Agricultural Species Research Articles

Novel odor sensing intelligence and surveillance capabilities in controller-responder robots

The rise in global travel has led to an increased need for heightened security measures at airports. Despite the best efforts of airport security officers, in the past year, hundreds of kilograms of illegal drugs and thousands of agricultural invasive species have found their way into the country, posing a severe threat to public safety and the environment. Moreover, human threats pose a significant risk to civil aviation, reinforcing the need for advanced security technology. In response to these challenges, NOSI (Novel Odor Sensing Intelligence) and ROSI (Reconnaissance Operations Security Intelligence), intelligence surveillance systems consisting of semi-autonomous controller-responder robots, were developed as a proof of concept to supplement the efforts of security and K-9 (police dogs) operators at airports. NOSI is equipped with multi-channel gas sensors for odor detection, enabling it to identify illegal drugs and invasive species in the baggage handling process, while ROSI is equipped with computer vision to identify individuals already in the government’s database of persons of interest. These coordinated robots also provide travelers with important information pertaining to their journey and allow them to trigger emergency alerts. The robots were tested in a custom-designed test bed that replicated both the behind-the-scenes baggage handling and front-office customer service operations of an airport, thus simulating a realistic airport-like setting. Based on design criteria, NOSI and ROSI demonstrated success rates of 73.4 percent and 69.8 percent, respectively. Improvements in areas of robot stability, sensor accuracy, and feature expansion were documented for further development. In conclusion, the NOSI and ROSI framework can enhance the efficiency and accuracy of airport infrastructure monitoring and supplement the capabilities of human and K9 operators. Overall, this approach can potentially revolutionize operations in various infrastructures and represents the future of human-robot collaboration.

Identification of breadfruit (Artocarpus altilis) and South American crops introduced during early settlement of Rapa Nui (Easter Island), as revealed through starch analysis.

Starch residue analysis was carried out on stone tools recovered from the bottom layer of the Anakena site on Rapa Nui (Easter Island). These deposits have been dated to AD 1000-1300 AD and so far, represent the earliest evidence of human settlement on this island. Twenty obsidian tools were analyzed. Analysis of 46 starch grains recovered from 20 obsidian tools from the earliest dated level of the Anakena site on Rapa Nui provides direct evidence for translocation of traditional crop plants at initial stages of the colonization of this island. The analysis of starch grains was based mainly on statistical methods for species identification but was complemented by visual inspection in some cases. Our results identify taxons previously unknown to have been cultivated on the island, such as breadfruit (Artocarpus altilis), Zingiber officinale (ginger), and starch grains of the Spondias dulcis and Inocarpus fagifer tropical trees. Additionally, starch grains of Colocasia esculenta (taro) and Dioscorea sp. (yam), both common species in Pacific agriculture, were identified. Furthermore, the presence of four American taxa Ipomoea batatas (sweet potato), Canna sp. (achira), Manihot esculenta (manioc), and Xanthosoma sp., was detected. The occurrence of Canna sp., M. esculenta, and Xanthosoma sp. starch grains suggests the translocation of previously not described South American cultivars into the Pacific. The detection of I. batatas from this site in Rapa Nui constitutes the earliest record of this cultigen in the Pacific. Our study provides direct evidence for translocation of a set of traditional Polynesian and South American crop plants at the initial stages of colonization in Rapa Nui.

