Deep learning in agriculture: A survey Kamilaris, Andreas; Prenafeta-Boldú, Francesc X.
Computers and electronics in agriculture,
April 2018, 2018-04-00, 20180401, Volume:
147
Journal Article
Peer reviewed
Open access
•Survey on the deep learning technique applied in agriculture.•Detailed review of 40 relevant research papers.•Examining research area, technical details, data sources and performance achieved.•Deep ...learning offers high precision outperforming other image processing techniques.•Discussion on advanced deep learning models used in various agricultural problems.•Status, advantages, disadvantages and potential of deep learning in agriculture.•Potential future applications in agriculture using deep learning.
Deep learning constitutes a recent, modern technique for image processing and data analysis, with promising results and large potential. As deep learning has been successfully applied in various domains, it has recently entered also the domain of agriculture. In this paper, we perform a survey of 40 research efforts that employ deep learning techniques, applied to various agricultural and food production challenges. We examine the particular agricultural problems under study, the specific models and frameworks employed, the sources, nature and pre-processing of data used, and the overall performance achieved according to the metrics used at each work under study. Moreover, we study comparisons of deep learning with other existing popular techniques, in respect to differences in classification or regression performance. Our findings indicate that deep learning provides high accuracy, outperforming existing commonly used image processing techniques.
•Survey on the practice of big data analysis in agriculture.•Detailed review of 34 high-impact relevant research studies.•Discussion on the status and potential of big data analysis in ...agriculture.•Open problems and challenges, barriers for wider adoption and use.•Ways to overcome barriers and potential future applications in agriculture.
To tackle the increasing challenges of agricultural production, the complex agricultural ecosystems need to be better understood. This can happen by means of modern digital technologies that monitor continuously the physical environment, producing large quantities of data in an unprecedented pace. The analysis of this (big) data would enable farmers and companies to extract value from it, improving their productivity. Although big data analysis is leading to advances in various industries, it has not yet been widely applied in agriculture. The objective of this paper is to perform a review on current studies and research works in agriculture which employ the recent practice of big data analysis, in order to solve various relevant problems. Thirty-four different studies are presented, examining the problem they address, the proposed solution, tools, algorithms and data used, nature and dimensions of big data employed, scale of use as well as overall impact. Concluding, our review highlights the large opportunities of big data analysis in agriculture towards smarter farming, showing that the availability of hardware and software, techniques and methods for big data analysis, as well as the increasing openness of big data sources, shall encourage more academic research, public sector initiatives and business ventures in the agricultural sector. This practice is still at an early development stage and many barriers need to be overcome.
The concurrence of structurally complex petroleum-associated contaminants at relatively high concentrations, with diverse climatic conditions and textural soil characteristics, hinders conventional ...bioremediation processes. Recalcitrant compounds such as high molecular weight polycyclic aromatic hydrocarbons (HMW-PAHs) and heavy alkanes commonly remain after standard soil bioremediation at concentrations above regulatory limits. The present study assessed the potential of native fungal bioaugmentation as a strategy to promote the bioremediation of an aged industrially polluted soil enriched with heavy hydrocarbon fractions. Microcosms assays were performed by means of biostimulation and bioaugmentation, by inoculating a defined consortium of six potentially hydrocarbonoclastic fungi belonging to the genera
,
,
, and
, which were isolated previously from the polluted soil. The biodegradation performance of fungal bioaugmentation was compared with soil biostimulation (water and nutrient addition) and with untreated soil as a control. Fungal bioaugmentation resulted in a higher biodegradation of total petroleum hydrocarbons (TPH) and of HMW-PAHs than with biostimulation. TPH (C
-C
) decreased by a 39.90 ± 1.99% in bioaugmented microcosms vs. a 24.17 ± 1.31% in biostimulated microcosms. As for the effect of fungal bioaugmentation on HMW-PAHs, the 5-ringed benzo(a)fluoranthene and benzo(a)pyrene were reduced by a 36% and 46%, respectively, while the 6-ringed benzoperylene decreased by a 28%, after 120 days of treatment. Biostimulated microcosm exhibited a significantly lower reduction of 5- and 6-ringed PAHs (8% and 5% respectively). Higher TPH and HMW-PAHs biodegradation levels in bioaugmented microcosms were also associated to a significant decrease in acute ecotoxicity (EC
) by
bioluminiscence inhibition assays. Molecular profiling and counting of viable hydrocarbon-degrading bacteria from soil microcosms revealed that fungal bioaugmentation promoted the growth of autochthonous active hydrocarbon-degrading bacteria. The implementation of such an approach to enhance hydrocarbon biodegradation should be considered as a novel bioremediation strategy for the treatment of the most recalcitrant and highly genotoxic hydrocarbons in aged industrially polluted soils.
