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Agronomy (ISSN 2073-4395; CODEN: ABSGGL) is an international, scientific, peer-reviewed, open access journal published monthly online by MDPI.
- Open Access free for readers, with article processing charges (APC) paid by authors or their institutions.
- High visibility: Indexed in the Science Citation Index Expanded (SCIE) - Web of Science from Vol. 5 (2015). Covered in Scopus, from Vol. 5, and other databases.
- Rapid publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 19.8 days after submission; acceptance to publication is undertaken in 4.1 days (median values for papers published in this journal in the second half of 2018).
- 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.
Impact Factor: 1.419 (2017)
Latest Articles
Effect of Vermicompost Application on Bioactive Properties and Antioxidant Potential of MD2 Pineapple Fruits
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Agronomy 2019, 9(2), 97; https://doi.org/10.3390/agronomy9020097 (registering DOI) - 19 February 2019
Abstract
Vermicompost is an organic waste produced from earthworms that can enhance the soil condition and is rich with essential plant nutrients, thus increasing produce quality and shelf life. In this study, a one-year field trial was conducted to elucidate the effects of vermicompost
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Vermicompost is an organic waste produced from earthworms that can enhance the soil condition and is rich with essential plant nutrients, thus increasing produce quality and shelf life. In this study, a one-year field trial was conducted to elucidate the effects of vermicompost supplementation on the composition of bioactive compounds and antioxidant activities of pineapple (Ananas comosus var. MD2) fruits, compared to control and application of chemical fertilizer. Based on the results, pineapple fruits produced from plants supplemented with chemical fertilizer showed the strongest radical scavenging properties against 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), followed by vermicompost and control plants. Application of chemical fertilizer and vermicompost also produced fruits with a very high content of chlorophylls and β-carotene compared to control plants. However, the amounts of bioactive compounds present in fruits produced with chemical fertilizer are higher than in fruits produced with vermicompost. Total phenolics content and Ferric Reducing Antioxidant Power (FRAP) reducing power were lowest in fruit extracts produced from pineapple plants supplemented with vermicompost. These results suggested that vermicompost cannot completely replace chemical fertilizer for the production of fruits with a high content of phytoconstituents but could be used as an additional supplement to reduce environmental pollution and ensure agricultural sustainability.
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An Automated Plot Heater for Field Frost Research in Cereals
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Agronomy 2019, 9(2), 96; https://doi.org/10.3390/agronomy9020096 (registering DOI) - 19 February 2019
Abstract
Frost research to improve genetics or management solutions requires a robust experimental design that minimizes the effects of all other variables that can cause plant damage except for the treatment (frost). Controlled environment facilities cannot faithfully replicate field radiative frost processes, but field
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Frost research to improve genetics or management solutions requires a robust experimental design that minimizes the effects of all other variables that can cause plant damage except for the treatment (frost). Controlled environment facilities cannot faithfully replicate field radiative frost processes, but field studies are limited by the reliability of field methods to exclude frost. An effective field frost exclusion method needs to prevent frost damage while not impacting growing microclimate or yield, and be automatic, modular, mobile, and affordable. In this study, we designed an effective prototype treatment with these features for field frost research that uses diesel heating. The effectiveness of the plot heater to provide an unfrosted control is evaluated by monitoring canopy temperature (CT) and air temperature during frost events, showing that these remain above zero in the heated plots when ambient temperature drops below zero. We find that the plot heater method can prevent potential frost damage at the plot-scale, while not appearing to have an impact on either plant development or yield components. This offers a potential new tool for frost field crop researchers to incorporate a plot-scale control into their experimental design.