A first characterization of the microbiota-resilience link in swine

BackgroundThe gut microbiome plays a crucial role in understanding complex biological mechanisms, including host resilience to stressors. Investigating the microbiota-resilience link in animals and plants holds relevance in addressing challenges like adaptation of agricultural species to a warming environment. This study aims to characterize the microbiota-resilience connection in swine. As resilience is not directly observable, we estimated it using four distinct indicators based on daily feed consumption variability, assuming animals with greater intake variation may face challenges in maintaining stable physiological status. These indicators were analyzed both as linear and categorical variables. In our first set of analyses, we explored the microbiota-resilience link using PERMANOVA, α-diversity analysis, and discriminant analysis. Additionally, we quantified the ratio of estimated microbiota variance to total phenotypic variance (microbiability). Finally, we conducted a Partial Least Squares-Discriminant Analysis (PLS-DA) to assess the classification performance of the microbiota with indicators expressed in classes.ResultsThis study offers four key insights. Firstly, among all indicators, two effectively captured resilience. Secondly, our analyses revealed robust relationship between microbial composition and resilience in terms of both composition and richness. We found decreased α-diversity in less-resilient animals, while specific amplicon sequence variants (ASVs) and KEGG pathways associated with inflammatory responses were negatively linked to resilience. Thirdly, considering resilience indicators in classes, we observed significant differences in microbial composition primarily in animals with lower resilience. Lastly, our study indicates that gut microbial composition can serve as a reliable biomarker for distinguishing individuals with lower resilience.ConclusionOur comprehensive analyses have highlighted the host-microbiota and resilience connection, contributing valuable insights to the existing scientific knowledge. The practical implications of PLS-DA and microbiability results are noteworthy. PLS-DA suggests that host-microbiota interactions could be utilized as biomarkers for monitoring resilience. Furthermore, the microbiability findings show that leveraging host-microbiota insights may improve the identification of resilient animals, supporting their adaptive capacity in response to changing environmental conditions. These practical implications offer promising avenues for enhancing animal well-being and adaptation strategies in the context of environmental challenges faced by livestock populations.7uyXcYriZkKxPgmfB9NKtxVideo

Python farming as a flexible and efficient form of agricultural food security

Diminishing natural resources and increasing climatic volatility are impacting agri-food systems, prompting the need for sustainable and resilient alternatives. Python farming is well established in Asia but has received little attention from mainstream agricultural scientists. We measured growth rates in two species of large pythons (Malayopython reticulatus and Python bivittatus) in farms in Thailand and Vietnam and conducted feeding experiments to examine production efficiencies. Pythons grew rapidly over a 12-month period, and females grew faster than males. Food intake and growth rates early in life were strong predictors of total lifetime growth, with daily mass increments ranging from 0.24 to 19.7 g/day for M. reticulatus and 0.24 to 42.6 g/day for P. bivittatus, depending on food intake. Pythons that fasted for up to 4.2 months lost an average of 0.004% of their body mass per day, and resumed rapid growth as soon as feeding recommenced. Mean food conversion rate for dressed carcasses was 4.1%, with useable products (dressed carcass, skin, fat, gall bladder) comprising 82% of the mass of live animals. In terms of food and protein conversion ratios, pythons outperform all mainstream agricultural species studied to date. The ability of fasting pythons to regulate metabolic processes and maintain body condition enhances food security in volatile environments, suggesting that python farming may offer a flexible and efficient response to global food insecurity.

Argonaute and Dicer are essential for communication between Trichoderma atroviride and fungal hosts during mycoparasitism.

Trichoderma species are known for their mycoparasitic activity against phytopathogenic fungi that cause significant economic losses in agriculture. During mycoparasitism, Trichoderma spp. recognize molecules produced by the host fungus and release secondary metabolites and hydrolytic enzymes to kill and degrade the host's cell wall. Here, we explored the participation of the Trichoderma atroviride RNAi machinery in the interaction with six phytopathogenic fungi of economic importance. We determined that both Argonaute-3 and Dicer-2 play an essential role during mycoparasitism. Using an RNA-Seq approach, we identified that perception, detox, and cell wall degradation depend on the T. atroviride-RNAi when interacting with Alternaria alternata, Rhizoctonia solani AG2, and R. solani AG5. Furthermore, we constructed a gene co-expression network that provides evidence of two gene modules regulated by RNAi, which play crucial roles in essential processes during mycoparasitism. In addition, based on small RNA-seq, we conclude that siRNAs regulate amino acid and carbon metabolism and communication during the Trichoderma-host interaction. Interestingly, our data suggest that siRNAs might regulate allorecognition (het) and transport genes in a cross-species manner. Thus, these results reveal a fine-tuned regulation in T. atroviride dependent on siRNAs that is essential during the biocontrol of phytopathogenic fungi, showing a greater complexity of this process than previously established.IMPORTANCEThere is an increasing need for plant disease control without chemical pesticides to avoid environmental pollution and resistance, and the health risks associated with the application of pesticides are increasing. Employing Trichoderma species in agriculture to control fungal diseases is an alternative plant protection strategy that overcomes these issues without utilizing chemical fungicides. Therefore, understanding the biocontrol mechanisms used by Trichoderma species to antagonize other fungi is critical. Although there has been extensive research about the mechanisms involved in the mycoparasitic capability of Trichoderma species, there are still unsolved questions related to how Trichoderma regulates recognition, attack, and defense mechanisms during interaction with a fungal host. In this work, we report that the Argonaute and Dicer components of the RNAi machinery and the small RNAs they process are essential for gene regulation during mycoparasitism by Trichoderma atroviride.

