume. Therefore, identifying efficient means of estimating these properties is very important and remains an open research area. This study applies the concept of computer vision based on traditional machine learning algorithms (partial least square regression (PLS), epsilon-support vector regression (ε-SVR), decision tree (DT), random forest (RF), adaptive boosting (AB), gradient boosting (GB), Bagging meta-estimator (BME), and extremely randomized trees (ERTs)) and pre-trained deep learning (InceptionV3, MoblieNetV2, ResNet50, and VGG-16) for estimating the weight and volume of limes. Our findings showed that the BME and ResNet50 could yield the highest performance for estimating the weight and volume of limes. The BME produced

R_{test}^{2}

values of 0.954 and 0.882 for weight and volume, respectively, while the

R_{test}^{2}

values of ResNet50 models were between 0.951 and 0.957 for weight and volume, respectively. This study concluded that computer vision based on both traditional machine learning and deep learning could be used to estimate the weight and volume of limes. The approach proposed in this study can be adopted for applications related to computer vision in the post-harvest process. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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20 pages, 6388 KiB

Open AccessArticle

Extraction of Winter Wheat Planting Plots with Complex Structures from Multispectral Remote Sensing Images Based on the Modified Segformer Model

by Chunshan Wang, Shuo Yang, Penglei Zhu and Lijie Zhang

Agronomy 2024, 14(10), 2433; https://doi.org/10.3390/agronomy14102433 - 20 Oct 2024

Viewed by 614

Abstract

As one of the major global food crops, the monitoring and management of the winter wheat planting area is of great significance for agricultural production and food security worldwide. Today, the development of high-resolution remote sensing imaging technology has provided rich sources of [...] Read more.

As one of the major global food crops, the monitoring and management of the winter wheat planting area is of great significance for agricultural production and food security worldwide. Today, the development of high-resolution remote sensing imaging technology has provided rich sources of data for extracting the visual planting information of winter wheat. However, the existing research mostly focuses on extracting the planting plots that have a simple terrain structure. In the face of diverse terrain features combining mountainous areas, plains, and saline alkali land, as well as small-scale but complex planting structures, the extraction of planting plots through remote sensing imaging is subjected to great challenges in terms of recognition accuracy and model complexity. In this paper, we propose a modified Segformer model for extracting winter wheat planting plots with complex structures in rural areas based on the 0.8 m high-resolution multispectral data obtained from the Gaofen-2 satellite, which significantly improves the extraction accuracy and efficiency under complex conditions. In the encoder and decoder of this method, new modules were developed for the purpose of optimizing the feature extraction and fusion process. Specifically, the improvement measures of the proposed method include: (1) The MixFFN module in the original Segformer model is replaced with the Multi-Scale Feature Fusion Fully-connected Network (MSF-FFN) module, which enhances the model’s representation ability in handling complex terrain features through multi-scale feature extraction and position embedding convolution; furthermore, the DropPath mechanism is introduced to reduce the possibility of overfitting while improving the model’s generalization ability. (2) In the decoder part, after fusing features at four different scales, a CoordAttention module is added, which can precisely locate important regions with enhanced features in the images by utilizing the coordinate attention mechanism, therefore further improving the model’s extraction accuracy. (3) The model’s input data are strengthened by incorporating multispectral indices, which are also conducive to the improvement of the overall extraction accuracy. The experimental results show that the accuracy rate of the modified Segformer model in extracting winter wheat planting plots is significantly increased compared to traditional segmentation models, with the mean Intersection over Union (mIOU) and mean Pixel Accuracy (mPA) reaching 89.88% and 94.67%, respectively (an increase of 1.93 and 1.23 percentage points, respectively, compared to the baseline model). Meanwhile, the parameter count and computational complexity are significantly reduced compared to other similar models. Furthermore, when multispectral indices are input into the model, the mIOU and mPA reach 90.97% and 95.16%, respectively (an increase of 3.02 and 1.72 percentage points, respectively, compared to the baseline model). Full article

