Journal Description
Agronomy
Agronomy
is an international, scientific, peer-reviewed, open access journal published monthly online by MDPI. The Spanish Society of Plant Physiology (SEFV) is affiliated with Agronomy and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubAg, AGRIS, and other databases.
- Journal Rank: JCR - Q1 (Agronomy) / CiteScore - Q2 (Agronomy and Crop Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 18.7 days after submission; acceptance to publication is undertaken in 2.5 days (median values for papers published in this journal in the first half of 2022).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journals for Agronomy include: Seeds, Agrochemicals and Grasses.
Impact Factor:
3.949 (2021);
5-Year Impact Factor:
4.117 (2021)
Latest Articles
SSR Genotypes of the Puccinia triticina in 15 Provinces of China Indicate Regional Migration in One Season from East to West and South to North
Agronomy 2022, 12(12), 3068; https://doi.org/10.3390/agronomy12123068 (registering DOI) - 04 Dec 2022
Abstract
Leaf rust of wheat caused by Puccinia triticina (Pt) is one of the most common fungal diseases in the southwest and northwest of China, the middle and lower reaches of the Yangtze River, and the southern part of the Huang-Huai-Hai river
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Leaf rust of wheat caused by Puccinia triticina (Pt) is one of the most common fungal diseases in the southwest and northwest of China, the middle and lower reaches of the Yangtze River, and the southern part of the Huang-Huai-Hai river basin. Using 13 simple sequence repeat (SSR) markers, we systematically revealed the genotypic diversities, population differentiation and reproduction of Pt isolates in 15 wheat-producing areas in China. A total of 622 isolates were divided into 3 predominant populations, including the eastern Pt populations, consisting of Pt samples from 8 eastern provinces of Beijing, Hebei, Shanxi, Shaanxi, Anhui, Shandong, Henan, and Heilongjiang; the 4 western Pt populations from Gansu, Qinghai, Sichuan, and Inner Mongolia provinces; and the bridge Pt populations including Jiangsu, Hubei, and Yunnan, which communicated the other 2 populations as a “bridge”. The pathogen transmission of eastern Pt populations was more frequent than western Pt populations. The linkage disequilibrium test indicated that the whole Pt population was in a state of linkage disequilibrium. However, populations of Beijing, Hebei, Shaanxi, Jiangsu, Henan, and Heilongjiang provinces showed obvious linkage equilibrium, while the five provinces of Qinghai, Hubei, Anhui, Shandong, and Inner Mongolia supported clonal modes of reproduction.
Full article
(This article belongs to the Special Issue Epidemiology and Control of Fungal Diseases of Crop Plants)
Open AccessArticle
Comprehensive Analysis of GASA Family Members in the Peanut Genome: Identification, Characterization, and Their Expressions in Response to Pod Development
by
, , , , , , and
Agronomy 2022, 12(12), 3067; https://doi.org/10.3390/agronomy12123067 (registering DOI) - 03 Dec 2022
Abstract
The gibberellic acid-stimulated Arabidopsis (GASA) gene family is essential for plant growth and development, hormone level control, and phytohormone signal transmission. Different plants have been shown to contain numerous GASA homologs. However, there is no knowledge about these proteins in peanuts. In the
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The gibberellic acid-stimulated Arabidopsis (GASA) gene family is essential for plant growth and development, hormone level control, and phytohormone signal transmission. Different plants have been shown to contain numerous GASA homologs. However, there is no knowledge about these proteins in peanuts. In the current study, we performed a thorough bioinformatics and expression analysis and found 20, 22, and 40 GASA genes by genome-wide analyses of A. hypogaea L., A. duranensis, and A. ipaensis, respectively. We analyzed and predicted the physical properties of these genes. Based on the results of our phylogenetic analysis, the evolutionary tree constructed from the 40 AhGASA proteins was divided into seven categories, forming a total of 14 gene pairs. According to our observations, tandem duplication is a significant factor in the expansion of the GASA gene family. AhGASA was unevenly distributed on 20 chromosomes, and 17 tandem duplicated genes were identified. A co-lineage analysis with the A/B subgenome identified 69 linear/parallel homologous gene pairs. A cis-element analysis revealed that the AhGASA protein is crucial for hormone responsiveness. In materials with different size traits at various stages of peanut pod development, transcriptomics and RT-qPCR analyses revealed that AhGASA genes are expressed at various levels and are tissue-specific. This finding suggests that some AhGASA genes may be involved in controlling peanut pod size. This study suggests that GASA genes are crucial for controlling the development of peanut pods and provides the first systematic identification and analysis of GASA genes in peanut. These findings will help future research into the function of the GASA gene in the cultivated peanut.
