Prediction of leaf wetness duration using a fuzzy logic system

Models have been developed to estimate leaf wetness duration (LWD) using measured or estimated weather data on the basis of approaches such as energy balance equations, neural networks, and classification and regression trees (CART). Models that embody physical principles ensure spatial portability but usually require accurate and extensive input data to estimate LWD accurately. Empirical models may be more tolerant to errors of input data and require more limited weather inputs, but they rarely possess wide portability because they do not incorporate physical principles. In this study, a hybrid model was developed to incorporate both energy balance principles and empirical approaches by using fuzzy logic. The results suggested that a LWD model based on a fuzzy logic system offers advantages in comparison to the previous models since the model possessed wider portability than strictly empirical models. Empirical methodologies included in the model algorithm allowed a relatively small number of input variables and tolerated imprecise weather data input. The fuzzy LWD model also possessed adaptability to specific circumstances using a correction factor, which can be determined through a simple training process. For example, when LWD was predicted with site-specific weather forecasts in which substantial systematic errors are contained, the fuzzy LWD model was able to forecast LWD accurately using a correction factor. The correction factor also expanded spatial portability of the fuzzy LWD model to environments in which climate conditions differed considerably, e.g., from temperate to tropical zones. The fuzzy LWD model, therefore, deserves further attention as a substitute for current physical and empirical LWD models

Deep Eutectic Solvent Pretreatment of Transgenic Biomass With Increased C6C1 Lignin Monomers.

The complex and heterogeneous polyphenolic structure of lignin confers recalcitrance to plant cell walls and challenges biomass processing for agroindustrial applications. Recently, significant efforts have been made to alter lignin composition to overcome its inherent intractability. In this work, to overcome technical difficulties related to biomass recalcitrance, we report an integrated strategy combining biomass genetic engineering with a pretreatment using a bio-derived deep eutectic solvent (DES). In particular, we employed biomass from an Arabidopsis line that expressed a bacterial hydroxycinnamoyl-CoA hydratase-lyase (HCHL) in lignifying tissues, which results in the accumulation of unusual C6C1 lignin monomers and a slight decrease in lignin molecular weight. The transgenic biomass was pretreated with renewable DES that can be synthesized from lignin-derived phenols. Biomass from the HCHL plant line containing C6C1 monomers showed increased pretreatment efficiency and released more fermentable sugars up to 34% compared to WT biomass. The enhanced biomass saccharification of the HCHL line is likely due to a reduction of lignin recalcitrance caused by the overproduction of C6C1 aromatics that act as degree of polymerization (DP) reducers and higher chemical reactivity of lignin structures with such C6C1 aromatics. Overall, our findings demonstrate that strategic plant genetic engineering, along with renewable DES pretreatment, could enable the development of sustainable biorefinery

How to read spore forecasting maps

In the coming season, forecasting or modeling of rust spore movement has been proposed to provide producers with a tool for rust management. There is a possibility of spore maps being used to guide our scouts if the model is implemented. This article addresses two related aspects: (1) how soybean rust spreads from southern overwintering regions to northern soybean production regions; (2) how to read spore forecasting maps that will be posted on the Web to help us scout soybean rust during the coming growing season

High-Throughput Screening of Acyl-CoA Thioesterase I Mutants Using a Fluid Array Platform

Screening target microorganisms from a mutated recombinant library plays a crucial role in advancing synthetic biology and metabolic engineering. However, conventional screening tools have several limitations regarding throughput, cost, and labor. Here, we used the fluid array platform to conduct high-throughput screening (HTS) that identified Escherichia coli ???TesA thioesterase mutants producing elevated yields of free fatty acids (FFAs) from a large (106) mutant library. A growth-based screening method using a TetA-RFP fusion sensing mechanism and a reporter-based screening method using high-level FFA producing mutants were employed to identify these mutants via HTS. The platform was able to cover >95% of the mutation library, and it screened target cells from many arrays of the fluid array platform so that a post-analysis could be conducted by gas chromatography. The ???TesA mutation of each isolated mutant showing improved FFA production in E. coli was characterized, and its enhanced FFA production capability was confirmed

Extracting Concrete Thermal Characteristics from Temperature Time History of RC Column Exposed to Standard Fire

A numerical method to identify thermal conductivity from time history of one-dimensional temperature variations in thermal unsteady-state is proposed. The numerical method considers the change of specific heat and thermal conductivity with respect to temperature. Fire test of reinforced concrete (RC) columns was conducted using a standard fire to obtain time history of temperature variations in the column section. A thermal equilibrium model in unsteady-state condition was developed. The thermal conductivity of concrete was then determined by optimizing the numerical solution of the model to meet the observed time history of temperature variations. The determined thermal conductivity with respect to temperature was then verified against standard thermal conductivity measurements of concrete bricks. It is concluded that the proposed method can be used to conservatively estimate thermal conductivity of concrete for design purpose. Finally, the thermal radiation properties of concrete for the RC column were estimated from the thermal equilibrium at the surface of the column. The radiant heat transfer ratio of concrete representing absorptivity to emissivity ratio of concrete during fire was evaluated and is suggested as a concrete criterion that can be used in fire safety assessment

Altered expression of norepinephrine transporter and norepinephrine in human placenta cause pre-eclampsia through regulated trophoblast invasion

Objective: We investigated the norepinephrine transporter (NET) expression in normal and pre-eclamptic placentas and analyzed the invasion activity of trophoblastic cells based on norepinephrine (NE)-NET regulation. Methods: NET and NE expression levels were examined by western blot and enzyme-linked immunosorbent assay, respectively. Trophoblast invasion activity, depending on NE-NET regulation, was determined by NET-small interfering RNA (siRNA) and NET transfection into the human extravillous trophoblast cells with or without NE treatment and invasion rates were analyzed by zymography and an invasion assay. Results: NET mRNA was expressed at a low level in pre-eclamptic placentas compared with normal placentas and NE concentration in maternal plasma increased significantly in pre-eclamptic women compared to normal pregnant women (p<0.05). NET gene upregulation and NE treatment stimulated trophoblast cell invasion up to 2.5-fold (p<0.05) by stimulating matrix metalloproteinase-9 activity via the phosphoinositol-3-kinase/AKT signaling pathway, whereas NET-siRNA with NE treatment reduced invasion rates. Conclusion: NET expression is reduced by inadequate regulation of NE levels during placental development. This suggests that a complementary balance between NET and NE regulates trophoblast cell invasion activities during placental development