(This article belongs to the Section Precision and Digital Agriculture)

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9 pages, 1128 KiB

Open AccessArticle

Understanding the Feeding Behavior and Identifying the Plant Parts Preferences of Fall Armyworm on Peanut Seedlings

by Yuanyuan Cheng, Lulu Liu, Hongmei Li, Xianming Yang and Suqin Shang

Agronomy 2024, 14(10), 2432; https://doi.org/10.3390/agronomy14102432 - 20 Oct 2024

Viewed by 560

Abstract

Fall armyworm (FAW), Spodoptera frugiperda, has posed a serious threat to global food security since its discovery in Africa in 2016. Intercropping peanuts with maize is a very common cultivation practice, which can result in a high possibility of peanut damage by [...] Read more.

Fall armyworm (FAW), Spodoptera frugiperda, has posed a serious threat to global food security since its discovery in Africa in 2016. Intercropping peanuts with maize is a very common cultivation practice, which can result in a high possibility of peanut damage by FAW. Our study investigated the feeding behavior, plant part preferences, and damage symptoms of FAW larvae on peanuts throughout the larval period, considering changes in population densities and the passage of time over the number of investigations. The results indicated that FAW larvae frequently inhabited peanut leaves, particularly the undersides of the leaves. Larvae moved from the leaves to the soil in the seedling pot to complete development. Furthermore, FAW larvae tended to feed on peanut leaves rather than stems regardless of population densities. Based on the damage symptoms, the feeding preferences of FAW larvae tended to be heart leaves, followed by mature leaves and stems. The most frequent damage symptoms caused by FAW to peanuts were “window panes”, followed by “leafless”. This study provides a reference for the integrated management of FAW in peanut fields. Full article

(This article belongs to the Section Pest and Disease Management)

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21 pages, 2928 KiB

Open AccessArticle

Assessment of the Effects of Biochar on the Physicochemical Properties of Saline–Alkali Soil Based on Meta-Analysis

by Tingting Mao, Yaofeng Wang, Songrui Ning, Jiefei Mao, Jiandong Sheng and Pingan Jiang

Agronomy 2024, 14(10), 2431; https://doi.org/10.3390/agronomy14102431 - 20 Oct 2024

Viewed by 855

Abstract

Enhancing global agricultural sustainability critically requires improving the physicochemical properties of saline–alkali soil. Biochar has gained increasing attention as a strategy due to its unique properties. However, its effect on the physicochemical properties of saline–alkali soil varies significantly. This study uses psychometric meta-analysis [...] Read more.

Enhancing global agricultural sustainability critically requires improving the physicochemical properties of saline–alkali soil. Biochar has gained increasing attention as a strategy due to its unique properties. However, its effect on the physicochemical properties of saline–alkali soil varies significantly. This study uses psychometric meta-analysis across 137 studies to synthesize the findings from 1447 relatively independent data sets. This study investigates the effects of biochar with different characteristics on the top 20 cm of various saline–alkali soils. In addition, aggregated boosted tree (ABT) analysis was used to identify the key factors of biochar influencing the physicochemical properties of saline soils. The results showed that biochar application has a positive effect on improving soil properties by reducing the sodium adsorption ratio (SAR) and the exchangeable sodium percentage (ESP) by 30.31% and 28.88%, respectively, with a notable 48.97% enhancement in cation exchange capacity (CEC). A significant inverse relationship was found between soil salinity (SC) and ESP, while other factors were synergistic. Biochar application to mildly saline soil (<0.2%) and moderately saline soil (0.2–0.4%) demonstrated greater improvement in soil bulk density (SBD), total porosity (TP), and soil moisture content (SMC) compared to highly saline soil (>0.4%). However, the reduction in SC in highly saline soil was 4.9 times greater than in moderately saline soils. The enhancement of soil physical properties positively correlated with higher biochar application rates, largely driven by soil movements associated with the migration of soil moisture. Biochar produced at 401–500 °C was generally the most effective in improving the physicochemical properties of various saline–alkali soils. In water surplus regions, for mildly saline soil with pH < 8.5, mixed biochar (pH 6–8) at 41–80 t ha⁻¹ was the most effective in soil improvement. Moreover, in water deficit areas with soil at pH ≥ 8.5, biochar with pH ≤ 6 applied at rates of >80 t ha⁻¹ showed the greatest benefits. Agricultural residue biochar showed superior efficiency in ameliorating highly alkaline (pH ≥ 8.5) soil. In contrast, the use of mixed types of biochar was the most effective in the amelioration of other soil types. Full article