Full article
(This article belongs to the Special Issue Genetic Dissection of Important Agronomy Characteristics and Gene Function Analysis in Oilseed Crops)
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Open AccessArticle
Experimental Study of the Droplet Deposition Characteristics on an Unmanned Aerial Vehicle Platform under Wind Tunnel Conditions
Agronomy 2022, 12(12), 3066; https://doi.org/10.3390/agronomy12123066 (registering DOI) - 03 Dec 2022
Abstract
Unmanned aerial vehicles (UAVs) are widely used in field pesticide spray operations due to their wide applicability and high operational efficiency. However, their high spray height and fine pesticide droplets lead to a greater risk of drift and likely different droplet deposition outcomes
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Unmanned aerial vehicles (UAVs) are widely used in field pesticide spray operations due to their wide applicability and high operational efficiency. However, their high spray height and fine pesticide droplets lead to a greater risk of drift and likely different droplet deposition outcomes compared to the expectation. So far, most of the previous studies have used direct field methods on UAVs’ droplet deposition characteristics and there have been few carried out in wind tunnels. Thus, in this paper, a simulated UAV platform equipped with TeeJet 80-015 VP fan nozzles was utilized to study the droplet deposition characteristics in a wind tunnel. The droplet deposition amount and drift potential reduction percentage (DPRP) under different spray parameters were obtained. The results showed that when the rotor was open, the deposition amount in the target area increased by 2.6 times and the drift deposition amount decreased by 7.3 times when spraying tap water at 3 m/s wind speed and 3 bar pressure. Faster wind speeds led to greater drift deposition amounts and a lower DPRP, but higher pressures resulted in greater drift deposition amounts and a larger DPRP. The 30 g/L PEG-20000 solution has a higher droplet size and smaller relative droplet spectrum width RS, resulting in the deposition amount in the target area increasing by 9.13% on average and the drift amount decreasing by 24.7% on average, and it can be used as an anti-drift additive when needed. The research results can provide reference and technical support for UAV wind tunnel tests and field operation specifications.
Full article
(This article belongs to the Special Issue Development of Crop Protection Mechanical Engineering Technology, Evaluation of Efficacy and Safety of Pesticide Spraying)
Open AccessReview
Meta-Analysis for Quantifying Carbon Sequestration and Greenhouse Gas Emission in Paddy Soils One Year after Biochar Application
Agronomy 2022, 12(12), 3065; https://doi.org/10.3390/agronomy12123065 (registering DOI) - 03 Dec 2022
Abstract
The incorporation of biochar into soils has been recognized as a promising method to combat climate change. However, the full carbon reduction potential of biochar in paddy soils is still unclear. To give an overview of the quantified carbon reduction, a meta-analysis model
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The incorporation of biochar into soils has been recognized as a promising method to combat climate change. However, the full carbon reduction potential of biochar in paddy soils is still unclear. To give an overview of the quantified carbon reduction, a meta-analysis model of different carbon emission factors was established, and the life cycle-based carbon reduction of biochar was estimated. After one year of incorporation, biochar significantly increased the total soil carbon (by 27.2%) and rice production (by 11.3%); stimulated methane (CH4) and carbon dioxide (CO2) emissions by 13.6% and 1.41%, respectively, but having insignificant differences with no biochar amendment; and reduced nitrous oxide (N2O) emissions by 25.1%. The soil total carbon increase was mainly related to the biochar rate, whereas CH4 emissions were related to the nitrogen fertilizer application rate. Biochar pyrolysis temperature, soil type, and climate were the main factors to influence the rice yield. The total carbon reduction potential of biochar incorporation in Chinese paddy soils in 2020 ranged from 0.0066 to 2.0 Pg C using a biochar incorporation rate from 2 to 40 t ha−1. This study suggests that biochar application has high potential to reduce carbon emissions, thereby contributing to the carbon neutrality goal, but needs field-scale long-term trials to validate the predictions.
