Machine Learning-Based Plant Detection Algorithms to Automate Counting Tasks Using 3D Canopy Scans

This study tested whether machine learning (ML) methods can effectively separate individual plants from complex 3D canopy laser scans as a prerequisite to analyzing particular plant features. For this, we scanned mung bean and chickpea crops with PlantEye (R) laser scanners. Firstly, we segmented the crop canopies from the background in 3D space using the Region Growing Segmentation algorithm. Then, Convolutional Neural Network (CNN) based ML algorithms were fine-tuned for plant counting. Application of the CNN-based (Convolutional Neural Network) processing architecture was possible only after we reduced the dimensionality of the data to 2D. This allowed for the identification of individual plants and their counting with an accuracy of 93.18% and 92.87% for mung bean and chickpea plants, respectively. These steps were connected to the phenotyping pipeline, which can now replace manual counting operations that are inefficient, costly, and error-prone. The use of CNN in this study was innovatively solved with dimensionality reduction, addition of height information as color, and consequent application of a 2D CNN-based approach. We found there to be a wide gap in the use of ML on 3D information. This gap will have to be addressed, especially for more complex plant feature extractions, which we intend to implement through further research. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Using Growth and Transpiration Phenotyping Under Controlled Conditions to Select Water Efficient Banana Genotypes

Water deficit is one of the world’s major constraints in agriculture and will aggravate in the future. Banana (Musa spp.) is an important crop that needs vast amounts of water for optimal production. The International Transit Center of Bioversity International holds the world’s biggest collection of banana biodiversity (>1,500 accessions). The long-term aim of this research is to evaluate the potential within this collection for climate smart agricultural usage. Therefore, we developed a phenotyping setup under controlled environmental conditions and we selected 32 representatives of the Musa biodiversity (29 cultivars and 3 wild relatives) for evaluation. The best performing genotypes accumulated six to seven times more biomass than the least performing. Eight genotypes (five ABB, one AAB, and two AAA) invest under osmotic stress significantly more in root growth than in leaf growth. We predict therefore that these genotypes have potential for high productivity under rain fed conditions with a short dry season. To gain more insight in the transpiration physiology, we gravimetrically monitored individual plant transpiration over the diurnal period. All analyzed genotypes showed a marked reduction in transpiration rate in the afternoon. Moreover, the timing of this onset, as well as its impact on total transpiration, was genotype dependent. This phenomenon was more pronounced in 13 genotypes (eight ABB, two AAB, two AA, one BB). Banana is a crop originating from the humid tropics and has developed a strong root pressure to maintain an efficient water and nutrient transport even under saturated relative humidity conditions. Therefore, we hypothesize that the diurnal transpiration decline contributes to a higher water use efficiency without compromising the nutrient transport. Of the eight genotypes that had the best growth under osmotic stress, all analyzed ABB cultivars have a lower maximal transpiration rate, keep this maximal transpiration for a shorter time and therefore consume less water per day. We conclude that lab models are very useful to study the biodiversity and to identify different traits that contribute to a better drought tolerance/avoidance. We encourage researchers investigating other crops to start exploring their collections

Practical guidelines for early screening and field evaluation of banana against Fusarium wilt, Pseudocercospora leaf spots and drought

Practical guidelines for the early screening and field evaluation of banana (Musa spp.) for resistance to three major traits: Fusarium wilt (Fusarium oxysporum f. sp. cubense), leaf spot diseases (Pseudocercospora spp.) and drought. The guidelines have been produced by experts from the Evaluation Thematic Group of MusaNet, the global network for Musa genetic resources (www.musanet.org) coordinated by the Alliance of Bioversity and CIAT

Practical guidelines for early screening and field evaluation of banana against Fusarium wilt, Pseudocercospora leaf spots and drought

Practical guidelines for the early screening and field evaluation of banana (Musa spp.) for resistance to three major traits: Fusarium wilt (Fusarium oxysporum f. sp. cubense), leaf spot diseases (Pseudocercospora spp.) and drought. The guidelines have been produced by experts from the Evaluation Thematic Group of MusaNet, the global network for Musa genetic resources (www.musanet.org) coordinated by the Alliance of Bioversity and CIAT

Using Growth and Transpiration Phenotyping Under Controlled Conditions to Select Water Efficient Banana Genotypes

Water deficit is one of the world's major constraints in agriculture and will aggravate in the future. Banana (Musa spp.) is an important crop that needs vast amounts of water for optimal production. The International Transit Center of Bioversity International holds the world's biggest collection of banana biodiversity (>1,500 accessions). The long-term aim of this research is to evaluate the potential within this collection for climate smart agricultural usage. Therefore, we developed a phenotyping setup under controlled environmental conditions and we selected 32 representatives of the Musa biodiversity (29 cultivars and 3 wild relatives) for evaluation. The best performing genotypes accumulated six to seven times more biomass than the least performing. Eight genotypes (five ABB, one AAB, and two AAA) invest under osmotic stress significantly more in root growth than in leaf growth. We predict therefore that these genotypes have potential for high productivity under rain fed conditions with a short dry season. To gain more insight in the transpiration physiology, we gravimetrically monitored individual plant transpiration over the diurnal period. All analyzed genotypes showed a marked reduction in transpiration rate in the afternoon. Moreover, the timing of this onset, as well as its impact on total transpiration, was genotype dependent. This phenomenon was more pronounced in 13 genotypes (eight ABB, two AAB, two AA, one BB). Banana is a crop originating from the humid tropics and has developed a strong root pressure to maintain an efficient water and nutrient transport even under saturated relative humidity conditions. Therefore, we hypothesize that the diurnal transpiration decline contributes to a higher water use efficiency without compromising the nutrient transport. Of the eight genotypes that had the best growth under osmotic stress, all analyzed ABB cultivars have a lower maximal transpiration rate, keep this maximal transpiration for a shorter time and therefore consume less water per day. We conclude that lab models are very useful to study the biodiversity and to identify different traits that contribute to a better drought tolerance/avoidance. We encourage researchers investigating other crops to start exploring their collections.status: publishe

