Evaluation of Broadcast Steam Application with Mustard Seed Meal in Fruiting Strawberry

Soil disinfestation with steam has potential to partially replace fumigants such as methyl bromide, chloropicrin, and 1,3-dichloropropene because it is effective, safer to apply, and has less negative impact on the environment. Here, we compared the efficacy of steam and steam + mustard seed meal (MSM) to chloropicrin on soil disinfection, plant growth, and fruit yield in a strawberry (Fragaria ×ananassa) fruiting field. The MSM was applied at 3368 kg·ha−1 before the steam application. Steam was injected into a 3-m-wide reverse tiller that was set to till 30 to 40 cm deep. Soil temperatures at depths of 10, 20, 25, and 35 cm were monitored. Steam and steam + MSM treatments reduced the viability of purslane seeds and nutsedge tubers, microsclerotia density of Verticillium dahliae, propagule density of Pythium ultimum, cumulative weed densities, and biomass compared with the nontreated control. Moreover, the steam application was as efficacious as chloropicrin on these pests. The growth and fruit yield of strawberries grown on soils previously treated with the steam and steam + MSM treatments were similar to those in the chloropicrin treatment and were higher than those in the nontreated control. Our study indicated that steam, steam + MSM, and chloropicrin are equally effective at suppressing weeds and soilborne pathogens. These results suggest that the steam and steam + MSM treatment can be a practical alternative for soil disinfestation in conventional and organic strawberry fields

An Image Segmentation Technique with Statistical Strategies for Pesticide Efficacy Assessment

Image analysis is a useful technique to evaluate the efficacy of a treatment for weed control. In this study, we address two practical challenges in the image analysis. First, it is challenging to accurately quantify the efficacy of a treatment when an entire experimental unit is not affected by the treatment. Second, RGB codes, which can be used to identify weed growth in the image analysis, may not be stable due to various surrounding factors, human errors, and unknown reasons. To address the former challenge, the technique of image segmentation is considered. To address the latter challenge, the proportion of weed area is adjusted under a beta regression model. The beta regression is a useful statistical method when the outcome variable (proportion) ranges between zero and one. In this study, we attempt to accurately evaluate the efficacy of a 35% hydrogen peroxide (HP). The image segmentation was applied to separate two zones, where the HP was directly applied (gray zone) and its surroundings (nongray zone). The weed growth was monitored for five days after the treatment, and the beta regression was implemented to compare the weed growth between the gray zone and the control group and between the nongray zone and the control group. The estimated treatment effect was substantially different after the implementation of image segmentation and the adjustment of green area

A Dicationic Calix 4 Pyrrole Derivative and Its Use for the Selective Recognition and Displacement-Based Sensing of Pyrophosphate

A new bis-pyridinium calix[4] pyrrole derivative is reported. This system forms a non-fluorescent complex upon exposure to the chromenolate anion. The resulting supramolecular ensemble binds the pyrophosphate anion with high affinity (K-a (2.55 +/- 0.12) x 10(7) M-1) in acetonitrile. It exhibits sensitive "turn-on" fluorescence when exposed to tetrabutylammonium pyrophosphate, and does so in preference to other anions, including the fluoride and phosphate anions.NRF 2009-0087013BK21 programNational Science Foundation NSF CHE-1057904Chemistr

Applications of Statistical Experimental Designs to Improve Statistical Inference in Weed Management

In a balanced design, researchers allocate the same number of units across all treatment groups. It has been believed as a rule of thumb among some researchers in agriculture. Sometimes, an unbalanced design outperforms a balanced design. Given a specific parameter of interest, researchers can design an experiment by unevenly distributing experimental units to increase statistical information about the parameter of interest. An additional way of improving an experiment is an adaptive design (e.g., spending the total sample size in multiple steps). It is helpful to have some knowledge about the parameter of interest to design an experiment. In the initial phase of an experiment, a researcher may spend a portion of the total sample size to learn about the parameter of interest. In the later phase, the remaining portion of the sample size can be distributed in order to gain more information about the parameter of interest. Though such ideas have existed in statistical literature, they have not been applied broadly in agricultural studies. In this article, we used simulations to demonstrate the superiority of the experimental designs over the balanced designs under three practical situations: comparing two groups, studying a dose-response relationship with right-censored data, and studying a synergetic effect of two treatments. The simulations showed that an objective-specific design provides smaller error in parameter estimation and higher statistical power in hypothesis testing when compared to a balanced design. We also conducted an adaptive experimental design applied to a dose-response study with right-censored data to quantify the effect of ethanol on weed control. Retrospective simulations supported the benefit of this adaptive design as well. All researchers face different practical situations, and appropriate experimental designs will help utilize available resources efficiently

ShinyCore: An R/Shiny program for establishing core collection based on single nucleotide polymorphism data

Background: Managing and investigating all available genetic resources are challenging. As an alternative, breeders and researchers use core collection—a representative subset of the entire collection. A good core is characterized by high genetic diversity and low repetitiveness. Among the several available software, GenoCore uses a coverage criterion that does not require computationally expensive distance-based metrics. Results: ShinyCore is a new method to select a core collection through two phases. The first phase uses the coverage criterion to quickly attain a fixed coverage, and the second phase uses a newly devised score (referred to as the rarity score) to further enhance diversity. It can attain a fixed coverage faster than a currently available algorithm devised for the coverage criterion, so it will benefit users who have big data. ShinyCore attains the minimum coverage specified by a user faster than GenoCore, and it then seeks to add entries with the rarest allele for each marker. Therefore, measures of genetic diversity and distance can be improved. Conclusion: Although GenoCore is a fast algorithm, its implementation is difficult for those unfamiliar with R, ShinyCore can be easily implemented in Shiny with RStudio and an interactive web applet is available for those who are not familiar with programming languages