(This article belongs to the Section Water Use and Irrigation)

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33 pages, 3882 KiB

Open AccessArticle

Optimization of Potato Cultivation Through the Use of Biostimulator Supporter

by Piotr Barbaś, Barbara Sawicka, Piotr Pszczółkowski, Talal Seead Hameed and Alaa Kadhim Farhan

Agronomy 2024, 14(10), 2430; https://doi.org/10.3390/agronomy14102430 - 20 Oct 2024

Viewed by 815

Abstract

Seed potato treatment is vital for plant protection, yield enhancement, and product quality. In the conducted research, the plant biostimulator Supporter was applied to evaluate its impact on potato yields and its structure. Supporter contains both synthetic and SL amino acids, which promote [...] Read more.

Seed potato treatment is vital for plant protection, yield enhancement, and product quality. In the conducted research, the plant biostimulator Supporter was applied to evaluate its impact on potato yields and its structure. Supporter contains both synthetic and SL amino acids, which promote plant growth by enhancing nutrient utilization and fostering the development of a more effective root system. Such a formulation allows to maintain better resistance to environmental stresses, which may include drought or nutrient deficiency, among others. The field study was conducted in 2015–2017 in four towns located in different regions of Poland (Barankowo, Głubczyce, Kędrzyno, and Ryn) using a randomized complete block design with a split-plot design. Varieties (‘Innovator’, ‘Lilly’, ‘Lady Claire’, and ‘Verdi’) were tested. The experiment compared the cultivation technology using Supporter biostimulator with which seed potatoes were treated compared to conventional cultivation (control object) by soaking the tubers in distilled water before planting. The total yield of potato tubers after Supporter application was higher by 13.3%, while the commercial yield increased by 21.1% compared to the traditional cultivation method. The most productive, regardless of cultivation technology and years of research, in terms of total tuber yield was the ‘Lilly’ variety with an average yield of 47.95 t∙ha⁻¹, while the least productive variety was the ‘Innovator’ variety with an average yield of 29.93 t∙ha⁻¹. The ‘Lady Claire’ variety had the highest commercial tuber yield, while the ‘Innovator’ variety had the lowest. Full article

(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems—2nd Edition)

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21 pages, 1209 KiB

Open AccessArticle

Livestock Changes in Brazil and Sustainable Intensification Challenges

by Tiago Santos Telles, Anathan Bichel, Ediane Zanin, Tiago Pellini and Laíse da Silveira Pontes

Agronomy 2024, 14(10), 2429; https://doi.org/10.3390/agronomy14102429 - 20 Oct 2024

Viewed by 917

Abstract

The increasing global demand for animal products has impacted Brazilian cattle farming. This study aims to offer references for developing more sustainable livestock farming in Brazil. It analyzes the numbers of pasture areas, cattle herds, and stocking rates from 1970 to 2017, based [...] Read more.