Full article
(This article belongs to the Special Issue Biochar for Sustainable Farming and Recultivation)
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Open AccessArticle
Foliar Application of Chitosan and Phosphorus Alleviate the Potato virus Y-Induced Resistance by Modulation of the Reactive Oxygen Species, Antioxidant Defense System Activity and Gene Expression in Potato
by
, , , , , , , , , and
Agronomy 2022, 12(12), 3064; https://doi.org/10.3390/agronomy12123064 (registering DOI) - 03 Dec 2022
Abstract
Viruses pose a serious threat to the sustainable production of economically important crops around the world. In the past 20 years, potato virus Y (PVY) emerged as a relatively new and very serious problem in potatoes, even though it is the oldest known
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Viruses pose a serious threat to the sustainable production of economically important crops around the world. In the past 20 years, potato virus Y (PVY) emerged as a relatively new and very serious problem in potatoes, even though it is the oldest known plant virus. Multiple strains of the virus cause various symptoms on the leaves and tubers of potatoes, resulting in yield reduction and poor-quality tubers. Consequently, it would be very interesting to learn what causes systemic PVY resistance in plants. Natural compounds such as chitosan (CHT) and phosphorus have been developed as alternatives to chemical pesticides to manage crop diseases in recent years. In the current study, potato leaves were foliar-sprayed with chitosan and phosphorus to assess their ability to induce PVY resistance. Compared to untreated plants, the findings demonstrated a significant decrease in disease severity and PVY accumulation in plants for which CHT and P were applied. Every treatment includes significantly increased growth parameters, chlorophyll content, photosynthetic characteristics, osmoprotectants (glycine betaine, proline, and soluble sugar), non-enzymatic antioxidants (glutathione, phenols, and ascorbic acid), enzymatic antioxidants (peroxidase, superoxide dismutase, lipoxygenase, glutathione reductase, catalase, β-1,3 glucanase, and ascorbate peroxidase), phytohormones (gibberellic acid, indole acetic acid, jasmonic acid, and salicylic acid), and mineral content (phosphorus, nitrogen, and potassium), compared to infected plants. However, compared to PVY infection values, CHT and P treatments showed a significant decrease in malondialdehyde, DPPH, H2O2, O2, OH, and abscisic acid levels. In addition, increased expression levels of some regulatory defense genes, including superoxide dismutase (SOD), ascorbic acid peroxidase (APX), relative pathogenesis-related 1 basic (PR-1b), and relative phenylalanine ammonia-lyase (PAL), were found in all treated plants, compared to PVY-infected plants. Conclusion: Phosphorus is the most effective treatment for alleviating virus infections.
Full article
(This article belongs to the Special Issue Perspectives and Challenges for Sustainable Management of Fruit and Foliar Diseases)
Open AccessArticle
Rapid and Accurate Prediction of Soil Texture Using an Image-Based Deep Learning Autoencoder Convolutional Neural Network Random Forest (DLAC-CNN-RF) Algorithm
Agronomy 2022, 12(12), 3063; https://doi.org/10.3390/agronomy12123063 (registering DOI) - 03 Dec 2022
Abstract
Soil determines the degree of water infiltration, crop nutrient absorption, and germination, which in turn affects crop yield and quality. For the efficient planting of agricultural products, the accurate identification of soil texture is necessary. This study proposed a flexible smartphone-based machine vision
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Soil determines the degree of water infiltration, crop nutrient absorption, and germination, which in turn affects crop yield and quality. For the efficient planting of agricultural products, the accurate identification of soil texture is necessary. This study proposed a flexible smartphone-based machine vision system using a deep learning autoencoder convolutional neural network random forest (DLAC-CNN-RF) model for soil texture identification. Different image features (color, particle, and texture) were extracted and randomly combined to predict sand, clay, and silt content via RF and DLAC-CNN-RF algorithms. The results show that the proposed DLAC-CNN-RF model has good performance. When the full features were extracted, a very high prediction accuracy for sand (R2 = 0.99), clay (R2 = 0.98), and silt (R2 = 0.98) was realized, which was higher than those frequently obtained by the KNN and VGG16-RF models. The possible mechanism was further discussed. Finally, a graphical user interface was designed and used to accurately predict soil types. This investigation showed that the proposed DLAC-CNN-RF model could be a promising solution to costly and time-consuming laboratory methods.
Full article
(This article belongs to the Special Issue “Smart Agriculture” Information Technology and Agriculture Cross-Discipline Research and Development)
Open AccessArticle
Impacts of Climate Change on the Mean and Variance of Indica and Japonica Rice Yield in China
Agronomy 2022, 12(12), 3062; https://doi.org/10.3390/agronomy12123062 (registering DOI) - 03 Dec 2022
Abstract
The overall goal of this study was to examine the impacts of climate change on the mean and variance of rice yields in China by using historical climate and crop data. An econometric model was established to estimate Just–Pope stochastic production functions and
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The overall goal of this study was to examine the impacts of climate change on the mean and variance of rice yields in China by using historical climate and crop data. An econometric model was established to estimate Just–Pope stochastic production functions and identify the potential impacts of climate change on the mean and variance of rice yields by type, keeping other factors constant. Based on the estimated production functions, the contribution rate of climatic factors to rice yield was then assessed by conducting the growth accounting of yields over the past 30 years. The results showed that both the mean rice yield and the yield variability were influenced by changes in the mean climate conditions and climatic variance. In the future, the impacts of climate change on rice yields will depend on local regions’ present climatic conditions. The results have implications for improving the adaptation capacity of rice production.