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Genomic Selection in Cereal Breeding
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Agronomy 2019, 9(2), 95; https://doi.org/10.3390/agronomy9020095 (registering DOI) - 19 February 2019
Abstract
Genomic Selection (GS) is a method in plant breeding to predict the genetic value of untested lines based on genome-wide marker data. The method has been widely explored with simulated data and also in real plant breeding programs. However, the optimal strategy and
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Genomic Selection (GS) is a method in plant breeding to predict the genetic value of untested lines based on genome-wide marker data. The method has been widely explored with simulated data and also in real plant breeding programs. However, the optimal strategy and stage for implementation of GS in a plant-breeding program is still uncertain. The accuracy of GS has proven to be affected by the data used in the GS model, including size of the training population, relationships between individuals, marker density, and use of pedigree information. GS is commonly used to predict the additive genetic value of a line, whereas non-additive genetics are often disregarded. In this review, we provide a background knowledge on genomic prediction models used for GS and a view on important considerations concerning data used in these models. We compare within- and across-breeding cycle strategies for implementation of GS in cereal breeding and possibilities for using GS to select untested lines as parents. We further discuss the difference of estimating additive and non-additive genetic values and its usefulness to either select new parents, or new candidate varieties.
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Selection of Salicylic Acid Tolerant Epilines in Brassica napus
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Agronomy 2019, 9(2), 92; https://doi.org/10.3390/agronomy9020092 - 18 February 2019
Abstract
Two of the major pathways involved in induced defense of plants against pathogens include the salicylic acid (SA)- and jasmonic acid (JA)-mediated pathways that act mainly against biotrophs and necrotrophs, respectively. However, some necrotrophic pathogens, such as Botrytis cinerea, actively induce the
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Two of the major pathways involved in induced defense of plants against pathogens include the salicylic acid (SA)- and jasmonic acid (JA)-mediated pathways that act mainly against biotrophs and necrotrophs, respectively. However, some necrotrophic pathogens, such as Botrytis cinerea, actively induce the SA pathway, resulting in cell death that allows the pathogen to proliferate in the plant. Starting from an isogenic canola (Brassica napus) line, epilines were selected with a reduced sensitivity to SA. The genes belonging to the SA pathway had an altered transcription profile in the SA-tolerant lines, when treated with SA. Besides the already known genes of the SA pathway, new SA target genes were identified, creating possibilities to better understand the plant defense mechanism against pathogens. The SA-tolerant line with the lowest SA-induced gene expression is tolerant to Botrytis cinerea. When treated with SA, this line has also a reduced histone modification (histone H3 lysine 4 trimethylation) at the genes at the start of the SA pathway.
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Unsupervised Greenhouse Tomato Plant Segmentation Based on Self-Adaptive Iterative Latent Dirichlet Allocation from Surveillance Camera
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Agronomy 2019, 9(2), 91; https://doi.org/10.3390/agronomy9020091 - 16 February 2019
Abstract
It has long been a great concern in deep learning that we lack massive data for high-precision training sets, especially in the agriculture field. Plants in images captured in greenhouses, from a distance or up close, not only have various morphological structures but
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It has long been a great concern in deep learning that we lack massive data for high-precision training sets, especially in the agriculture field. Plants in images captured in greenhouses, from a distance or up close, not only have various morphological structures but also can have a busy background, leading to huge challenges in labeling and segmentation. This article proposes an unsupervised statistical algorithm SAI-LDA (self-adaptive iterative latent Dirichlet allocation) to segment greenhouse tomato images from a field surveillance camera automatically, borrowing the language model LDA. Hierarchical wavelet features with an overlapping grid word document design and a modified density-based method quick-shift are adopted, respectively, according to different kinds of images, which are classified by specific proportions between fruits, leaves, and the background. We also utilize the feature correlation between several layers of the image to make further optimization through three rounds of iteration of LDA, with updated documents to achieve finer segmentation. Experiment results show that our method can automatically label the organs of the greenhouse plant under complex circumstances, fast and precisely, overcoming the difficulty of inferior real-time image quality caused by a surveillance camera, and thus obtain large amounts of valuable training sets.