The increasing global demand for animal products has impacted Brazilian cattle farming. This study aims to offer references for developing more sustainable livestock farming in Brazil. It analyzes the numbers of pasture areas, cattle herds, and stocking rates from 1970 to 2017, based on agricultural census data. Additionally, it compares pasture conditions using agricultural census data and satellite imagery for the years 2006 and 2017. The key findings include the following: (1) a 119.7% increase in cattle herds, with migration from the South and Southeast to the North and Central–West regions, which have lower land prices; (2) a 2.6% decrease in the pasture area for cattle (except in the North region); (3) a 3.8% decrease in areas in poor condition; and (4) a 125.5% increase in the stocking rate. Despite technological advancements improving productivity, most pastures (59.6%) are still underperforming, indicating potential for reducing the pressure on native vegetation. This study concludes that production areas are shifting between regions in Brazil, with livestock farming intensifying, marked by a decrease in pasture areas and degraded pastures, alongside an increase in cattle numbers and stocking rates. However, these changes are heterogeneous across the country. This analysis provides an overview of beef cattle nationwide, which is relevant for addressing production sustainability challenges. Full article

(This article belongs to the Section Grassland and Pasture Science)

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13 pages, 238 KiB

Open AccessArticle

Effect of Different Fertilization Strategies on Infestation of Brown Wheat Mite and Wheat Productivity

by Fatma Sh. Kalmosh, M. M. A. Ibrahim, Jiale Lv, Ibrahim A. Saleh, Jehad S. Al-Hawadie and Wahidah H. Al-Qahtani

Agronomy 2024, 14(10), 2428; https://doi.org/10.3390/agronomy14102428 - 19 Oct 2024

Viewed by 811

Abstract

The brown wheat mite, Petrobia tritici, poses a significant threat to wheat fields. While fertilizers can increase crop productivity, imbalanced application may exacerbate plant susceptibility to pests. This study aimed to evaluate the impact of various NPK fertilization programs on P. tritici [...] Read more.

The brown wheat mite, Petrobia tritici, poses a significant threat to wheat fields. While fertilizers can increase crop productivity, imbalanced application may exacerbate plant susceptibility to pests. This study aimed to evaluate the impact of various NPK fertilization programs on P. tritici infestations over two consecutive cropping seasons. The results revealed significant differences in mite infestation among the treatment groups (p < 0.001). The lowest populations (1.1 and 3.0 mites/leaf) were observed in the treatments sprayed with phosphoric acid (at 0.75 and 1.00 cm/L), where the infestation appeared approximately 120 days after sowing; in contrast, it appeared early at 75 days in the other treatments. Conversely, treatments lacking potassium fertilizer presented the greatest degree of mite injury levels (49.5–57.7 mites/leaf). Although these treatments provided moderate leaf nutrition and crop yield, the highest nutritional content and total yield (10.49 and 9.71 1 t/ha for the two years) were observed in the treatment that received 224:70:100 kg fad⁻¹ commercial fertilizers (=178:25:114 kg ha⁻¹ NPK units) as soil fertilization, which was followed by the treatment with a foliar application of phosphoric acid (1.00 cm/L) with a total yield of 9.34 and 8.53 1 t/ha for the two years. In this treatment, the P. tritici density was moderately high at 9.40 and 6.32 mites/leaf over the two years, respectively. The consistency of P. tritici density and total yield ranking across both years indicated reliable estimates of the impact of fertilization. This study suggests that potassium sulfate application is crucial for reducing P. tritici density and that foliar phosphoric acid application instead of soil application reduces the number of P. tritici and delays its occurrence. Full article

(This article belongs to the Special Issue Sustainable Agriculture: Plant Protection and Crop Production)

16 pages, 8100 KiB

Open AccessArticle

YOLOv8n-CSD: A Lightweight Detection Method for Nectarines in Complex Environments

by Guohai Zhang, Xiaohui Yang, Danyang Lv, Yuqian Zhao and Peng Liu

Agronomy 2024, 14(10), 2427; https://doi.org/10.3390/agronomy14102427 - 19 Oct 2024

Viewed by 657

Abstract

At present, the picking of nectarines mainly relies on manual completion in China, and the process involves high labor intensity during picking and low picking efficiency. Therefore, it is necessary to introduce automated picking. To improve the accuracy of nectarine fruit recognition in [...] Read more.