Pastorale urbana. Kampung Admiralty a Singapore e il mito del villaggio

The strategies for the construction of national identity devised by the Singaporean government in the years following independence as a British colony included the evocation of an ideal original landscape, epitomized both by the tropical forests that covered the archipelago of Singapore and by the productive landscape of rural villages, or kampung in Malay. The idealized representations of these two local landscapes were entrusted to the plants selected to shape the greening campaigns accompanying the massive urbanization process that rapidly transformed Singapore into a high-density metropolis. Evolving from that approach is Kampung Admiralty, a large contemporary multifunctional building crowned by roof gardens designed by Singapore-based architectural practice WOHA, with Henning Larsen Landscape as landscape consultant. The architectural and landscape architectural complex appears as a technological celebration of the rural landscape: while the botanical associations employed suggest the varied spaces and lively atmospheres of traditional villages with their distinctive mixture of agricultural, wild, and ornamental plants species, the introduction of nature-based solutions and plant communities promoting biodiversity adapt the operational role of tropical vegetation in sustaining the survival of the community that inhabited the kampung to the needs of the contemporary city.

RNA and protein biomarkers for detecting enhanced metabolic resistance to herbicides mesosulfuron-methyl and fenoxaprop-ethyl in black-grass (Alopecurus myosuroides).

The evolution of non-target site resistance (NTSR) to herbicides leads to a significant reduction in herbicide control of agricultural weed species. Detecting NTSR in weed populations prior to herbicide treatment would provide valuable information for effective weed control. While not all NTSR mechanisms have been fully identified, enhanced metabolic resistance (EMR) is one of the better studied, conferring tolerance through increased herbicide detoxification. Confirming EMR towards specific herbicides conventionally involves detecting metabolites of the active herbicide molecule in planta, but this approach is time-consuming and requires access to well-equipped laboratories. In this study, we explored the potential of using molecular biomarkers to detect EMR before herbicide treatment in black-grass (Alopecurus myosuroides). We tested the reliability of selected biomarkers to predict EMR and survival after herbicide treatments in both reference and 27 field-derived black-grass populations collected from sites across the UK. The combined analysis of the constitutive expression of biomarkers and metabolism studies confirmed three proteins, namely, AmGSTF1, AmGSTU2 and AmOPR1, as differential biomarkers of EMR toward the herbicides fenoxaprop-ethyl and mesosulfuron in black-grass. Our findings demonstrate that there is potential to use molecular biomarkers to detect EMR toward specific herbicides in black-grass without reference to metabolism analysis. However, biomarker development must include testing at both transcript and protein levels in order to be reliable indicators of resistance. This work is a first step towards more robust resistance biomarker development, which could be expanded into other herbicide chemistries for on-farm testing and monitoring EMR in uncharacterised black-grass populations. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Phylogenomic analysis reveals five independently evolved African forage grass clades in the genus Urochloa.