Full article
(This article belongs to the Special Issue Strategic Analysis of Sustainable Agriculture and Future Foods)
Open AccessArticle
Winter Wheat Seeding Decisions for Improved Grain Yield and Yield Components
Agronomy 2022, 12(12), 3061; https://doi.org/10.3390/agronomy12123061 (registering DOI) - 03 Dec 2022
Abstract
The continual re-evaluation of agronomic practices is necessary to improve crop performance and sustainability of the production of winter wheat (Triticum aestivum L.), particularly as genetics and climate conditions change. Recommendations made about winter wheat planting dates, spacing, variety, and seed rates
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The continual re-evaluation of agronomic practices is necessary to improve crop performance and sustainability of the production of winter wheat (Triticum aestivum L.), particularly as genetics and climate conditions change. Recommendations made about winter wheat planting dates, spacing, variety, and seed rates under normal climatic conditions may not be suitable in current times with more climate variability. Our experiment investigated the effect of planting date (early, historic-optimum, and late), row spacing (19 and 25 cm), variety (Goodstreak, Robidoux, and Wesley), and seed rate (1.8, 2.1, 2.3, 2.4, 2.6, 2.8, 3.1, and 3.4 M seeds ha−1) on winter wheat grain yield and yield components. The seeding rate was nested within row spacing in nested-factorial design. A nested-factorial treatment design was used with testing at several locations in Nebraska across two years. Variety had a substantial effect on winter wheat grain yield (p < 0.05). Variety also had a substantial interaction effect with planting date and row spacing 50% of the time (p ≤ 0.01). At Hemingford, for example, Wesley planted at 19 cm had 5.9% more yield when compared to Robidoux planted at 19 cm (5.5 Mg ha−1). Similarly, biomass was influenced by variety across sites (p < 0.01), but a substantial interaction effect also occurred between planting date and variety at two of the three sites. Narrow row spacing (19 cm) led to significantly more tillers (6.9 M ha−1) when planted with Goodstreak at two of the sites. While planting date by itself did not affect any of the responses evaluated, this research highlights the importance of comprehensive and holistic approaches to wheat production in the High Plains.
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(This article belongs to the Section Innovative Cropping Systems)
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The Expanded and Diversified Calmodulin-Binding Protein 60 (CBP60) Family in Rice (Oryza sativa L.) Is Conserved in Defense Responses against Pathogens
Agronomy 2022, 12(12), 3060; https://doi.org/10.3390/agronomy12123060 (registering DOI) - 03 Dec 2022
Abstract
Plant disease management is key to sustainable production of staple food crops. Calcium (Ca2+) signal and phytohormones play critical roles in regulating plant defense responses against pathogens. The Ca2+ signals are sensed, decoded and transduced by calmodulin and other Ca
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Plant disease management is key to sustainable production of staple food crops. Calcium (Ca2+) signal and phytohormones play critical roles in regulating plant defense responses against pathogens. The Ca2+ signals are sensed, decoded and transduced by calmodulin and other Ca2+ -binding proteins, followed by interaction with and modulation of activities of target proteins such as calmodulin-binding proteins (CBPs). Members of the Arabidopsis CBP60 gene family, AtCBP60g and AtSARD1, have emerged as major regulators of immune responses. In this study, we identified a 15 member CBP60 gene family in rice (Oryza sativa) of which OsCBP60g-3, OsCBP60g-4, OsCBP60a and OsSARD-like1 genes were consistently upregulated in rice seedlings in response to infection with both fungal (Magnaporthe oryzae) and bacterial (Xanthomonas oryzae) pathogens as well as by salicylic acid (SA). OsCBP60g-4 and OsCBP60g-3 were induced maximally by SA and brassinosteroid (BR), respectively, and OsCBP60g-4 was expressed at 3-fold higher levels in the M. oryzae resistant rice genotype (IC-346004) as compared to the susceptible rice genotype (Rajendra Kasturi). The considerable expansion of the immunity clade and the up-regulation of several OsCBP60 genes in response to pathogens and defense hormones supports the importance of further investigating OsCBP60 genes as targets for increasing disease resistance in rice.
