AI-powered detection and quantification of post-harvest physiological deterioration (PPD) in cassava using YOLO foundation models and K-means clustering.

Background: Post-harvest physiological deterioration (PPD) poses a significant challenge to the cassava industry, leading to substantial economic losses. This study aims to address this issue by developing a comprehensive framework in collaboration with cassava breeders.

Results: Advanced deep learning (DL) techniques such as Segment Anything Model (SAM) and YOLO foundation models (YOLOv7, YOLOv8, YOLOv9, and YOLO-NAS), were used to accurately categorize PPD severity from RGB images captured by cameras or cell phones.

Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI.

Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring both nutrition and economic stability in diverse communities, particularly in Africa and Latin America. However, CB cultivation poses a significant threat to diseases that can drastically reduce yield and quality. Detecting these diseases solely based on visual symptoms is challenging, due to the variability across different pathogens and similar symptoms caused by distinct pathogens, further complicating the detection process.

Assessing methane emissions from paddy fields through environmental and UAV remote sensing variables.

Concerns about methane (CH) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH emissions from rice fields is crucial for understanding gas concentrations.

Comparative Analysis of Detectors and Feature Descriptors for Multispectral Image Matching in Rice Crops.

Precision agriculture has greatly benefited from advances in machine vision and image processing techniques. The use of feature descriptors and detectors allows to find distinctive keypoints in an image and the use of this approach for agronomical applications has become a widespread field of study. By combining near infrared (NIR) images, acquired with a modified Nikon D80 camera, and visible spectrum (VIS) images, acquired with a Nikon D300s, a proper crop identification could be obtained.

Field-transcriptome analyses reveal developmental transitions during flowering in cassava (Manihot esculenta Crantz).

We characterized genes that function in the photoperiodic flowering pathway in cassava. Transcriptome analysis of field-grown plants revealed characteristic expression patterns of these genes, demonstrating that field-grown cassava experiences two distinct developmental transitions. Cassava is an important crop for both edible and industrial purposes.

The Rice DNA-Binding Protein ZBED Controls Stress Regulators and Maintains Disease Resistance After a Mild Drought.

Background: Identifying new sources of disease resistance and the corresponding underlying resistance mechanisms remains very challenging, particularly in Monocots. Moreover, the modification of most disease resistance pathways made so far is detrimental to tolerance to abiotic stresses such as drought. This is largely due to negative cross-talks between disease resistance and abiotic stress tolerance signaling pathways.

Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava ( Crantz).

Background: Rapid non-destructive measurements to predict cassava root yield over the full growing season through large numbers of germplasm and multiple environments is a huge challenge in Cassava breeding programs. As opposed to waiting until the harvest season, multispectral imagery using unmanned aerial vehicles (UAV) are capable of measuring the canopy metrics and vegetation indices (VIs) traits at different time points of the growth cycle. This resourceful time series aerial image processing with appropriate analytical framework is very important for the automatic extraction of phenotypic features from the image data.

Expression of the CCCH-tandem zinc finger protein gene OsTZF5 under a stress-inducible promoter mitigates the effect of drought stress on rice grain yield under field conditions.

Increasing drought resistance without sacrificing grain yield remains an ongoing challenge in crop improvement. In this study, we report that Oryza sativa CCCH-tandem zinc finger protein 5 (OsTZF5) can confer drought resistance and increase grain yield in transgenic rice plants. Expression of OsTZF5 was induced by abscisic acid, dehydration and cold stress.

Convolutional Neural Net-Based Cassava Storage Root Counting Using Real and Synthetic Images.

Cassava roots are complex structures comprising several distinct types of root. The number and size of the storage roots are two potential phenotypic traits reflecting crop yield and quality. Counting and measuring the size of cassava storage roots are usually done manually, or semi-automatically by first segmenting cassava root images.

A low-cost aeroponic phenotyping system for storage root development: unravelling the below-ground secrets of cassava ().

Background: Root and tuber crops are becoming more important for their high source of carbohydrates, next to cereals. Despite their commercial impact, there are significant knowledge gaps about the environmental and inherent regulation of storage root (SR) differentiation, due in part to the innate problems of studying storage roots and the lack of a suitable model system for monitoring storage root growth. The research presented here aimed to develop a reliable, low-cost effective system that enables the study of the factors influencing cassava storage root initiation and development.

Ground penetrating radar: a case study for estimating root bulking rate in cassava ( Crantz).

Background: Understanding root traits is a necessary research front for selection of favorable genotypes or cultivation practices. Root and tuber crops having most of their economic potential stored below ground are favorable candidates for such studies. The ability to image and quantify subsurface root structure would allow breeders to classify root traits for rapid selection and allow agronomist the ability to derive effective cultivation practices.

Overexpression of an Arabidopsis thaliana galactinol synthase gene improves drought tolerance in transgenic rice and increased grain yield in the field.

Drought stress has often caused significant decreases in crop production which could be associated with global warming. Enhancing drought tolerance without a grain yield penalty has been a great challenge in crop improvement. Here, we report the Arabidopsis thaliana galactinol synthase 2 gene (AtGolS2) was able to confer drought tolerance and increase grain yield in two different rice (Oryza sativa) genotypes under dry field conditions.

Development and field performance of nitrogen use efficient rice lines for Africa.

Nitrogen (N) fertilizers are a major input cost in rice production, and its excess application leads to major environmental pollution. Development of rice varieties with improved nitrogen use efficiency (NUE) is essential for sustainable agriculture. Here, we report the results of field evaluations of marker-free transgenic NERICA4 (New Rice for Africa 4) rice lines overexpressing barley alanine amino transferase (HvAlaAT) under the control of a rice stress-inducible promoter (pOsAnt1).

OsMADS26 Negatively Regulates Resistance to Pathogens and Drought Tolerance in Rice.

Functional analyses of MADS-box transcription factors in plants have unraveled their role in major developmental programs (e.g. flowering and floral organ identity) as well as stress-related developmental processes, such as abscission, fruit ripening, and senescence.

Development of disease-resistant rice by optimized expression of WRKY45.

The rice transcription factor WRKY45 plays a central role in the salicylic acid signalling pathway and mediates chemical-induced resistance to multiple pathogens, including Magnaporthe oryzae and Xanthomonas oryzae pv. oryzae. Previously, we reported that rice transformants overexpressing WRKY45 driven by the maize ubiquitin promoter were strongly resistant to both pathogens; however, their growth and yield were negatively affected because of the trade-off between the two conflicting traits.

Current issues in cereal crop biodiversity.

The exploration, conservation, and use of agricultural biodiversity are essential components of efficient transdisciplinary research for a sustainable agriculture and food sector. Most recent advances on plant biotechnology and crop genomics must be complemented with a holistic management of plant genetic resources. Plant breeding programs aimed at improving agricultural productivity and food security can benefit from the systematic exploitation and conservation of genetic diversity to meet the demands of a growing population facing climate change.

A first insight into population structure and linkage disequilibrium in the US peanut minicore collection.

Knowledge of genetic diversity, population structure, and degree of linkage disequilibrium (LD) in target association mapping populations is of great importance and is a prerequisite for LD-based mapping. In the present study, 96 genotypes comprising 92 accessions of the US peanut minicore collection, a component line of the tetraploid variety Florunner, diploid progenitors A. duranensis (AA) and A.