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Estimating Body Condition Score in Dairy Cows From Depth Images Using Convolutional Neural Networks, Transfer Learning and Model Ensembling Techniques
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Agronomy 2019, 9(2), 90; https://doi.org/10.3390/agronomy9020090 - 16 February 2019
Abstract
BCS (Body Condition Score) is a method to estimate body fat reserves and accumulated energy balance of cows, placing estimations (or BCS values) in a scale of 1 to 5. Periodically rating BCS of dairy cows is very important since BCS values are
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BCS (Body Condition Score) is a method to estimate body fat reserves and accumulated energy balance of cows, placing estimations (or BCS values) in a scale of 1 to 5. Periodically rating BCS of dairy cows is very important since BCS values are associated with milk production, reproduction, and health of cows. However, in practice, obtaining BCS values is a time-consuming and subjective task performed visually by expert scorers. There have been several efforts to automate BCS of dairy cows by using image analysis and machine learning techniques. In a previous work, an automatic system to estimate BCS values was proposed, which is based on Convolutional Neural Networks (CNNs). In this paper we significantly extend the techniques exploited by that system via using transfer learning and ensemble modeling techniques to further improve BCS estimation accuracy. The improved system has achieved good estimations results in comparison with the base system. Overall accuracy of BCS estimations within 0.25 units of difference from true values has increased 4% (up to 82%), while overall accuracy within 0.50 units has increased 3% (up to 97%).
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Soil Amendment with Raw Garlic Stalk: A Novel Strategy to Stimulate Growth and the Antioxidative Defense System in Monocropped Eggplant in the North of China
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Agronomy 2019, 9(2), 89; https://doi.org/10.3390/agronomy9020089 - 15 February 2019
Abstract
Garlic (Allium Sativum L.) is a vegetable with known medicinal value. It is not only rich in nutrients, but also has the ability to combat different microbial infections. This is, however, the first study to investigate the effect of soil incorporation of
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Garlic (Allium Sativum L.) is a vegetable with known medicinal value. It is not only rich in nutrients, but also has the ability to combat different microbial infections. This is, however, the first study to investigate the effect of soil incorporation of the raw garlic stalk (RGS) on the growth and antioxidative defense system of eggplant. The experiments were conducted in pots using soil amendments of RGS in different ratios (RGS1 1:100; RGS2 3:100; RGS3 5:100 and control (CK) 0:100 of RGS: Soil w/w) and repeated in two consecutive years (2016 and 2017). A dose-dependent response of RGS amendment was observed in the growth and physiology of the eggplant. RGS1 and RGS2 significantly enhanced the plant height, root/shoot weight, stem diameter, leaf area, root length, root activity, pigment contents (chlorophyll a, chlorophyll b, and total chlorophyll), and photosynthetic parameters, but reduced intracellular CO2 (Ci) and enhanced fruit yield as compared with the respective controls. Consistently, RGS also enhanced activities of antioxidative enzymes of eggplant reported as a defense against stress indicators. RGS in its higher ratios (RGS3), however, caused a reduction in all of the growth and physiological parameters and increased stress indicators such as hydrogen peroxide (H2O2) and malondialdehyde (MDA). Overall, RGS2 was found to be the most efficient for regulation of plant defense systems, reducing H2O2 and MDA and enhancing superoxide dismutase (SOD), peroxidase (POD), and phenylalanine ammonia–lyase (PAL) activity. It can be concluded that the appropriate ratio of RGS could efficiently promote plant growth and regulate the reactive oxygen-based plant defense system.