Blockchain is an emerging digital technology allowing ubiquitous financial transactions among distributed untrusted parties, without the need of intermediaries such as banks. This article examines ...the impact of blockchain technology in agriculture and food supply chain, presents existing ongoing projects and initiatives, and discusses overall implications, challenges and potential, with a critical view over the maturity of these projects. Our findings indicate that blockchain is a promising technology towards a transparent supply chain of food, with many ongoing initiatives in various food products and food-related issues, but many barriers and challenges still exist, which hinder its wider popularity among farmers and systems. These challenges involve technical aspects, education, policies and regulatory frameworks.
•Discussion of the impact of blockchain in agriculture and food supply chains.•Presentation of many ongoing existing projects and initiatives.•The maturity level of these projects is analyzed.•Blockchain is a promising technology towards a transparent supply chain of food.•Existing challenges involve accessibility, governance, technical aspects, policies and regulatory frameworks.
Tetrapods do not express hydrolases for cellulose and hemicellulose assimilation, and hence, the independent acquisition of herbivory required the establishment of new endosymbiotic relationships ...between tetrapods and microbes. Green turtles (Chelonia mydas) are one of the three groups of marine tetrapods with an herbivorous diet and which acquire it after several years consuming pelagic animals. We characterized the microbiota present in the feces and rectum of 24 young wild and captive green turtles from the coastal waters of Brazil, with curved carapace length ranging from 31.1 to 64.7 cm, to test the hypotheses that (1) the ontogenetic dietary shift after settlement is followed by a gradual change in the composition and diversity of the gut microbiome, (2) differences exist between the composition and diversity of the gut microbiome of green turtles from tropical and subtropical regions, and (3) the consumption of omnivorous diets modifies the gut microbiota of green turtles.
A genomic library of 2,186,596 valid bacterial 16S rRNA reads was obtained and these sequences were grouped into 6321 different operational taxonomic units (at 97% sequence homology cutoff). The results indicated that most of the juvenile green turtles less than 45 cm of curved carapace length exhibited a fecal microbiota co-dominated by representatives of the phyla Bacteroidetes and Firmicutes and high levels of Clostridiaceae, Prophyromonas, Ruminococaceae, and Lachnospiraceae within the latter phylum. Furthermore, this was the only microbiota profile found in wild green turtles > 45 cm CCL and in most of the captive green turtles of any size feeding on a macroalgae/fish mixed diet. Nevertheless, microbial diversity increased with turtle size and was higher in turtles from tropical than from subtropical regions.
These results indicate that juvenile green turtles from the coastal waters of Brazil had the same general microbiota, regardless of body size and origin, and suggest a fast acquisition of a polysaccharide fermenting gut microbiota by juvenile green turtles after settlement into coastal habitats.
•A centralized optimal algorithm to solve the logistics problem of satisfying nutrient crops needs by means of livestock manure.•Based on a realistic simulator that considers numerous real-world ...constraints, not addressed by related work.•Implementation and evaluation carried out based on extensive geolocalized data from Catalonia (Spain), one of the densest European farming regions.•Findings show that the use of treatment units in pig farms is not profitable.•Applying treatment units on selected cow farms for composting manure has its merits, under an intelligent choice of cow farms.
Intensive livestock production has a negative environmental impact by producing large amounts of animal dejections, which, if not properly managed, can contaminate nearby water bodies with nutrient excess. However, if the animal manure could be transferred efficiently to nearby crops and used as a fertilizer for the plants, pollution/contamination would be mitigated, transforming manure from a waste to a resource. This valorization of manure from waste to a resource falls within the circular economy principles, but the transportation of manure also comes at an environmental and economic cost. It is a single-objective optimization problem regarding finding the best solution for the logistics process of satisfying nutrient crops needs through livestock manure. This paper uses a centralized optimal algorithm (COA) to solve the problem, based on a realistic simulator that considers numerous real-world constraints that related work has not yet addressed. Implementation and evaluation of this method have been carried out based on extensive geolocalized data from Catalonia (Spain), one of the densest European farming regions, as a case study. The findings show that the use of treatment units in pig farms is not profitable, while applying treatment units on selected cow farms for composting manure has its merits, under an intelligent choice of cow farms. Finally, a comparison of our findings with those of two similar studies in Hangzhou, China and Minnesota, USA, are performed.