At present, the picking of nectarines mainly relies on manual completion in China, and the process involves high labor intensity during picking and low picking efficiency. Therefore, it is necessary to introduce automated picking. To improve the accuracy of nectarine fruit recognition in complex environments and to increase the efficiency of automatic orchard-picking robots, a lightweight nectarine detection method, YOLOv8n-CSD, is proposed in this study. This model improves on YOLOv8n by first proposing a new structure, C2f-PC, to replace the C2f structure used in the original network, thus reducing the number of model parameters. Second, the SEAM is introduced to improve the model’s recognition of the occluded part. Finally, to realize real-time detection of nectarine fruits, the DySample Lightweight Dynamic Upsampling Module is introduced to save computational resources while effectively enhancing the model’s anti-interference ability. With a compact size of 4.7 MB, this model achieves 95.1% precision, 84.9% recall, and a [email protected] of 93.2%—the model’s volume has been reduced while the evaluation metrics have all been improved over the baseline model. The study shows that the YOLOv8n-CSD model outperforms the current mainstream target detection models, and can recognize nectarines in different environments faster and more accurately, which lays the foundation for the field application of automatic picking technology. Full article

(This article belongs to the Special Issue Intelligent Information System for Agriculture Based on Vision Technology)

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14 pages, 1209 KiB

Open AccessArticle

Characterization and Greenhouse Trial of Zn Bio-Chelates Derived from Spent Coffee Grounds

by Ana Cervera-Mata, Leslie Lara-Ramos, José Ángel Rufián-Henares, Alejandro Fernández-Arteaga, Jesús Fernández-Bayo and Gabriel Delgado

Agronomy 2024, 14(10), 2426; https://doi.org/10.3390/agronomy14102426 - 19 Oct 2024

Viewed by 788

Abstract

The conversion of spent coffee grounds (SCG) into hydrochars has been the subject of extensive research in recent years, aimed at evaluating their potential for biofortifying foods and mitigating the plant toxicity linked to SCG. This study aimed to assess the physicochemical characterization [...] Read more.

The conversion of spent coffee grounds (SCG) into hydrochars has been the subject of extensive research in recent years, aimed at evaluating their potential for biofortifying foods and mitigating the plant toxicity linked to SCG. This study aimed to assess the physicochemical characterization and the impact of incorporating both activated (ASCG and AH160) and functionalized SCG (ASCG-Zn), as well as SCG-derived hydrochars (AH160-Zn), on cucumber yield and plant zinc content. The following physicochemical properties were analyzed: specific surface area, pH and electrical conductivity, polyphenols, and nuclear magnetic resonance. The by-products activated and functionalized with zinc were applied to cucumber crops grown in a greenhouse across multiple harvests. The activation of both SCG and H160 reduced the specific surface area of the particles. However, when these by-products were functionalized, their Zn content increased significantly, up to 7400 ppm. Concerning polyphenol content, the activated products showed levels ranging from 3.5 to 4.9 mg GAE/g. Regarding cumulative production, the treatments that showed the highest yields were the by-products activated and functionalized with Zn reaching 25 kg. Incorporating these by-products notably raised the Zn content in cucumbers, reaching 0.1 mg Zn per 100 g of fresh weight. The activated by-products demonstrated the highest Zn utilization efficiency. Full article

(This article belongs to the Special Issue Effects of Agrotechnical Factors and Farming Systems on Soil Properties and Plant Productivity)

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15 pages, 3277 KiB

Open AccessArticle

Warming Increases Ecological Niche of Leymus chinensis but Is Detrimental to Species Diversity in Inner Mongolia Temperate Grasslands

by Xingbo Zhang, Zhiqiang Wan, Rui Gu, Lingman Dong, Xuemeng Chen, Xi Chun, Haijun Zhou and Weiqing Zhang

Agronomy 2024, 14(10), 2425; https://doi.org/10.3390/agronomy14102425 - 19 Oct 2024

Viewed by 475

Abstract

Dominant species are crucial in regulating the structure and productivity of plant communities. Adaptation strategies to climate change vary among the dominant species of different life types. However, the responses of the ecological niches of dominant species to warming and precipitation in semi-arid [...] Read more.

