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G protein α subunit suppresses sporangium formation through a serine/threonine protein kinase in Phytophthora sojae
Get PDFEukaryotic heterotrimeric guanine nucleotide-binding proteins consist of α, β, and γ subunits, which act as molecular switches to regulate a number of fundamental cellular processes. In the oomycete pathogen Phytophthora sojae, the sole G protein α subunit (Gα; encoded by PsGPA1) has been found to be involved in zoospore mobility and virulence, but how it functions remains unclear. In this study, we show that the Gα subunit PsGPA1 directly interacts with PsYPK1, a serine/threonine protein kinase that consists of an N-terminal region with unknown function and a C-terminal region with a conserved catalytic kinase domain. We generated knockout and knockout-complemented strains of PsYPK1 and found that deletion of PsYPK1 resulted in a pronounced reduction in the production of sporangia and oospores, in mycelial growth on nutrient poor medium, and in virulence. PsYPK1 exhibits a cytoplasmic-nuclear localization pattern that is essential for sporangium formation and virulence of P. sojae. Interestingly, PsGPA1 overexpression was found to prevent nuclear localization of PsYPK1 by exclusively binding to the N-terminal region of PsYPK1, therefore accounting for its negative role in sporangium formation. Our data demonstrate that PsGPA1 negatively regulates sporangium formation by repressing the nuclear localization of its downstream kinase PsYPK1.</p
Exploring the boundaries of the passive greenhouse in Jordan: A modelling approach
No full textGreenhouses are expanding fast in arid and semi-arid regions, among other reasons, because of the water savings that can be realized compared to open field cultivation. However, it is difficult for growers to recognize the optimum greenhouse design. Many competing aspects must be weighed against each other such as the structure, the cover and the climate control equipment. Obviously, the optimum design must be tailored for each specific crop and growing cycle and availability of resources (land, water, energy, labor, etc.). Simulation models can assist in this process, saving time and money. Wageningen University & Research, BU Greenhouse Horticulture has developed the Adaptive Greenhouse Methodology. It combines the use of greenhouse climate and resources simulation models, with crop growth and economic models, to solve the problem of designing the optimum greenhouse for each specific scenario in the world. In the present work we present the results of the application of this methodology to the specific case of the production of greenhouse soilless tomato in two regions in Jordan in the mid tech range: the highlands and the Jordan Valley. Results show that different mid tech designs could potentially provide yield levels of up to 35 and 27 kg m-2 in the Highlands and the Jordan Valley, respectively. The final design is similar in the two locations.</p
Dataset on proteomic changes of whey protein after different heat treatment
Get PDFHereby we provide data from a shot-gun proteomics experiment, using filtered-aided sample preparation (FASP), and liquid chromatography with tandem mass spectrometry (LC-MS/MS), to relatively quantify the changes in the protein profile of whey proteins after heating milk at either 65 °C, 70 °C, 75 °C, 80 °C, or 85 °C for 30 min. The data supplied in this article supports the accompanying publication [1]. The raw mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier “PXD016436”.</p
Farmer cooperation in agro-clusters: Evidence from Indonesia
No full textCollective action in geographically concentrated farming regions can lead to improvements in farmer income. We model farmer cooperation inside such agro-clusters as a two-stage decision process. From 1,151 completely filled-in questionnaires, we find that being located in an agro-cluster increases farmers' likelihood to cooperate as well as enhances their income. Farmers' attitude towards cooperation is positively influenced by being male, having more assets, and operating a larger farm, but negatively affected if the farmer reports that her household is food vulnerable. The number of hours worked by farmers on the farm and the frequency of face-to-face meetings also raise the probability of engaging in cooperation. A higher density of agro-clusters, higher crop diversity and being located farther away from urban centers are found to increase on average the income level of a farmer. Hence, the promotion of agro-clusters also in rural regions remains a promising initiative for increasing farmer income
Automated Processing of Sentinel-2 Products for Time-Series Analysis in Grassland Monitoring
No full textEffective grassland management practices require a good understanding of soil and vegetation properties, that can be quantified by farmers’ knowledge and remote sensing techniques. Many systems have been proposed in the past for grassland monitoring, but open-source alternatives are increasingly being preferred. In this paper, a system is proposed to process data in an open-source and automated way. This system made use of Sentinel-2 data to support grassland management at Haus Riswick in the region around Kleve, Germany, retrieved with help of a platform called Sentinelsat that was developed by ESA. Consecutive processing steps consisted of atmospheric correction, cloud masking, clipping the raster data, and calculation of vegetation indices. First results from 2018 resembled the mowing regime of the area with four growing cycles, although outliers were detected due to a lack of data caused by cloud cover. Moreover, that year’s extremely dry summer was visible in the time-series pattern as well. The proposed script is a primary version of a processing chain, which is suitable to be further expanded for more advanced data pre-processing and data analysis in the future