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Aggressiveness and Fumonisins Production of Fusarium Subglutinans and Fusarium Temperatum on Korean Maize Cultivars
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Agronomy 2019, 9(2), 88; https://doi.org/10.3390/agronomy9020088 - 15 February 2019
Abstract
Fusarium root rot and stalk rot are becoming a threat to maize production worldwide. However, there is still limited information about the aggressiveness of Fusarium subglutinans Edwards and Fusarium temperatum and their relationship with fumonisin production. In this study, for the first time,
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Fusarium root rot and stalk rot are becoming a threat to maize production worldwide. However, there is still limited information about the aggressiveness of Fusarium subglutinans Edwards and Fusarium temperatum and their relationship with fumonisin production. In this study, for the first time, the reaction of seven Korean maize cultivars to F. subglutinans and F. temperatum was investigated. The results showed that among the maize cultivars, Hik-chal and Miheung-chal had the highest Fusarium-induced root rot and stalk rot severity, while De Hack-chal had the lowest disease severity regardless of the Fusarium species. Furthermore, the disease resistant cv. De Hack-chal accumulated low levels of fumonisins (FUM) in the infected stalk, while cv. Hik-chal and Miheung-chal had the highest level of FUM. It is worth to note that, plants infected with F. temperatum had a higher FUM concentration compared to cultivars infected with F. subglutinans. The present study shows a significant correlation between stalk rot ratings and FUM levels and it also presents new information about the potential risk of FUM contamination of maize stalk with F. subglutinans and F. temperatum in South Korea. In addition, enzyme activities like polyphenol oxidase (PPO), peroxidase (POD), and the amount of total phenol content (TPC) were studied in selected susceptible cultivar Miheung-chal and resistant cultivar De Hack-chal. The activity of PPO, POD and concentration of TPC were generally higher in the roots of the resistant cultivar than the susceptible cultivar. Moreover, following inoculation of either F. subglutinans or F. temperatum, there was a significant increase in PPO and POD activity in the roots of both cultivars. Hence, the information provided in this study could be helpful to better understand the mechanisms of resistance response to infection of Fusarium root rot pathogens.
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Agronomic Basis and Strategies for Precision Water Management: A Review
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Agronomy 2019, 9(2), 87; https://doi.org/10.3390/agronomy9020087 - 14 February 2019
Abstract
Agriculture faces the challenge of feeding a growing population with limited or depleting fresh water resources. Advances in irrigation systems and technologies allow site-specific application of irrigation water within the field to improve water use efficiency or reduce water usage for sustainable crop
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Agriculture faces the challenge of feeding a growing population with limited or depleting fresh water resources. Advances in irrigation systems and technologies allow site-specific application of irrigation water within the field to improve water use efficiency or reduce water usage for sustainable crop production, especially in arid and semi-arid regions. This paper discusses recent development of variable-rate irrigation (VRI) technologies, data and information for VRI application, and impacts of VRI, including profitability using this technology, with a focus on agronomic factors in precision water management. The development in sprinkler systems enabled irrigation application with greater precision at the scale of individual nozzle control. Further research is required to evaluate VRI prescription maps integrating different soil and crop characteristics in different environments. On-farm trials and whole-field studies are needed to provide support information for practical VRI applications. Future research also needs to address the adjustment of the spatial distribution of prescription zones in response to temporal variability in soil water status and crop growing conditions, which can be evaluated by incorporating remote and proximal sensing data. Comprehensive decision support tools are required to help the user decide where to apply how much irrigation water at different crop growth stages to optimize water use and crop production based on the regional climate conditions and cropping systems.
