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Plant pathogens can decimate crops and render the local cultivation of a species unprofitable. In extreme cases this has caused famine and economic collapse. Timing is vital in treating crop diseases, and the use of computer vision for precise disease detection and timing of pesticide application is gaining popularity. Computer vision can reduce labour costs, prevent misdiagnosis of disease, and prevent misapplication of pesticides. Pesticide misapplication is both financially costly and can exacerbate pesticide resistance and pollution. Here, we review the application and development of computer vision and machine learning methods for the detection of plant disease. This review goes beyond the scope of previous works to discuss important technical concepts and considerations when applying computer vision to plant pathology. We present new case studies on adapting standard computer vision methods and review techniques for acquiring training data, the use of diagnostic tools from biology, and the inspection of informative features. In addition to an in‐depth discussion of convolutional neural networks (CNNs) and transformers, we also highlight the strengths of methods such as support vector machines and evolved neural networks. We discuss the benefits of carefully curating training data and consider situations where less computationally expensive techniques are advantageous. This includes a comparison of popular model architectures and a guide to their implementation. [ABSTRACT FROM AUTHOR]

SUMMARY: The photosynthetic capacity of mature leaves increases after several days' exposure to constant or intermittent episodes of high light (HL) and is manifested primarily as changes in chloroplast physiology. How this chloroplast‐level acclimation to HL is initiated and controlled is unknown. From expanded Arabidopsis leaves, we determined HL‐dependent changes in transcript abundance of 3844 genes in a 0–6 h time‐series transcriptomics experiment. It was hypothesized that among such genes were those that contribute to the initiation of HL acclimation. By focusing on differentially expressed transcription (co‐)factor genes and applying dynamic statistical modelling to the temporal transcriptomics data, a regulatory network of 47 predominantly photoreceptor‐regulated transcription (co‐)factor genes was inferred. The most connected gene in this network was B‐BOX DOMAIN CONTAINING PROTEIN32 (BBX32). Plants overexpressing BBX32 were strongly impaired in acclimation to HL and displayed perturbed expression of photosynthesis‐associated genes under LL and after exposure to HL. These observations led to demonstrating that as well as regulation of chloroplast‐level acclimation by BBX32, CRYPTOCHROME1, LONG HYPOCOTYL5, CONSTITUTIVELY PHOTOMORPHOGENIC1 and SUPPRESSOR OF PHYA‐105 are important. In addition, the BBX32‐centric gene regulatory network provides a view of the transcriptional control of acclimation in mature leaves distinct from other photoreceptor‐regulated processes, such as seedling photomorphogenesis. Significance Statement: Identifying genes that control plants' intrinsic photosynthetic capacity would provide opportunities for increasing crop productivity. Photosynthetic capacity in mature leaves increases after several days' exposure to episodes of high‐light intensity (HL), which is defined as HL acclimation. Using temporal transcriptomics data and dynamic modelling, we inferred a BBX32‐centric 47‐member Gene Regulatory Network, members of which control, in the first hours of HL exposure, cellular processes that result in enhanced photosynthetic capacity 5 days later. [ABSTRACT FROM AUTHOR]

Summary: Traditional crops have historically provided accessible and affordable nutrition to millions of rural dwellers but have been neglected, with most modern agricultural systems over‐reliant on a small number of internationally traded crops. Traditional crops are typically well‐adapted to local agro‐ecological conditions and many are nutrient‐dense. They can play a vital role in local food systems through enhanced nutrition (particularly where diets are dominated by starch crops), food security and livelihoods for smallholder farmers, and a climate‐resilient and biodiverse agriculture. Using short‐read, long‐read and phased sequencing technologies, we generated a high‐quality chromosome‐level genome assembly for Amaranthuscruentus, an under‐researched crop with micronutrient‐ and protein‐rich leaves and gluten‐free seed, but lacking improved varieties, with respect to productivity and quality traits. The 370.9 Mb genome demonstrates a shared whole genome duplication with a related species, Amaranthushypochondriacus. Comparative genome analysis indicates chromosomal loss and fusion events following genome duplication that are common to both species, as well as fission of chromosome 2 in A. cruentus alone, giving rise to a haploid chromosome number of 17 (versus 16 in A. hypochondriacus). Genomic features potentially underlying the nutritional value of this crop include two A. cruentus‐specific genes with a likely role in phytic acid synthesis (an anti‐nutrient), expansion of ion transporter gene families, and identification of biosynthetic gene clusters conserved within the amaranth lineage. The A. cruentus genome assembly will underpin much‐needed research and global breeding efforts to develop improved varieties for economically viable cultivation and realization of the benefits to global nutrition security and agrobiodiversity. [ABSTRACT FROM AUTHOR]

• Describes impact of Maf1 depletion by RNAi and mutagenesis in Arabidopsis. • Selective increases in expression of specific tRNAs on Maf1 depletion. • Significantly enhanced plant growth after Maf1 depletion. • No evidence of increased vulnerability to a common pathogen. • Growth enhancement by Maf1 depletion retained during drought and salt stress. Maf1 is a transcription factor that is conserved in sequence and structure between yeasts, animals and plants. Its principal molecular function is also well conserved, being to bind and repress RNA polymerase (pol) III, thereby inhibiting synthesis of tRNAs and other noncoding RNAs. Restrictions on tRNA production and hence protein synthesis can provide a mechanism to preserve resources under conditions that are suboptimal for growth. Accordingly, Maf1 is found in some organisms to influence growth and/or stress survival. Because of their sessile nature, plants are especially vulnerable to environmental changes and molecular adaptations that enhance growth under benign circumstances can increase sensitivity to external challenges. We tested if Maf1 depletion in the model plant Arabidopsis affects growth, pathogen resistance and tolerance of drought or soil salinity, a common physiological challenge that imposes both osmotic and ionic stress. We find that disruption of the Maf1 gene or RNAi-mediated depletion of its transcript is well-tolerated and confers a modest growth advantage without compromising resistance to common biotic and abiotic challenges. [ABSTRACT FROM AUTHOR]