Dominant species are crucial in regulating the structure and productivity of plant communities. Adaptation strategies to climate change vary among the dominant species of different life types. However, the responses of the ecological niches of dominant species to warming and precipitation in semi-arid grasslands and their impacts on community structure and function are unknown. This study involved conducting a long-term experimental simulation of warming and increased precipitation on grasslands in Inner Mongolia and studying population dynamics, ecological niches, and their responses to the structure and function of the community species of two dominant plants, L. chinensis (perennial rhizome grass) and S. krylovii (perennial clumped grass). The results show that the niche width of L. chinensis increased and S. krylovii decreased under warming and increased precipitation conditions. The overlap of L. chinensis and S. krylovii decreased under the same conditions. The niche widths of L. chinensis and S. krylovii were 1.22 for the control (C), 1.19 and 1.04 under warming (W) conditions, 1.27 and 0.97 under warming plus precipitation (WP) conditions, and 1.27 and 1.24 under the conditions of precipitation addition (P). The niche overlap of L. chinensis and S. krylovii were 0.72 in C, 0.69 in W, 0.68 in WP, and 0.82 in P. The biomass share and importance value of L. chinensis increased, and those of S. krylovii decreased in response to warming and precipitation. The effects of warming on species diversity and community stability are primarily influenced by the effects on the niche breadth of S. krylovii. Combined with our previous study, L. chinensis will offer more resources in communities in warmer and wetter steppe climates in the future. However, this is not conducive to community diversity. Full article

(This article belongs to the Section Grassland and Pasture Science)

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26 pages, 8706 KiB

Open AccessArticle

The Effect of Biobased N and P Fertilizers in a Winter Wheat–Ryegrass Crop Rotation

by Benedikt Müller, Michelle Natalie Herrmann, Iris Lewandowski, Torsten Müller, Jens Hartung and Andrea Bauerle

Agronomy 2024, 14(10), 2424; https://doi.org/10.3390/agronomy14102424 - 19 Oct 2024

Viewed by 923

Abstract

Novel recycled fertilizers could help close environmental nutrient cycles in the circular economy. To better understand their performance and residual value, commercially available biobased nitrogen (N) and phosphorus (P) fertilizers (BBFs) were tested in a two-year crop cycle of winter wheat and ryegrass. [...] Read more.

Novel recycled fertilizers could help close environmental nutrient cycles in the circular economy. To better understand their performance and residual value, commercially available biobased nitrogen (N) and phosphorus (P) fertilizers (BBFs) were tested in a two-year crop cycle of winter wheat and ryegrass. The N fertilizer replacement value of N-BBFs ranged from 47 to 80% in the main crop. Not all BBFs led to a similarly high N concentration as the mineral reference in the wheat straw. However, full and early fertilization with incorporation could make the fertilizing effect of N-BBFs more reliable. The P fertilizer replacement value ranged between 105 and 161% for the crop cycle. We assume that the N contained in biobased phosphorus fertilizers can be seen as unproblematic for losses during winter and can serve as a starter fertilizer already present in the soil for the succeeding crop in spring. In general, biobased P fertilizers had a higher residual value than biobased N fertilizers. However, these residual values were comparable to those of mineral fertilizer references. While P-BBFs proved to be a sustainable and reliable nutrient source for a crop cycle, the N-BBFs used as the main crop fertilizer were found to be more prone to environmental influences. Full article

(This article belongs to the Special Issue Sustainable Cropping Systems and Biomasses for Energy and Biorefinery Applications)

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15 pages, 2200 KiB

Open AccessReview

Circular Regenerative Agricultural Practices in Africa: Techniques and Their Potential for Soil Restoration and Sustainable Food Production

by Hamisi J. Tindwa, Ernest W. Semu and Bal Ram Singh

Agronomy 2024, 14(10), 2423; https://doi.org/10.3390/agronomy14102423 - 19 Oct 2024

Viewed by 1585

Abstract

The conventional linear system of global food production and consumption is unsustainable as it is responsible for a substantial share of greenhouse gas emissions, biodiversity declines due land use change, agricultural water stress due resource-intensive water consumption patterns and land degradation. During the [...] Read more.

