Using Brainwave Patterns Recorded from Plant Pathology Experts to Increase the Reliability of AI-Based Plant Disease Recognition System.

One of the most challenging problems associated with the development of accurate and reliable application of computer vision and artificial intelligence in agriculture is that, not only are massive amounts of training data usually required, but also, in most cases, the images have to be properly labeled before models can be trained. Such a labeling process tends to be time consuming, tiresome, and expensive, often making the creation of large labeled datasets impractical. This problem is largely associated with the many steps involved in the labeling process, requiring the human expert rater to perform different cognitive and motor tasks in order to correctly label each image, thus diverting brain resources that should be focused on pattern recognition itself.

Are economic thresholds for IPM decisions the same for low LAI soybean cultivars in Brazil?

Background: Economic thresholds (ETs) are well-established for defoliation of soybean, Glycine max, and have been updated for many of the newer cultivars; however, there is increasing grower adoption of cultivars with a reduced leaf area index (LAI). It is of theoretical and practical interest to determine low LAI cultivar tolerance to defoliation. We conducted experiments during two consecutive crop seasons (2017/2018 and 2018/2019) using three soybean cultivars (NS 5959 IPRO, NS 5445 IPRO, and DON MARIO 5.

An updated phylogenetic classification of isolates and a practical approach to their identification based on the nucleotide polymorphisms at the and loci.

(Burk. & M.A.

Performance and Profitability of Fungicides for Managing Soybean White Mold: A 10-Year Summary of Cooperative Trials.

White mold, caused by , is a yield-limiting disease of soybean in Brazil. Uniform fungicide trials have been conducted annually since 2009. Data from 74 cooperative field trials conducted over a 10-year period were assembled.

Meta-Analytic Modeling of the Decline in Performance of Fungicides for Managing Soybean Rust after a Decade of Use in Brazil.

An apparent decline of fungicide performance for the control of soybean rust in Brazil has been reported but the rate at which it has occurred has not been formally quantified. Control efficacy and yield response to three fungicides applied as single active ingredients (a.i.

The recombinant pea defensin Drr230a is active against impacting soybean and cotton pathogenic fungi from the genera Fusarium, Colletotrichum and Phakopsora.

Plant defensins are antifungal peptides produced by the innate immune system plants developed to circumvent fungal infection. The defensin Drr230a, originally isolated from pea, has been previously shown to be active against various entomopathogenic and phytopathogenic fungi. In the present study, the activity of a yeast-expressed recombinant Drr230a protein (rDrr230a) was tested against impacting soybean and cotton fungi.

Meta-analysis of the relationship between crop yield and soybean rust severity.

Meta-analytic models were used to summarize and assess the heterogeneity in the relationship between soybean yield (Y, kg/ha) and rust severity (S, %) data from uniform fungicide trials (study, k) conducted over nine growing seasons in Brazil. For each selected study, correlation (k=231) and regression (k=210) analysis for the Y-S relationship were conducted and three effect-sizes were obtained from these analysis: Fisher's transformation of the Pearson's correlation coefficient (Zr) and the intercept (β0) and slope (β1) coefficients. These effect-sizes were summarized through random-effect and mixed-effect models, with the latter incorporating study-specific categorical moderators such as disease onset time (DOT) (70%, moderate=>40 and ≤70%, and low=≤40% S the check treatment), and growing season.

A new chitinase-like xylanase inhibitor protein (XIP) from coffee (Coffea arabica) affects Soybean Asian rust (Phakopsora pachyrhizi) spore germination.

Background: Asian rust (Phakopsora pachyrhizi) is a common disease in Brazilian soybean fields and it is difficult to control. To identify a biochemical candidate with potential to combat this disease, a new chitinase-like xylanase inhibitor protein (XIP) from coffee (Coffea arabica) (CaclXIP) leaves was cloned into the pGAPZα-B vector for expression in Pichia pastoris.

Results: A cDNA encoding a chitinase-like xylanase inhibitor protein (XIP) from coffee (Coffea arabica) (CaclXIP), was isolated from leaves.

Distinct biphasic mRNA changes in response to Asian soybean rust infection.

Asian soybean rust (ASR), caused by Phakopsora pachyrhizi, is now established in all major soybean-producing countries. Currently, there is little information about the molecular basis of ASR-soybean interactions, which will be needed to assist future efforts to develop effective resistance. Toward this end, abundance changes of soybean mRNAs were measured over a 7-day ASR infection time course in mock-inoculated and infected leaves of a soybean accession (PI230970) carrying the Rpp2 resistance gene and a susceptible genotype (Embrapa-48).