The grass genus Urochloa (Brachiaria) sensu lato includes forage crops that are important for beef and dairy industries in tropical and sub-tropical Africa, South America and Oceania/Australia. Economically important species include U. brizantha, U. decumbens, U. humidicola, U. mutica, U. arrecta, U. trichopus, U. mosambicensis and Megathyrsus maximus, all native to the African continent. Perennial growth habits, large, fast growing palatable leaves, intra- and interspecific morphological variability, apomictic reproductive systems and frequent polyploidy are widely shared within the genus. The combination of these traits probably favoured the selection for forage domestication and weediness, but trait emergence across Urochloa cannot be modelled, as a robust phylogenetic assessment of the genus has not been conducted. We aim to produce a phylogeny for Urochloa that includes all important forage species, and identify their closest wild relatives (crop wild relatives). Finally, we will use our phylogeny and available trait data to infer the ancestral states of important forage traits across Urochloa s.l. and model the evolution of forage syndromes across the genus. Using a target enrichment sequencing approach (Angiosperm 353), we inferred a species-level phylogeny for Urochloa s.l., encompassing 54 species (~40 % of the genus) and outgroups. Phylogenies were inferred using a multispecies coalescent model and maximum likelihood method. We determined the phylogenetic placement of agriculturally important species and identified their closest wild relatives, or crop wild relatives, based on well-supported monophyly. Further, we mapped key traits associated with Urochloa forage crops to the species tree and estimated ancestral states for forage traits along branch lengths for continuous traits and at ancestral nodes in discrete traits. Agricultural species belong to five independent clades, including U. brizantha and U. decumbens lying in a previously defined species complex. Crop wild relatives were identified for these clades supporting previous sub-generic groupings in Urochloa based on morphology. Using ancestral trait estimation models, we find that five morphological traits that correlate with forage potential (perennial growth habits, culm height, leaf size, a winged rachis and large seeds) independently evolved in forage clades. Urochloa s.l. is a highly diverse genus that contains numerous species with agricultural potential, including crop wild relatives that are currently underexploited. All forage species and their crop wild relatives naturally occur on the African continent and their conservation across their native distributions is essential. Genomic and phenotypic diversity in forage clade species and their wild relatives need to be better assessed both to develop conservation strategies and to exploit the diversity in the genus for improved sustainability in Urochloa cultivar production.

Taxonomy, Biology, Symbionts, Omics, and Management of Rhynchophorus Palm Weevils (Coleoptera: Curculionidae: Dryophthorinae).

Palm weevils, Rhynchophorus spp., are destructive pests of native, ornamental, and agricultural palm species. Of the 10 recognized species, two of the most injurious species, Rhynchophorus ferrugineus and Rhynchophorus palmarum, both of which have spread beyond their native range, are the best studied. Due to its greater global spread and damage to edible date industries in the Middle East, R. ferrugineus has received more research interest. Integrated pest management programs utilize traps baited with aggregation pheromone, removal of infested palms, and insecticides. However, weevil control is costly, development of resistance to insecticides is problematic, and program efficacy can be impaired because early detection of infestations is difficult. The genome of R. ferrugineus has been sequenced, and omics research is providing insight into pheromone communication and changes in volatile and metabolism profiles of weevil-infested palms. We outline how such developments could lead to new control strategies and early detection tools.

Automated Classification of Agricultural Species through Parallel Artificial Multiple Intelligence System–Ensemble Deep Learning

The classification of certain agricultural species poses a formidable challenge due to their inherent resemblance and the absence of dependable visual discriminators. The accurate identification of these plants holds substantial importance in industries such as cosmetics, pharmaceuticals, and herbal medicine, where the optimization of essential compound yields and product quality is paramount. In response to this challenge, we have devised an automated classification system based on deep learning principles, designed to achieve precision and efficiency in species classification. Our approach leverages a diverse dataset encompassing various cultivars and employs the Parallel Artificial Multiple Intelligence System–Ensemble Deep Learning model (P-AMIS-E). This model integrates ensemble image segmentation techniques, including U-Net and Mask-R-CNN, alongside image augmentation and convolutional neural network (CNN) architectures such as SqueezeNet, ShuffleNetv2 1.0x, MobileNetV3, and InceptionV1. The culmination of these elements results in the P-AMIS-E model, enhanced by an Artificial Multiple Intelligence System (AMIS) for decision fusion, ultimately achieving an impressive accuracy rate of 98.41%. This accuracy notably surpasses the performance of existing methods, such as ResNet-101 and Xception, which attain 93.74% accuracy on the testing dataset. Moreover, when applied to an unseen dataset, the P-AMIS-E model demonstrates a substantial advantage, yielding accuracy rates ranging from 4.45% to 31.16% higher than those of the compared methods. It is worth highlighting that our heterogeneous ensemble approach consistently outperforms both single large models and homogeneous ensemble methods, achieving an average improvement of 13.45%. This paper provides a case study focused on the Centella Asiatica Urban (CAU) cultivar to exemplify the practical application of our approach. By integrating image segmentation, augmentation, and decision fusion, we have significantly enhanced accuracy and efficiency. This research holds theoretical implications for the advancement of deep learning techniques in image classification tasks while also offering practical benefits for industries reliant on precise species identification.