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Effect of Large-Scale Cultivated Land Expansion on the Balance of Soil Carbon and Nitrogen in the Tarim Basin
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Agronomy 2019, 9(2), 86; https://doi.org/10.3390/agronomy9020086 - 14 February 2019
Abstract
Land reclamation influences the soil carbon and nitrogen cycling, but its scale and time effects on the balance of soil carbon and nitrogen are still uncertain. Taking the Tarim Basin as the study area, the impact of land reclamation on the soil organic
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Land reclamation influences the soil carbon and nitrogen cycling, but its scale and time effects on the balance of soil carbon and nitrogen are still uncertain. Taking the Tarim Basin as the study area, the impact of land reclamation on the soil organic carbon (SOC), total nitrogen (TN), and carbon to nitrogen (C:N) ratio was explored by the multiple temporal changes of land use and soil samples. Remote sensing detected that cropland nearly doubled in area from 1978 to 2015. Spatial analysis techniques were used to identify land changes, including the prior land uses and cultivation ages. Using land reclamation history information, a specially designed soil sampling was conducted in 2015 and compared to soil properties in ca. 1978. Results found a decoupling characteristic between the C:N ratio and SOC or TN, indicating that changes in SOC and TN do not correspond directly to changes in the C:N ratio. The land reclamation history coupled with the baseline effect has opposite impacts on the temporal rates of change in SOC, TN and C:N ratios. SOC and TN decreased during the initial stage of conversion to cropland and subsequently recovered with increasing cultivation time. By contrast, the C:N ratio for soils derived from grassland increased at the initial stage but the increase declined when cultivated longer, and the C:N ratio decreased for soils derived from forest and fluctuated with the cultivation time. Lower C:N ratios than the global average and its decreasing trend with increasing reclamation age were found in newly reclaimed croplands from grasslands. Sustainable agricultural management practices are suggested to enhance the accumulation of soil carbon and nitrogen, as well as to increase the C:N ratio to match the nitrogen deposition to a larger carbon sequestration.
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Agroecological Practices and Agrobiodiversity: A Case Study on Organic Orange in Southern Italy
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Agronomy 2019, 9(2), 85; https://doi.org/10.3390/agronomy9020085 - 14 February 2019
Abstract
The integration of Agroecological Service Crops (ASCs) into agroecosystems can provide several ecological services, such as nutrient cycling and disease and weed management. A two-year experiment on an organic orchard was carried out to compare barley (B) and horse bean (HB) ASCs with
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The integration of Agroecological Service Crops (ASCs) into agroecosystems can provide several ecological services, such as nutrient cycling and disease and weed management. A two-year experiment on an organic orchard was carried out to compare barley (B) and horse bean (HB) ASCs with a control without ASC (Cont) in combination with fertilizers. Their effects on soil fertility and weed- and soil-borne fungi communities were evaluated by direct measurements, visual estimation, and indicators computation. A Principal Component Analysis (PCA) was used to identify latent patterns and redundancy among variables, whereas a correlation analysis was used to discriminate the compared systems within the PCA matrix. The empirical results of this study put in evidence the correlation among soil, weed, and fungal variables. A slight contribution of fertilizers on the system’s variability was observed, whereas a clear effect of ASCs was highlighted. The systems differed in weed communities, with the lowest density associated to B and the highest to Cont. B showed the highest fungal diversity, with changes in community compared to HB. HB showed a contribution on soil fertility, being associated to organic matter increase and N availability, and evidencing mixed impacts on soil quality and ecosystem functioning. Overall, the above-ground diversity and below-ground community results were inter-correlated.
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An Automatic Non-Destructive Method for the Classification of the Ripeness Stage of Red Delicious Apples in Orchards Using Aerial Video
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Agronomy 2019, 9(2), 84; https://doi.org/10.3390/agronomy9020084 - 14 February 2019
Abstract
The estimation of the ripening state in orchards helps improve post-harvest processes. Picking fruits based on their stage of maturity can reduce the cost of storage and increase market outcomes. Moreover, aerial images and the estimated ripeness can be used as indicators for
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The estimation of the ripening state in orchards helps improve post-harvest processes. Picking fruits based on their stage of maturity can reduce the cost of storage and increase market outcomes. Moreover, aerial images and the estimated ripeness can be used as indicators for detecting water stress and determining the water applied during irrigation. Additionally, they can also be related to the crop coefficient (Kc) of seasonal water needs. The purpose of this research is to develop a new computer vision algorithm to detect the existing fruits in aerial images of an apple cultivar (of Red Delicious variety) and estimate their ripeness stage among four possible classes: unripe, half-ripe, ripe, and overripe. The proposed method is based on a combination of the most effective color features and a classifier based on artificial neural networks optimized with genetic algorithms. The obtained results indicate an average classification accuracy of 97.88%, over a dataset of 8390 images and 27,687 apples, and values of the area under the ROC (receiver operating characteristic) curve near or above 0.99 for all classes. We believe this is a remarkable performance that allows a proper non-intrusive estimation of ripening that will help to improve harvesting strategies.
