Getting into the Weeds of Citrus HLB

Mar 10, 2022

By Ben Faber

New ‘Candidatus Liberibacter' Pathosystems Focus Issue from APS (American Phytopathological Society)

Read the great review of the bacteria that causes Citrus Huanglongbing and then the abstracts of the articles in this edition of Phytopathology. The review itself is pretty comprehensive, however you can't read the full articles contained in the editon without paying. But this gives you an idea of the extent of work being done, even though the language may be quite technical. The 18 articles in this Phytopathology Focus Issue showcase the enormous research efforts made by the scientific community, giving rise to major advances and achievements in a short time often through multidisciplinary approaches applied to the bacterium, psyllid vector, and plant host. Preview two editors' pick below or see the full Focus Issue.

Transcriptome Profiling of ‘Candidatus Liberibacter asiaticus' in Citrus and Psyllids

De Francesco et al. used an elegant bacterial cell enrichment procedure that enables the most comprehensive expression profile of ‘Candidatus Liberibacter asiaticus' that is yet to be cultured. The authors also identified 106 differentially expressed genes in citrus versus Asian citrus psyllids. This study sheds light on our understanding of ‘Candidatus Liberibacter asiaticus' biology.

Linking Climate Variables to Large-Scale Spatial Pattern and Risk of Citrus Huanglongbing: A Hierarchical Bayesian Modeling Approach

Alves et al. explored Huanglongbing (HLB) presence and absence over 13 years in citrus orchards in Brazil and compared two hierarchical Bayesian modeling approaches to link climatic factors to the spatial distribution of HLB prevalence. They found an inverse relationship between HLB prevalence and mean temperature during the dry season, but wind speed, rainfall, and proximity of other HLB contributed to HLB prevalence. The results further our understanding of environmental factors associated with disease distribution and spread and assists policymakers in defining regions at risk of HLB outbreaks to help guide monitoring strategies that mitigate further spread of HLB.

Source : ucanr.edu

Video: Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Plant breeding has long been shaped by snapshots. A walk through a plot. A single set of notes. A yield check at the end of the season. But crops do not grow in moments. They change every day.

In this conversation, Gary Nijak of AerialPLOT explains how continuous crop modeling is changing the way breeders see, measure, and select plants by capturing growth, stress, and recovery across the entire season, not just at isolated points in time.

Nijak breaks down why point-in-time observations can miss critical performance signals, how repeated, season-long data collection removes the human bottleneck in breeding, and what becomes possible when every plot is treated as a living data set. He also explores how continuous modeling allows breeding programs to move beyond vague descriptors and toward measurable, repeatable insights that connect directly to on-farm outcomes.

This conversation explores:

• What continuous crop modeling is and how it works

• Why traditional field observations fall short over a full growing season

• How scale and repeated measurement change breeding decisions

• What “digital twins” of plots mean for selection and performance

• Why data, not hardware, is driving the next shift in breeding innovation As data-driven breeding moves from research into real-world programs, this discussion offers a clear look at how seeing the whole season is reshaping value for breeders, seed companies, and farmers, and why this may be only the beginning.