Survey on Drosophila suzukii and Ceratitis capitata (Diptera: Drosophilidae, Tephritidae) and Associated Eucoilinae Species (Hymenoptera: Figitidae) in Northwestern Argentina. First Record of Dicerataspis grenadensis and Leptopilina boulardi as Parasitoids of D. suzukii.

The Southeast Asian-native Drosophila suzukii (Matsumura) (Diptera: Drosophilidae), also known as "spotted-wing Drosophila," is one of the most globally invasive agricultural species. Although D. suzukii is a pest spread throughout all the Argentinian fruit-growing regions, few information has been published on its impact on local fruit production. Parasitoid species associated with D. suzukii in Argentina belong to Pteromalidae (Chalcidoidea), Diapriidae (Diaprioidea), both attacking host pupae, and Figitidae (Cynipoidea), which attack host larvae. Nine Eucoilinae (Figitidae) species, belonging to Dicerataspis, Dieucoila, Euxestophaga, Ganaspis, Hexacola, and Leptopilina genera, have been associated with D. suzukii in Argentina. Ceratitis capitata (Wiedemann), commonly known as "medfly," is native to Africa and has a worldwide distribution, covering many tropical, subtropical, and temperate regions. In Argentina, C. capitata has been associated with several native hymenopterous parasitoids belonging to Braconidae (Ichneumonioidea), Eulophidae (Chalcidoidea), Pteromalidae, Diapriidae, and Figitidae families. Only two eucoline species, Ganaspis pelleranoi (Brèthes) and Leptopilina haywardi (Blanchard) have been related to medfly in Argentina. We report new trophic associations between the parasitoids Dicerataspis grenadensis Ashmead and Leptopilina boulardi (Barbotin, Carton and Kelner-Pillault) and D. suzukii, and between the parasitoid Odontosema albinerve Kieffer and C. capitata, after surveys conducted in Tucumán, northwestern Argentina. An annotated checklist and a taxonomic key of Eucoilinae associated with both invasive pests, in Argentina, are also provided.

Gene drive and genetic sex conversion in the global agricultural pest Ceratitis capitata

Homing-based gene drives are recently proposed interventions promising the area-wide, species-specific genetic control of harmful insect populations. Here we characterise a first set of gene drives in a tephritid agricultural pest species, the Mediterranean fruit fly Ceratitis capitata (medfly). Our results show that the medfly is highly amenable to homing-based gene drive strategies. By targeting the medfly transformer gene, we also demonstrate how CRISPR-Cas9 gene drive can be coupled to sex conversion, whereby genetic females are transformed into fertile and harmless XX males. Given this unique malleability of sex determination, we modelled gene drive interventions that couple sex conversion and female sterility and found that such approaches could be effective and tolerant of resistant allele selection in the target population. Our results open the door for developing gene drive strains for the population suppression of the medfly and related tephritid pests by co-targeting female reproduction and shifting the reproductive sex ratio towards males. They demonstrate the untapped potential for gene drives to tackle agricultural pests in an environmentally friendly and economical way.

Features of the distribution of species of the genus Ferula L. on the territory of the Turan lowland

This article presents materials on the study of the distribution area of Ferula species in the flora of the Turonian lowland. The presented materials were obtained as a result of field research. Herbarium materials were collected during our research. The life forms of the plant were studied, and the chemical composition of Ferula species in the area was determined. The importance of Ferula species in agriculture was studied.