Incorporating Statistical Strategy into Image Analysis to Estimate Effects of Steam and Allyl Isocyanate on Weed Control

Weeds are the major limitation to efficient crop production, and effective weed management is necessary to prevent yield losses due to crop-weed competition. Assessments of the relative efficacy of weed control treatments by traditional counting methods is labor intensive and expensive. More efficient methods are needed for weed control assessments. There is extensive literature on advanced techniques of image analysis for weed recognition, identification, classification, and leaf area, but there is limited information on statistical methods for hypothesis testing when data are obtained by image analysis (RGB decimal code). A traditional multiple comparison test, such as the Dunnett-Tukey-Kramer (DTK) test, is not an optimal statistical strategy for the image analysis because it does not fully utilize information contained in RGB decimal code. In this article, a bootstrap method and a Poisson model are considered to incorporate RGB decimal codes and pixels for comparing multiple treatments on weed control. These statistical methods can also estimate interpretable parameters such as the relative proportion of weed coverage and weed densities. The simulation studies showed that the bootstrap method and the Poisson model are more powerful than the DTK test for a fixed significance level. Using these statistical methods, three soil disinfestation treatments, steam, allyl-isothiocyanate (AITC), and control, were compared. Steam was found to be significantly more effective than AITC, a difference which could not be detected by the DTK test. Our study demonstrates that an appropriate statistical method can leverage statistical power even with a simple RGB index

FOOT ARCH STRAIN OF EXCESSIVE PRONATORS DURING TWO-LEGS AND ONELEG STANDING AND WALKING

INTRODUCTION: The movement of plantar fascia under the foot has been characterized by foot arch strain in vitro (Kogler, Solomonidis, & Paul, 1995). The characteristics of the foot arch strain under the static and dynamic conditions in excessive pronators are not well known. Therefore, the purpose of this study is to investigate the foot arch strain during two legs, one-leg standing and walking in excessive pronation

Evaluation of a Steam Application by a Mobile Applicator for Soil Disinfestation in Strawberry Nurseries

Soil disinfestation with steam has been evaluated in strawberry fruiting fields as a nonchemical method of soil disinfestation; however, little is known about the use of steam for field production of strawberry daughter plants. The objective of this study was to compare daughter plant production in soils previously treated with steam compared to those treated with standard methyl bromide (MB) and chloropicrin (Pic) treatments. A prototype field steam applicator and a self-propelled diesel-fueled steam generator and applicator were tested at two high-elevation nurseries near Macdoel, CA, in Sept. 2018 and Aug. 2020, respectively. The steam application heated the soil above 60 °C for ≈60 minutes to a depth of 25 cm at both nurseries. The pest control efficacy of the steam applications against weeds, Verticillium spp., Tylenchulus semipenetrans, and Pythium ultimum were similar to that of MB:Pic. The stolons and daughter plants densities in fields with steam treatment were similar to those in fields with MB:Pic treatment. Therefore, we suggest that soil disinfestation with steam may be a viable method of producing healthy strawberry plants. However, more research is needed to verify plant sanitation and quality

Prediction of strawberry yield based on receptacle detection and Bayesian inference

The receptacle of strawberry is a more direct part than the flower for predicting yield as they eventually become fruits. Thus, we tried to predict the yield by combining an AI technique for receptacle detection in images and statistical analysis on the relationship between the number of receptacles detected and the strawberry yield over a period of time. Five major cultivars were cultivated to consider the cultivar characteristics and environmental factors for two years were collected to consider the climate difference. Faster R–CNN based object detector was used to estimate the number of receptacles per strawberry plant in given two-dimensional images, which achieved a mAP of 0.6587 for our dataset. However, not all receptacles appear on the two-dimensional images, and Bayesian analysis was used to model the uncertainty associated with the number of receptacles missed by the AI. After estimating the probability of fruiting per receptacle, prediction models for the total strawberry yield at the end of harvest season were evaluated. Even though the detection accuracy was not perfect, the results indicated that counting the receptacles by object detection and estimating the probability of fruiting per receptacle by Bayesian modeling are more useful for predicting the total yield per plant than knowing its cumulative yield during the first month

Time reduction effect of the enhanced TACT method for high-rise residential buildings

The finish work on high-rise residential buildings is performed simultaneously with mechanical and electrical construction work, which results in frequent work interference and delay. This significantly hinders efficient schedule management. Critical Path Method (CPM) is inefficient when applied to high-rise residential building projects in which work is repeatedly carried out for each floor. Line-of-Balance (LOB) is widely used for its effectiveness in managing repetitive work. LOB was developed into TACT and eTACT (enhanced-TACT) to combine heterogeneous works con­tinuously. In particular, the eTACT schedule management method has an advantage in that it is capable of systemati­cally connecting detailed construction, mechanical and electrical construction projects using a work planning template. This study evaluates the time reduction effect of the eTACT method for a high-rise residential building. A comparative analysis of data on 102 cases of non-applied projects and 44 cases of projects using the eTACT method over a period of 10 years is presented to verify its effectiveness. The result shows that finish work time was reduced by 25% or about 53 days on average. First published online: 18 Dec 201