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Research into the E-Learning Model of Agriculture Technology Companies: Analysis by Deep Learning
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Agronomy 2019, 9(2), 83; https://doi.org/10.3390/agronomy9020083 - 13 February 2019
Abstract
With the advancement of technology, the traditional e-learning model may expand the realm of knowledge and differentiate learning by means of deep learning (DL) and augmented reality (AR) scenarios. These scenarios make use of interactive interfaces that incorporate various operating methods, angles, perceptions,
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With the advancement of technology, the traditional e-learning model may expand the realm of knowledge and differentiate learning by means of deep learning (DL) and augmented reality (AR) scenarios. These scenarios make use of interactive interfaces that incorporate various operating methods, angles, perceptions, and experiences, and also draw on multimedia content and active interactive models. Modern education emphasizes that learning should occur in the process of constructing knowledge scenarios and should proceed through learning scenarios and activities. Compared to traditional “spoon-feeding” education, the model learning scenario is initiated with the learner at the center, allowing the person involved in the learning activity to solve problems and further develop their individual capabilities through exploring, thinking and a series of interactions and feedback. This study examined how students in the agriculture technological industry make use of AR digital learning to develop their industry-related knowledge and techniques to become stronger and more mature so that they unconsciously apply these techniques as employees, as well as encouraging innovative thought and methods to create new value for the enterprise.
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Reframing the Debate Surrounding the Yield Gap between Organic and Conventional Farming
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Agronomy 2019, 9(2), 82; https://doi.org/10.3390/agronomy9020082 - 13 February 2019
Abstract
In this article, we review the literature regarding the yield gap between organic and conventional agriculture and then reflect on the corresponding debate on whether or not organic farming can feed the world. We analyze the current framework and highlight the need to
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In this article, we review the literature regarding the yield gap between organic and conventional agriculture and then reflect on the corresponding debate on whether or not organic farming can feed the world. We analyze the current framework and highlight the need to reframe the yield gap debate away from “Can organic feed the world?” towards the more pragmatic question, “How can organic agriculture contribute to feeding the world?”. Furthermore, we challenge the benchmarks that are used in present yield comparison studies, as they are based on fundamentally distinct paradigms of the respective farming methods, and then come up with a novel model to better understand the nature of yield gaps and the benchmarks that they are premised on. We thus conclude that, by establishing appropriate benchmarks, re-prioritizing research needs, and focusing on transforming natural resources rather than inputs, organic systems can raise their yields and play an ever-greater role in global sustainable agriculture and food production in the future.
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To Stop Nitrogen Overdose in Soilless Tomato Crop: A Way to Promote Fruit Quality without Affecting Fruit Yield
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Agronomy 2019, 9(2), 80; https://doi.org/10.3390/agronomy9020080 - 12 February 2019
Abstract
Precision horticulture is fundamental to ensure high quality production with a minimal environmental footprint. It offers the possibility to manage climatic and fertilization inputs closer to the plant needs. In practice, there is a tendency to over-fertilize, as nitrogen limitation can decrease photosynthesis
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Precision horticulture is fundamental to ensure high quality production with a minimal environmental footprint. It offers the possibility to manage climatic and fertilization inputs closer to the plant needs. In practice, there is a tendency to over-fertilize, as nitrogen limitation can decrease photosynthesis and consequently fruit yield, but also because nutrient recycling does not lead to any substantial costs increase, thus ignoring the influence of nitrogen input on the balance between growth and metabolism. Nitrogen recommendation for tomato greenhouse production on rockwool is 16mM, even it is well established that only 50% of nitrogen amount is really absorbed by plants. This study compares the usual practice (16 mM) to a nitrogen supply to meet plant’s needs (5 mM). We analyzed plant growth and development, yield, leaf photosynthetic activity and fruit quality (sugars, acids, vitamin C,) over the entire crop period (December to October). Over-fertilization favoured the accumulation of nitrogen in leaves and stem but yield, leaf photosynthetic activity and plant architecture were not significantly improved. In addition, it decreased the quality of the tomatoes as the sugar:acid ratio decreased dramatically in the pericarp, whereas the locular gel composition remained similar. A reduction of the nitrogen supply is one solution to improve tomato quality without any reduction of yield in greenhouse. These data have to be incorporated in tomato fertigation management to define a new standard based on overall quality of tomato fruit and low environmental footprint.