Overview of insights into the role of Bacillus species in drought stress alleviation and plant disease management

Drought and plant diseases are major constraints on crop production, causing significant losses. As the effects of climate change worsen, there is an urgent need to adopt sustainable agricultural strategies. Plant Growth-Promoting Bacteria (PGPB) are emerging as a promising approach, aimed at enhancing productivity and plant resilience to various stresses. Among them, Bacillus spp. are gaining research interest due to their unique ability to adapt to harsh environmental conditions and produce metabolites of interest in several sectors. Besides improving plant growth and yield, Bacillus plays a pivotal role in enhancing the ability of plants to withstand drought stress mainly by producing of water absorbing substances and enhancing water and nutrient uptake. Some Bacillus species are able to effectively resist plant pathogens through several mechanisms, including antibiosis, competition, induced systemic resistance (ISR), and enriching the microbiome of the soil, enabling them to become important biological agents in the management of plant diseases. This overview aims to highlight the potential of Bacillus species in sustainable agriculture, focusing on their role in mitigating drought stress and controlling plant diseases.

Assessment of the phytotoxicity of petroleum-polluted black soil in relation to agricultural and wild species of phytoremediator plants

The effect of petroleum pollution on soil was assessed for its impact on the adaptation properties of 12 agricultural and 5 wild plant species. The influence of petroleum on seed germination was determined at concentrations of 1%, 3%, 4%, 6%, and 8% in the soil. Wild plants exhibited lower germination rates compared to cultivated species. For most cultivated plants, a 1% concentration of petroleum did not inhibit seed germination, but germination decreased to 60-80% of the control under concentrations of 2% and 4%. In soil containing 6% petroleum, peas, clover, alfalfa, and sunflower exhibited germination rates of more than 50%, while alfalfa and sunflower germinated only at an 8% concentration. The assessment of soil phytotoxicity revealed that sunflower plants are the most resistant to petroleum pollution. A comparison of resistance to soil petroleum pollution among four sunflower varieties showed that the ’Bombardir’ cultivar exhibited the best growth parameters.

Study of the Influence of Cultivar and Biological Seed Category on Winter Wheat Production

Wheat is one of the most cultivated agricultural species alongside corn and rice. In this study, we tested the influence of cultivars and seed biological class on yield in winter wheat. As a comparison, we used two Romanian varieties, Dropia and Faur, and two foreign varieties, Apache and Bercy in field-testing under normal agronomical practices. Data obtained in field trails was statistically processed by Duncan test for multiple comparisons between tested variants. Results indicate that yield decreases according to the seed biological class. Furthermore, the analysis of the distribution of significance differences in production, it resulted that both the cultivar and the biological category of the seeds act individually and combined on the average yields of winter wheat. Since the assortment of varieties in winter wheat is one that is renewed every year, and as a result of the fact that farmers have the option of multiplying the seed of autogamous varieties for their own use, we believe that the obtained results can be useful in evaluating the productive potential of winter wheat crops sown with seed from certified generations C1 and C2 or from subsequent generations of multiplication, which are not subject to the official certification process.

Lupinus mutabilis Breeding in the Andes of Ecuador, Peru, and Bolivia: A Review

Lupinus mutabilis, also known as tarwi or chocho, is an important agricultural species that has been cultivated in South America since ancient times. Tarwi is native to the Andean regions of Peru, Bolivia, and Ecuador and has very high protein content. Despite its high nutritional value and promotion efforts by regional researchers and breeders, tarwi is not a widely cultivated crop in its center of origin. In this review, we present the work carried out by public breeding programs of L. mutabilis at national agricultural research institutes, universities, and other institutions in Ecuador, Peru, and Bolivia. The main breeding method used in the Andes to improve local landraces has been mass selection to adapt lines to specific environments. At least 25 cultivars or ecotypes have been selected and released over the last 40 years using this breeding system. Nevertheless, breeders are currently struggling to develop new varieties that are high yielding, suitable for mechanized harvesting, have a low content of alkaloids or other anti-nutritional properties, and resistant to anthracnose (Colletotrichum acutatum). Therefore, it is necessary to reassess the potential of this crop and invest in its research to incorporate new techniques and breeding strategies to optimize the development of new varieties in the Andes which address the current cultivation challenges of the species.