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(This article belongs to the Section Crop Breeding and Genetics)
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Open AccessArticle
Underestimated Damage Caused by the European Hazelnut Weevil, Curculio nucum (Curculionidae)
Agronomy 2022, 12(12), 3059; https://doi.org/10.3390/agronomy12123059 (registering DOI) - 02 Dec 2022
Abstract
Hazelnut is an important food resource for the larvae and adults of the hazelnut weevil, Curculio nucum. While wormy nuts reflect the impact of such weevils at harvest time, little is known about the other types of damage they cause. To establish a
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Hazelnut is an important food resource for the larvae and adults of the hazelnut weevil, Curculio nucum. While wormy nuts reflect the impact of such weevils at harvest time, little is known about the other types of damage they cause. To establish a comprehensive list of damages, and thereby identify the period of hazelnut vulnerability, male and female weevils were collected weekly and isolated on fruiting branches for 1 week. Based on nut development, higher rates of dropped nutlets, belted nuts, and blank nuts were observed at harvest. Marks specific to weevils, including wormy nuts, riddled shells, and larvae paths on the basal scar, were recorded during nut lignification. Belted nuts and blank nuts are empty nuts and constituted the main damage. The feeding activities of both the adults and larvae, but also the oviposition punctures, are likely to be the main causes of embryo abortions. The greatest damages occurred during kernel growth and when the shell had almost reached its final size. The larvae failed to penetrate fully lignified shells, with dead larvae mainly being found on the basal scar, the later softer part of the hazelnut. In Ségorbe cultivars, the dynamic of hazelnut development is the main factor involved in its susceptibility to C. nucum, with aborted nuts being the most underestimated damage.
Full article
(This article belongs to the Special Issue Preventative Pest Management in Food Crops: A Compilation of Success Stories)
Open AccessFeature PaperArticle
Effect of Pulp Pigmentation Intensity on Consumer Acceptance of New Blood Mandarins: A Cross-Cultural Study in Spain and Italy
Agronomy 2022, 12(12), 3058; https://doi.org/10.3390/agronomy12123058 (registering DOI) - 02 Dec 2022
Abstract
One of the current objectives of different citrus breeding programmes is obtaining new pigmented mandarins. This study investigates to what extent consumer preferences, expectations and purchase intention are affected by the appearance of new mandarins, specifically pulp pigmentation intensity. Four hundred consumers from
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One of the current objectives of different citrus breeding programmes is obtaining new pigmented mandarins. This study investigates to what extent consumer preferences, expectations and purchase intention are affected by the appearance of new mandarins, specifically pulp pigmentation intensity. Four hundred consumers from both Italy and Spain (800 in all) participated in the study. In each country, half were informed about the healthy properties of the anthocyanins responsible for red pulp colouration, while the other half were not. Italians more readily accepted new mandarin varieties than Spaniards, which was linked to them being more familiar with blood oranges. In Italy, both slight- and medium-pigmented mandarins were well-accepted. Spanish consumers preferred the slight-pigmented variety. The most intense pigmented varieties were not well-accepted in either country. Health-related information positively affected Spaniards’ consumer response but did not modify that of Italians. A halo effect was detected in Spain, where health-related information positively affected mandarin appearance liking and its expected taste liking. Consumer perception that new varieties were unnatural was identified as a consumption barrier, mainly in Spain. Blood orange familiarity and health claims are revealed as conditioning factors for consumer response to pigmented mandarins. Interventions should be made to inform consumers that these varieties are obtained by conventional breeding and not by transgenic technology. Future studies should evaluate consumer response to other sensory characteristics, such as odour, taste and texture.
Full article
(This article belongs to the Special Issue Effects of Agronomical Practices on Crop Quality and Sensory Profile)
Open AccessArticle
Effects of Grazing Intensity on the Carbon, Nitrogen, and Phosphorus Content, Stoichiometry, and Storage of Plant Functional Groups in a Meadow Steppe
Agronomy 2022, 12(12), 3057; https://doi.org/10.3390/agronomy12123057 (registering DOI) - 02 Dec 2022
Abstract
Studies on the impacts of grazing on carbon, nitrogen, and phosphorus stoichiometry and storage are crucial for better understanding the nutrient cycles of grasslands ecosystems. Using a controlled grazing experimental platform in a meadow steppe ecosystem, the effects of different stocking rates (0.00,
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Studies on the impacts of grazing on carbon, nitrogen, and phosphorus stoichiometry and storage are crucial for better understanding the nutrient cycles of grasslands ecosystems. Using a controlled grazing experimental platform in a meadow steppe ecosystem, the effects of different stocking rates (0.00, 0.23, 0.34, 0.46, 0.69, and 0.92 AU ha−1) on the carbon, nitrogen, and phosphorus contents of plant functional groups were explored. The major results were: (1) The carbon content of Gramineae Barnhart was significantly reduced by grazing intensity (p < 0.05), and the organic carbon content of Cyperaceae Rotundus was significantly higher than that of the other groups; the total nitrogen content of Cyperaceae and other groups and total phosphorus contents of Gramineae, Leguminosae Sp, Cyperaceae, and other groups all increased significantly with increasing grazing intensity (p < 0.05). (2) The carbon, nitrogen, and phosphorus storage amounts of Gramineae, Leguminosae, and Ranunculaceae L decreased significantly with increasing grazing intensity. Heavy grazing reduced the carbon, nitrogen, and phosphorus storage amounts of Cyperaceae and other groups, while the carbon, nitrogen, and phosphorus storage amounts of Compositae were the largest under moderate grazing. (3) The nitrogen content of each functional group was highly significantly negatively correlated with the C/N ratio, and the phosphorus content was highly significantly negatively correlated with the C/P ratio. Grazing and foraging affected the growth of the different functional groups, which in turn affected their carbon, nitrogen, and phosphorus content, stoichiometry, and storage. Moderate grazing improved the nutrient utilization efficiency of grassland and is beneficial for promoting sustainable grassland development.