Evolution of IFN subgroups in bony fish - 2. analysis of subgroup appearance and expansion in teleost fish with a focus on salmonids
No full textA relatively large repertoire of type I interferon (IFN) genes is apparent in rainbow trout/Atlantic salmon, that includes six different IFN subgroups (IFNa-IFNf) belonging to the three known type I IFN groups (1–3) in bony fish. Whether this is true for other salmonids, and how the various type I subgroups evolved in teleost fish was studied using the extensive genomic resources available for fish. This confirmed that salmonids, at least the Salmoninae, indeed have a complex (in terms of IFN subgroups present) and large (number of genes) IFN repertoire relative to other teleost fish. This is in part a consequence of the salmonid 4 R WGD that duplicated the growth hormone (GH) locus in which type I IFNs are generally located. Divergence of the IFN genes at the two GH loci was apparent but was not seen in common carp, a species that also underwent an independent 4 R WGD. However, expansion of IFN gene number can be found at the CD79b locus of some perciform fish (both freshwater and marine), with expansion of the IFNd gene repertoire. Curiously the primordial gene order of GH-IFNc-IFNb-IFNa-IFNe is largely retained in many teleost lineages and likely reflects the tandem duplications that are taking place to increase IFN gene number. With respect to the evolution of the IFN subgroups, a complex acquisition and/or loss has occurred in different teleost lineages, with complete loss of IFN genes at the GH or CD79b locus in some species, and reduction to a single IFN subgroup in others. It becomes clear that there are many variations to be discovered regarding the mechanisms by which fish elicit protective (antiviral) immune responses.</p
The fate of (compostable) plastic products in a full scale industrial organic waste treatment facility
Get PDFEstimation of tomato yield gaps for greenhouse in Uruguay
No full textYield gap analysis is a powerful method to explore gap’s breadth between potential yields, attainable and those realized in farmers’ fields, identifying constraints to production and assess opportunities to yield increase. We assessed yields and yield components across two seasons, in 110 greenhouse tomato (Solanum lycopersicum) crops during 2014/15 and 2015/16 in the south region of Uruguay, and compared them with potential and attainable yield. Potential yield was calculated with a simulation model based on photosynthetic active radiation (PAR) and light use efficiency, and TOMSIM to estimate assimilate partition and fruit yield. Since yield was primarily determined by cumulative PAR intercepted, a boundary function was fitted to estimate attainable yield as a function of cumulative PAR intercepted. Our study quantified a yield gap of 10.7 kg m−2 or 44 % relative to potential. Overall gap was divided into three components: difference between actual and attainable (45 % of total gap), attainable and potential with actual greenhouse PAR transmissivity (29 % of total gap) and between potential with actual transmissivity and potential with 70 % of greenhouse transmissivity (26 % of total gap). For long summer and short spring/summer crops the greatest impact in yield could be obtained by increasing leaf area index by reducing plant lowering operations and leaf pruning intensity, and by increasing plant density. For autumn crops, yield could be improved by earlier planting, reducing leaf pruning intensity after harvest beginning, and increasing greenhouse transmissivity by more frequent plastic cover renewal and removing roofs’ shading screens and whitenin
Modelling root water uptake under deficit irrigation and rewetting in Northwest China
No full textThe spatial and temporal distribution of root water uptake (RWU) under deficit irrigation are critical factors for crop growth. The SWAP (soil–water–atmosphere–plant) model was applied to analyze the pattern of RWU for winter wheat (Triticum aestivum L.) under three irrigation levels: no water deficit (100% evapotranspiration [ET]), moderate water deficit (80% ET) and severe water deficit (60% ET). The 2–yr experiments indicated that SWAP was highly accurate (mean relative error [MRE] 3 cm−3) in simulating the soil water content (SWC). Root water uptake was significantly (P 3 cm−3 d−1. The critical SWC was 67.9% of the field capacity, when the RWU dropped to 95% of the control treatment. After rewetting, compensation and hysteresis effects on RWU were observed. The ranking of RWU recovery ability after rewetting was: emergence to jointing > jointing to heading > grain filling to maturity > heading to grain filling. Recovery time of RWU was 2 to 11 d and gradually increased with growth stage. The simplified RWU model established using path analysis and regression performed well (R2 = 0.836; P < 0.01) for RWU. This provided a more convenient way to accurately estimate RWU with fewer variables.</p