The conventional linear system of global food production and consumption is unsustainable as it is responsible for a substantial share of greenhouse gas emissions, biodiversity declines due land use change, agricultural water stress due resource-intensive water consumption patterns and land degradation. During the last decade (1994–2014), for example, the greenhouse emissions from agriculture in Africa were reported to increase at an average annual rate of between 2.9% and 3.1%, equivalent to 0.44 Gt and 0.54 Gt CO₂ per annum, respectively. Between 2000 and 2020, the greenhouse gas emissions from agrifood systems were shown to decrease in all major regions of the world, except in Africa and Asia, where they grew by 35 and 20 percent, respectively. With most of the circular agricultural practices still central to food production in the developing African countries, the continent can spearhead a global return to circular agriculture. Using a descriptive review approach, we explore the literature to examine the extent to which African agriculture is deploying these practices, the potential areas for improvement and lessons for the world in embracing sustainable food production. We underscore that the farming communities in sub-Saharan Africa have, for decades, been using some of the most effective circular agricultural principles and practices in agricultural production. We further show that practices and strategies akin to sustainable agricultural production include agronomic practices, smart irrigation options, renewable energy harvesting and waste-to-fertilizer technologies. All of these technologies, which are central to sustainable agricultural production, are not new to Africa, although they may require packaging and advocacy to reach a wider community in sub-Saharan Africa. Full article

(This article belongs to the Collection Innovative Organic and Regenerative Agricultural Production)

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12 pages, 1423 KiB

Open AccessArticle

Cotton Response to Foliar Potassium Application in South Texas Dryland

by Varshith Kommineni, Ammar B. Bhandari, Greta Schuster and Shad D. Nelson

Agronomy 2024, 14(10), 2422; https://doi.org/10.3390/agronomy14102422 - 19 Oct 2024

Viewed by 527

Abstract

Potassium (K) deficiency is common in cotton (Gossypium hirsutum L.)-growing areas. This study aims to investigate the effects of different rates of foliar K fertilizer application on three cotton varieties: NG 5711 B3XF (V1), PHY 480 W3FE (V2), and FM 1953GLTP (V3). [...] Read more.

Potassium (K) deficiency is common in cotton (Gossypium hirsutum L.)-growing areas. This study aims to investigate the effects of different rates of foliar K fertilizer application on three cotton varieties: NG 5711 B3XF (V1), PHY 480 W3FE (V2), and FM 1953GLTP (V3). Potassium fertilizer was dissolved in water and was foliar-applied at 34, 50, and 67 kg ha⁻¹. Cotton plant height (CH) and canopy width (CW) were monitored throughout the growing season. The results showed that foliar K fertilizer application significantly impacted the CH and CW in dry years. Although insignificant, the cotton lint yield increased by 15% and 20% with 34 and 50 kg ha⁻¹ in 2020 and by 9% and 7% with 50 and 67 kg ha⁻¹ in 2021, indicating the potential for improved lint yield with foliar K application in rainfed production systems. Similarly, variety V3 had significantly greater lint and seed yields than V1 in 2020. The average lint yield among the varieties was 32%, and the seed yield was 27% greater in 2020 than in 2021. The cotton fiber color grade was significantly greater at 50 kg ha⁻¹ in 2020 and 67 kg ha⁻¹ in 2021. Cotton variety significantly affected color grade, uniformity, staple length, Col, RD, and Col-b contents in 2020 and 2021. The results suggest that foliar K application can enhance cotton production in rainfed production systems. However, more research is required to quantify varietal and foliar K application rates for improved lint yield and quality. Full article

(This article belongs to the Special Issue Advances in Soil Fertility, Plant Nutrition and Nutrient Management)

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Agronomy, Volume 14, Issue 10 (October 2024) – 272 articles

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