Full article
(This article belongs to the Special Issue Modeling and Monitoring of Grassland Ecosystem Productivity, Carbon Assimilation and Allocation)
Open AccessArticle
Genetic Diversity and Population Differentiation of Dongxiang Wild Rice (Oryza rufipogon Griff.) Based on SNP Markers
Agronomy 2022, 12(12), 3056; https://doi.org/10.3390/agronomy12123056 (registering DOI) - 02 Dec 2022
Abstract
Dongxiang wild rice (DXWR) is one of the most valuable germplasm resources of rice. It is important to conserve the genetic diversity and uncover the population differentiation of DXWR. In this study, we analyzed the genetic diversity and population differentiation of DXWR based
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Dongxiang wild rice (DXWR) is one of the most valuable germplasm resources of rice. It is important to conserve the genetic diversity and uncover the population differentiation of DXWR. In this study, we analyzed the genetic diversity and population differentiation of DXWR based on whole-genome resequencing of 220 DXWR lines collected from nine natural populations in an ex situ conservation nursery. Almost half of the SNPs and Indels detected in these DXWR lines were absent in cultivated rice or other common wild rice, indicating the potential and importance of DXWR in rice breeding. Based on Structure and PCA analysis, these DXWR lines could be divided into two subpopulations, in which subpopulation G1 had more specific SNPs and Indels and was genetically more genetically diverse than subpopulation G2. The average Fst of regions with low relative genetic diversity between G1 and G2 were significantly lower than whole-genomic Fst, indicating directional selection in these regions. Some functional genes and QTLs were found to locate in highly differentiated regions between G1 and G2. Moreover, the deep root ratios of G2 were significantly higher than G1. Our results would be helpful to the conservation and utilization of DXWR germplasm.
Full article
(This article belongs to the Special Issue Discovery and Utilization of Germplasm Resources in Rice)
Open AccessArticle
Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland
Agronomy 2022, 12(12), 3055; https://doi.org/10.3390/agronomy12123055 (registering DOI) - 02 Dec 2022
Abstract
Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In
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Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.
Full article
(This article belongs to the Special Issue Advance in Grassland Productivity and Sustainability)
Open AccessArticle
Litchi Detection in a Complex Natural Environment Using the YOLOv5-Litchi Model
by
, , , , , , , , , and
Agronomy 2022, 12(12), 3054; https://doi.org/10.3390/agronomy12123054 (registering DOI) - 02 Dec 2022
Abstract
Detecting litchis in a complex natural environment is important for yield estimation and provides reliable support to litchi-picking robots. This paper proposes an improved litchi detection model named YOLOv5-litchi for litchi detection in complex natural environments. First, we add a convolutional block attention
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Detecting litchis in a complex natural environment is important for yield estimation and provides reliable support to litchi-picking robots. This paper proposes an improved litchi detection model named YOLOv5-litchi for litchi detection in complex natural environments. First, we add a convolutional block attention module to each C3 module in the backbone of the network to enhance the ability of the network to extract important feature information. Second, we add a small-object detection layer to enable the model to locate smaller targets and enhance the detection performance of small targets. Third, the Mosaic-9 data augmentation in the network increases the diversity of datasets. Then, we accelerate the regression convergence process of the prediction box by replacing the target detection regression loss function with CIoU. Finally, we add weighted-boxes fusion to bring the prediction boxes closer to the target and reduce the missed detection. An experiment is carried out to verify the effectiveness of the improvement. The results of the study show that the mAP and recall of the YOLOv5-litchi model were improved by 12.9% and 15%, respectively, in comparison with those of the unimproved YOLOv5 network. The inference speed of the YOLOv5-litchi model to detect each picture is 25 ms, which is much better than that of Faster-RCNN and YOLOv4. Compared with the unimproved YOLOv5 network, the mAP of the YOLOv5-litchi model increased by 17.4% in the large visual scenes. The performance of the YOLOv5-litchi model for litchi detection is the best in five models. Therefore, YOLOv5-litchi achieved a good balance between speed, model size, and accuracy, which can meet the needs of litchi detection in agriculture and provides technical support for the yield estimation and litchi-picking robots.