Agricultural eco-efficiency and water footprint- A case study of fifteen crops in the Chupaca province of Peru

The water footprint is an indicator of the impact of water use from its formation to its final destination. Agricultural eco-efficiency measures the efficient use of resources or materials available for crop production. Water's economic productivity analyses a product's efficient value as per its water supply and commercial value. The present research aimed to determine and relate the water footprint, economic productivity of water and agricultural eco-efficiency of 15 crops in the province of Chupaca - Peru. Georeferencing material was used for the delimitation of agricultural species, CROPWAT 8.0, CLIMWAT8.0, ArcGis 10.5 software, mathematical equations for the water footprint, agricultural eco-efficiency (Data Envelopment Analysis (DEA)) and economic productivity of water. The Total water footprint (TWF) of the fifteen crops was 1718237.01 m3/ton, likewise the BlueWF > GreenWF > GreyWF. In their economic outputs, gross value of production (GVP) > agricultural production (Ag-p) > economic rent agricultural (ERA) was verified. In environmental costs, water consumption that meets the needs of crops (Wc-Ag) > consumption of phytosanitary products (C-fly) > fertilizer consumption (C-fe) was determined. The average Agricultural eco-efficiency (Ag-Eec) and Economic water productivity (Ewp) were 89.8% and 0.046 PEN/m3 respectively. Statistical analysis between Ewp and Ag-Eec was rho = 0.18, t-test = 0.66 < 2.16 (α = 0.05; bilateral), and the correlation indicated that both activities are independent. The environmental costs and economic outputs of agricultural eco-efficiency did not influence the economic value of water.

Imputation strategies for genomic prediction using nanopore sequencing

BackgroundGenomic prediction describes the use of SNP genotypes to predict complex traits and has been widely applied in humans and agricultural species. Genotyping-by-sequencing, a method which uses low-coverage sequence data paired with genotype imputation, is becoming an increasingly popular SNP genotyping method for genomic prediction. The development of Oxford Nanopore Technologies’ (ONT) MinION sequencer has now made genotyping-by-sequencing portable and rapid. Here we evaluate the speed and accuracy of genomic predictions using low-coverage ONT sequence data in a population of cattle using four imputation approaches. We also investigate the effect of SNP reference panel size on imputation performance.ResultsSNP array genotypes and ONT sequence data for 62 beef heifers were used to calculate genomic estimated breeding values (GEBVs) from 641 k SNP for four traits. GEBV accuracy was much higher when genome-wide flanking SNP from sequence data were used to help impute the 641 k panel used for genomic predictions. Using the imputation package QUILT, correlations between ONT and low-density SNP array genomic breeding values were greater than 0.91 and up to 0.97 for sequencing coverages as low as 0.1 × using a reference panel of 48 million SNP. Imputation time was significantly reduced by decreasing the number of flanking sequence SNP used in imputation for all methods. When compared to high-density SNP arrays, genotyping accuracy and genomic breeding value correlations at 0.5 × coverage were also found to be higher than those imputed from low-density arrays.ConclusionsHere we demonstrated accurate genomic prediction is possible with ONT sequence data from sequencing coverages as low as 0.1 × , and imputation time can be as short as 10 min per sample. We also demonstrate that in this population, genotyping-by-sequencing at 0.1 × coverage can be more accurate than imputation from low-density SNP arrays.

Tolerance of Brazilian Bean Cultivars to S-Metolachlor and Poaceae Weed Control in Two Agricultural Soils

Brazil stands out in the world for being one of the largest producers and consumers of common beans and cowpeas. However, the cultivation of this agricultural species is exposed to competition with weeds for water, light and nutrients. One of the management methods for weed control is the use of pre-emergent herbicides. Although pre-emergence herbicides are beneficial in controlling weeds, it is important to know the dynamics of these products in the soil, especially their residual effect. Two experiments were carried out to assess the tolerance of bean genotypes to the pre-emergent herbicide S-metolachlor in two Brazilian soils. Bean genotypes have differential tolerance to S-metolachlor when grown in soils with different characteristics. The Vigna spp. were the most affected by S-metolachlor, especially the red Adzuki. Plant growth was more sensitive when grown in sandy soil for most species. Total chlorophyll content was not affected for most genotypes in the two soils evaluated. The differential tolerance of the genotypes in both soils confirms the potential of S-metolachlor to cause damage to the bean crop, especially in sandy soil. The S-metolachlor was efficient in controlling sourgrass and selective to the bean cultivars (Pérola and Talismã) in both soils evaluated. Alexandergrass behaved differently in the soils evaluated, showing tolerance to the application of S-metolachlor when in Oxisol and sensitivity in Ultisol.