Black fungi reported as degraders of volatile aromatic compounds were isolated from hydrocarbon-polluted sites and indoor environments. Several of the species encountered are known opportunistic ...pathogens or are closely related to pathogenic species causing severe mycoses, among which are neurological infections in immunocompetent individuals. Given the scale of the problem of environmental pollution and the phylogenetic relation of aromate-degrading black fungi with pathogenic siblings, it is of great interest to select strains able to mineralize these substrates efficiently without any risk for public health. Fifty-six black strains were obtained from human-made environments rich in hydrocarbons (gasoline car tanks, washing machine soap dispensers) after enrichment with some phenolic intermediates of toluene and styrene fungal metabolism. Based on ITS sequencing identification, the majority of the obtained isolates were members of the genus
Exophiala
.
Exophiala xenobiotica
was found to be the dominant black yeast present in the car gasoline tanks. A higher biodiversity, with three
Exophiala
species, was found in soap dispensers of washing machines. Strains obtained were screened using a 2,6-dichlorophenol-indophenol (DCPIP) assay, optimized for black fungi, to assess their potential ability to degrade toluene. Seven out of twenty strains tested were able to use toluene as carbon source.
•Addressing the logistics process of satisfying nutrient crops needs by means of livestock manure.•A centralized solution has been developed, based on an adapted version of Dijkstra’s algorithm.•A ...decentralized solution has also been developed, based on the foraging behavior of ants.•The centralized solution is more efficient, while the decentralized one is fairer to the farmers.•This is the first application of a decentralized ant-inspired algorithm to this problem.
Intensive livestock production might have a negative environmental impact, by producing large amounts of animal manure, which, if not properly managed, can contaminate nearby water bodies with nutrient excess. However, if animal manure is exported to nearby crop fields, to be used as organic fertilizer, pollution can be mitigated. It is a single-objective optimization problem, in regards to finding the best solution for the logistics process of satisfying nutrient needs of crops by means of livestock manure. This paper proposes three different approaches to solve the problem: a centralized optimal algorithm (COA), a decentralized nature-inspired cooperative technique, based on the foraging behaviour of ants (AIA), as well as a naive neighbour-based method (NBS), which constitutes the existing practice used today in an ad hoc, uncoordinated manner in Catalonia. Results show that the COA approach is 8.5% more efficient than the AIA. However, the AIA approach is fairer to the farmers and more balanced in terms of average transportation distances that need to be covered by each livestock farmer, while it is 1.07 times more efficient than the NBS. Our work constitutes the first application of a decentralized AIA to this interesting real-world problem, in a domain where swarm intelligence methods are still under-exploited.
Display omitted
•The indoor air from agrifood research laboratories comprise a complex COVs mixture.•Black yeasts reduce the total VOCs concentration from indoor air by more than 95%.•Fungal ...hydrophobicity and biodegradation capacity play a major role in VOCs removal.•The emission of fungal volatile metabolites is rather low and species-specific.•Black yeasts might be used advantageously in the biofiltration of indoor air.
Cultures of melanized fungi representative of the black yeast orders Capnodiales (Cladosporium cladosporioides and Neohortaea acidophila) and Chaetothyriales (Cladophialophora psammophila) were confined with indoor air from the laboratory during 48 h. Volatile organic compounds (VOCs) from the headspace were analyzed by thermal desorption gas chromatography time-of-fly mass spectrometry (TD-GC-ToFMS, detection threshold 0.1 μg m−3) and compared against an abiotic control. A mixture of 71 VOCs were identified and quantified in the indoor air (total concentration 1.4 mg m−3). Most of these compounds were removed in the presence of fungal biomass, but 40 newly formed putative volatile metabolites were detected, though at comparatively low total concentrations (<50 μg m−3). The VOCs emission profile of C. cladosporioides, a ubiquitous and well-known species often associated to the sick building syndrome, was consistent with previous literature reports. The specialized C. psammophila and N. acidophila, isolated respectively from gasoline polluted soil and from lignite, displayed rather specific VOCs emission profiles. Mass balances on the fungal uptake and generation of VOCs resulted in overall VOCs removal efficiencies higher than 96% with all tested fungi. Applied aspects and biosafety issues concerning the suitability of black yeasts for the biofiltration of indoor air have been discussed.
A dynamic model for the composting process has been developed, which integrates several biochemical and physical processes. Different microbial populations (mesophilic and thermophilic bacteria, ...actinomycetes and fungi) have been considered, each specialized in certain types of polymeric substrates (carbohydrates, proteins, lipids, hemicellulose, cellulose and lignin) and their hydrolysis products. Heat and mass transfer between the three phases of the system have been taken into account. The gas phase was considered to be composed by nitrogen, oxygen, carbon dioxide, ammonia and water vapour. Model computer simulations provided results that fitted satisfactory the experimental data. A sensitivity analysis was performed to determine the key parameters of the model. The partition of both the composting mass and the active biomass into different major groups of substrates and specialized microbial populations, as well as the factors affecting the gas–liquid equilibrium, were important for an accurate description of the composting process.
PDF