Full article
(This article belongs to the Special Issue Precision Operation Technology and Intelligent Equipment in Farmland)
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Open AccessArticle
Salicylic Acid Pre-Treatment Reduces the Physiological Damage Caused by the Herbicide Mesosulfuron-methyl + Iodosulfuron-methyl in Wheat (Triticum aestivum)
Agronomy 2022, 12(12), 3053; https://doi.org/10.3390/agronomy12123053 (registering DOI) - 02 Dec 2022
Abstract
Chemical herbicides are the most common method of weed control in crops, but they can also negatively affect the host crops, such as wheat (Triticum aestivum L.). The damage caused to the crop plants is often temporary and minor, but sometimes, it
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Chemical herbicides are the most common method of weed control in crops, but they can also negatively affect the host crops, such as wheat (Triticum aestivum L.). The damage caused to the crop plants is often temporary and minor, but sometimes, it can be more substantial, requiring remedial measures. Salicylic acid (SA) is a plant hormone widely used to promote plant growth and to mitigate oxidative stress through its exogenous application. We evaluated the role of exogenously applied SA (as a pre-treatment) in ameliorating the oxidative damage caused by the herbicide mesosulfuron-methyl + iodosulfuron-methyl in wheat plants. The herbicide disrupted the physiological function of plants by affecting several enzymatic antioxidants. The hydrogen peroxide (H2O2) and malondialdehyde (MDA) contents increased at herbicide concentrations higher than 18 g ai ha−1 compared with the untreated control. However, the SA decreased the H2O2 and MDA contents compared with plants that were not treated with SA prior to the herbicide application. The activity of superoxide dismutase (SOD) and polyphenol oxidase (PPO) enzymes increased with increasing rates of the herbicide, as well as over time, regardless of the SA treatment. The activity of catalase (CAT) increased up to the herbicide rate of 18 g ai ha−1 and then decreased at the higher rates, while SA pre-treatment enhanced the CAT activity. The activities of ascorbate peroxidase, peroxidase, and glutathione-S-transferase enzymes generally increased in response to the herbicide application and SA pre-treatment, but fluctuated across different days of sampling following the herbicide application. Herbicide stress also induced high levels of proline production in wheat leaves as compared with the untreated control, while SA pre-treatment decreased the proline contents. Overall, the pre-treatment with different concentrations of SA mitigated the herbicide damage to the physiological functions by regulating the enzymatic antioxidants.
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(This article belongs to the Special Issue Crop Productivity and Energy Balance in Large-Scale Fields)
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Edge-Compatible Deep Learning Models for Detection of Pest Outbreaks in Viticulture
by
, , , , , and
Agronomy 2022, 12(12), 3052; https://doi.org/10.3390/agronomy12123052 (registering DOI) - 02 Dec 2022
Abstract
The direct effect of global warming on viticulture is already apparent, with unexpected pests and diseases as one of the most concerning consequences. Deploying sticky traps on grape plantations to attract key insects has been the backbone of conventional pest management programs. However,
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The direct effect of global warming on viticulture is already apparent, with unexpected pests and diseases as one of the most concerning consequences. Deploying sticky traps on grape plantations to attract key insects has been the backbone of conventional pest management programs. However, they are time-consuming processes for winegrowers, conducted through visual inspection via the manual identification and counting of key insects. Additionally, winegrowers usually lack taxonomy expertise for accurate species identification. This paper explores the usage of deep learning on the edge to identify and quantify pest counts automatically. Different mobile devices were used to acquire a dataset of yellow sticky and delta traps, consisting of 168 images with 8966 key insects manually annotated by experienced taxonomy specialists. Five different deep learning models suitable to run locally on mobile devices were selected, trained, and benchmarked to detect five different insect species. Model-centric, data-centric, and deployment-centric strategies were explored to improve and fine-tune the considered models, where they were tested on low-end and high-end mobile devices. The SSD ResNet50 model proved to be the most suitable architecture for deployment on edge devices, with accuracies per class ranging from 82% to 99%, the F1 score ranging from 58% to 84%, and inference speeds per trap image of 19.4 s and 62.7 s for high-end and low-end smartphones, respectively. These results demonstrate the potential of the approach proposed to be integrated into a mobile-based solution for vineyard pest monitoring by providing automated detection and the counting of key vector insects to winegrowers and taxonomy specialists.