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Root Distribution and Its Impacts on the Drought Tolerance Capacity of Hybrid Rice in the Sichuan Basin Area of China
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Agronomy 2019, 9(2), 79; https://doi.org/10.3390/agronomy9020079 - 12 February 2019
Abstract
Drought is one of the major factors limiting rice yield worldwide. A total of 46 hybrid rice varieties were chosen to investigate their root distribution and their response to drought. A field experiment was carried out in a dry shed building to evaluate
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Drought is one of the major factors limiting rice yield worldwide. A total of 46 hybrid rice varieties were chosen to investigate their root distribution and their response to drought. A field experiment was carried out in a dry shed building to evaluate the drought tolerance capacity of hybrid rice varieties on the basis of CTIRDE (complex tolerance index of rice under drought environment) values. Next, the experiment was conducted in a specially designed pot system and seed bags to analyze the root distribution and activity of antioxidant enzymes in different rice varieties. Moreover, the DEEPER ROOTING 1 (DRO1) gene was sequenced to elucidate its role in the root distribution of typical rice varieties. On the basis of CTIRDE values, the 46 hybrid rice varieties were classified as tolerant (CTIRDE ≥ 0.75), semi-tolerant (0.75 > CTIRDE > 0.65), or sensitive (CTIRDE ≤ 0.65) to drought stress. The tolerant varieties (Chuanguyou208 and Deyou4727) displayed a significantly larger length, had higher number and weight of roots in the 30–50 cm soil layer, and exhibited a significantly higher activity of Superoxide dismutase (SOD) and Peroxidase (POD) enzymes in roots during the drought stress period. The DRO1 gene sequencing results revealed that the tolerant and sensitive varieties exhibited a single-nucleotide polymorphism (SNP) in the 3-exon region, and the tolerant varieties (Chuanguyou208 and Deyou4727) exhibited a larger root growth angle with the horizontal axis, hence developing a deeper root system as compared with the other two group varieties. A significant correlation was found not only between the DRO1 gene and root distribution but also between DRO1 and the activity of SOD and POD enzymes. Conclusively, as a key feature, a deep root system enabled tolerant rice varieties (Chuanguyou208 and Deyou4727) to avoid drought stress by absorbing more water stored in deep soil layers. The root distribution, activity of POD and SOD enzymes in roots, and DRO1 gene can be used to screen tolerant rice varieties that can survive better under drought stress during the seedling stage of rice growth.
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News
Conferences
Special Issues
Special Issue in
Agronomy
Bioactives from Plants: Content, Accumulation and Means to Reach Higher Levels
Guest Editor: Othmane MerahDeadline: 28 February 2019
Special Issue in
Agronomy
Agricultural Water Management
Guest Editor: Maurizio BorinDeadline: 15 March 2019
Special Issue in
Agronomy
Genetics and Management of Perennial Forage Crops
Guest Editor: Susanne BarthDeadline: 20 March 2019
Special Issue in
Agronomy
Grassland Management for Sustainable Agroecosystems
Guest Editors: Abad Chabbi, Gianni BellocchiDeadline: 31 March 2019
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