Differential root transcriptomics in a polypoloid non-model crop: the importance of respiration during osmotic stress

To explore the transcriptomic global response to osmotic stress in roots, 18 mRNA-seq libraries were generated from three triploid banana genotypes grown under mild osmotic stress (5% PEG) and control conditions. Illumina sequencing produced 568 million high quality reads, of which 70-84% were mapped to the banana diploid reference genome. Using different uni- and multivariate statistics, 92 genes were commonly identified as differentially expressed in the three genotypes. Using our in house workflow to analyze GO enriched and underlying biochemical pathways, we present the general processes affected by mild osmotic stress in the root and focus subsequently on the most significantly overrepresented classes associated with: respiration, glycolysis and fermentation. We hypothesize that in fast growing and oxygen demanding tissues, mild osmotic stress leads to a lower energy level, which induces a metabolic shift towards (i) a higher oxidative respiration, (ii) alternative respiration and (iii) fermentation. To confirm the mRNA-seq results, a subset of twenty up-regulated transcripts were further analysed by RT-qPCR in an independent experiment at three different time points. The identification and annotation of this set of genes provides a valuable resource to understand the importance of energy sensing during mild osmotic stress.status: publishe

Abiotic stress research in crops using -omics approaches: drought stress and banana in the spotlight

Evaluating crop biodiversity is a challenging task and needs to integrate knowledge from different levels. This overview paper offers ways to tackle this challenge, illustrated by the case for drought tolerance in banana. KU Leuven hosts the International Musa Germplasm Collection managed by Bioversity International for safe storage and distribution in order to secure the crops genepool and encourage its use. The latter, however, requires an in-depth knowledge of the variability among the accessions for coping with varying environmental limitations. Our research focuses on variations in drought tolerance by integrating information from different biological levels (genome, transcriptome, metabolome and phenome). Banana originated in the humid tropics, and yields decrease dramatically when the crop is grown in dryer areas. Circumstantial evidence suggests that elements of the Musa balbisiana (B) genome confer greater drought tolerance on banana than those of the Musa acuminata (A) genome. Hence the genomic constitution may affect the stress response. To phenotype different Musa accessions belonging to different genomic groups, we monitored multiple non-destructive and destructive phenotypic plant variables in response to changing water availability. We used multivariate analysis to classify the different variables according to their contribution in explaining the observed variance between accessions. Ultimately, plant phenotype is driven by genes operating to regulate growth combined with environmental limitations. As such, gene and cell function must always be considered in the whole-plant context. Our brief overview of recent applications of -omics approaches in banana research also covers the challenges of applying such -omics approaches to a non-model crop, with a special focus on abiotic stress. As a general workflow, we propose to combine RNA-Seq, proteomics and metabolite analysis to characterize the cellular phenotype and link to the differential genotype. An interdisciplinary network in plant phenotyping should be established to characterize genetic diversity in genebanks and breeding programs.status: publishe

Effect of paleopolyploidy and allopolyploidy on gene expression in banana

BACKGROUND: Bananas (Musa spp.) are an important crop worldwide. Most modern cultivars resulted from a complex polyploidization history that comprised three whole genome duplications (WGDs) shaping the haploid Musa genome, followed by inter- and intra-specific crosses between Musa acuminata and M. balbisiana (A and B genome, respectively). Unresolved hybridizations finally led to banana diversification into several autotriploid (AAA) and allotriploid cultivars (AAB and ABB). Using transcriptomic data, we investigated the impact of the genome structure on gene expression patterns in roots of 12 different triploid genotypes covering AAA, AAB and ABB subgenome constitutions. RESULTS: We demonstrate that (i) there are different genome structures, (ii) expression patterns go beyond the predicted genomic groups, and (iii) the proportion of the B genome influences the gene expression. The presence of the B genome is associated with a higher expression of genes involved in flavonoid biosynthesis, fatty acid metabolism, amino sugar and nucleotide sugar metabolism and oxidative phosphorylation. There are cultivar-specific chromosome regions with biased B:A gene expression ratios that demonstrate homoeologous exchanges (HE) between A and B sub-genomes. In two cultivars, aneuploidy was detected. We identified 3674 genes with a different expression level between allotriploid and autotriploid with ~ 57% having recently duplicated copies (paralogous). We propose a Paralog Inclusive Expression (PIE) analysis that appears to be suitable for genomes still in a downsizing and fractionation process following whole genome duplications. Our approach allows highlighting the genes with a maximum likelihood to affect the plant phenotype. CONCLUSIONS: This study on banana is a good case to investigate the effects of alloploidy in crops. We conclude that allopolyploidy triggered changes in the genome structure of a crop and it clearly influences the gene.status: Published onlin