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(This article belongs to the Special Issue Application of Image Processing in Agriculture)
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Deep Learning-Based Weed Detection in Turf: A Review
Agronomy 2022, 12(12), 3051; https://doi.org/10.3390/agronomy12123051 - 02 Dec 2022
Abstract
Precision spraying can significantly reduce herbicide input for turf weed management. A major challenge for autonomous precision herbicide spraying is to accurately and reliably detect weeds growing in turf. Deep convolutional neural networks (DCNNs), an important artificial intelligent tool, demonstrated extraordinary capability to
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Precision spraying can significantly reduce herbicide input for turf weed management. A major challenge for autonomous precision herbicide spraying is to accurately and reliably detect weeds growing in turf. Deep convolutional neural networks (DCNNs), an important artificial intelligent tool, demonstrated extraordinary capability to learn complex features from images. The feasibility of using DCNNs, including various image classification or object detection neural networks, has been investigated to detect weeds growing in turf. Due to the high level of performance of weed detection, DCNNs are suitable for the ground-based detection and discrimination of weeds growing in turf. However, reliable weed detection may be subject to the influence of weeds (e.g., biotypes, species, densities, and growth stages) and turf factors (e.g., turf quality, mowing height, and dormancy vs. non-dormancy). The present review article summarizes the previous research findings using DCNNs as the machine vision decision system of smart sprayers for precision herbicide spraying, with the aim of providing insights into future research.
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(This article belongs to the Special Issue The Future of Weed Science—Novel Approaches to Weed Management)
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Carbon Dioxide Efflux of Bare Soil as a Function of Soil Temperature and Moisture Content under Weather Conditions of Warm, Temperate, Dry Climate Zone
by
, , , , , and
Agronomy 2022, 12(12), 3050; https://doi.org/10.3390/agronomy12123050 - 01 Dec 2022
Abstract
It is difficult to estimate the contribution of individual sources to the total CO2 efflux from soil with vegetation. Long-term experiments with bare soil will provide useful conclusions. In this study, we aimed to mathematize the effect of soil temperature and soil
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It is difficult to estimate the contribution of individual sources to the total CO2 efflux from soil with vegetation. Long-term experiments with bare soil will provide useful conclusions. In this study, we aimed to mathematize the effect of soil temperature and soil moisture content on bare soil CO2 efflux in a four-season semiarid region to assess the adequacy of different models and to enable future predictions by seasons. We proved that the exponential model adequately described the relationship between the CO2 efflux and the soil temperature. The model calculations showed no significant relationship in the case of an additional quadratic exponential function, while, in the case of the linear model, the homoscedasticity criteria were not met, and the accuracy of the estimation was found to be dependent on the level of CO2 efflux. When the soil moisture content with either an exponential function or power was added to the exponential formula, the models did not provide more accurate results. Our findings confirm that the best-fitting models are dependent on the local environmental conditions, and there are areas in which the moisture content does not significantly affect the CO2 efflux of bare soil. Using trends in historical hourly temperature data in the exponential model, the CO2 emission was estimated to be in the range 772–898 g m−2 y−1 in 2050 in the location we used. Trends in climate change are expected to have considerable effects on the processes that govern the CO2 emissions of soil.
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Antifeeding, Toxic, and Growth-Reducing Activity of trans-Anethole and S-(+)-Carvone against Larvae of the Gypsy Moth Lymantria dispar (L.)
by
, , , , , and
Agronomy 2022, 12(12), 3049; https://doi.org/10.3390/agronomy12123049 - 01 Dec 2022
Abstract
Botanicals, such as essential oils (EO) and their compounds, are considered a viable eco-friendly alternative to synthetic insecticides, which threaten human health and ecosystem functioning. In the present study, we explored the potential use of two EO compounds, trans-anethole (phenylpropanoide) and S
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Botanicals, such as essential oils (EO) and their compounds, are considered a viable eco-friendly alternative to synthetic insecticides, which threaten human health and ecosystem functioning. In the present study, we explored the potential use of two EO compounds, trans-anethole (phenylpropanoide) and S-(+)-carvone (monoterpene ketone), against gypsy moth larvae (GML), a serious pest of deciduous forests and orchards. GML feeding, survival, molting, and nutritional physiology were assessed at different compound concentrations and compared with the effects of the commercial botanical product NeemAzal®-T/S (neem). The impact of botanicals on GML feeding was assessed by the leaf-dipping method and showed the highest antifeeding activity of neem in the no-choice assay. GML that were offered a choice were deterred by anethole and attracted by low concentrations of carvone and neem. Ingestion of botanicals was more effective in inducing mortality and reducing molting than residual contact exposure. Anethole and carvone were better toxicants but worse growth regulators than neem. Assessing nutritional indices revealed reduced growth, consumption, and food utilization in larvae fed on botanical-supplemented diets. The highest metabolic cost of food processing was recorded in carvone-fed larvae, which exhibited a negative growth rate. The results suggest that anethole and carvone might be used as control agents against GML.
Full article
(This article belongs to the Special Issue Insecticide Resistance and Novel Insecticides)
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Plant Functional Genomics and Crop Genetic Improvement
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Weed Resistance to Herbicides: Assessing and Finding Solutions for a Complex Problem
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