Tomato detection method using domain adaptive learning for dense planting environments

This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.

Differential Expression of Genes Related to Fruit Development and Capsaicinoids Synthesis in Habanero Pepper Plants Grown in Contrasting Soil Types

Habanero pepper(Capsicum chinense Jacq.)is a crop of economic relevance in the Peninsula of Yucatan.Its fruits have a high level of capsaicinoids compared to peppers grown in other regions of the world,which gives them industrial importance.Soil is an important factor that affects pepper development,nutritional quality,and capsaicinoid content.However,the effect of soil type on fruit development and capsaicinoid metabolism has been little understood.This work aimed to compare the effect of soils with contrasting characteristics,black soil(BS)and red soil(RS),on the expression of genes related to the development of fruits,and capsaicinoid synthesis using a transcriptomic analysis of the habanero pepper fruits.Plants growing in RS had bigger fruits and higher expression of genes related to floral development,fruit abscission,and softening which suggests that RS stimulates fruit development from early stages until maturation stages.Fruits from plants growing in BS had enrichment in metabolic pathways related to growth,sugars,and photosynthesis.Besides,these fruits had higher capsaicinoid accumulation at 25 days post-anthesis,and higher expression of genes related to the branched-chain amino acids metabolism(ketol-acid reductisomerase KARI),pentose phosphate pathway and production of NADPH(glucose-6-phosphate-1-dehydrogenase G6PDH),and proteasome and vesicular traffic in cells(26S proteasome regulatory subunit T4 RPT4),which suggest that BS is better in the early stimulation of pathways related to the nutritional quality and capsaicinoid metabolism in the fruits.

Beyond Biochar-Soil, Plant and Environment: Research Progress and Future Prospects

Since industrial revolution, the atmospheric CO2 concentration has kept a continuous increase by more than 2.2 ppm yr^-1, and approaches to almost 400 ppm at present （Jouzel 2012）. China has become the largest country of greenhouse gas emission （GHG）, and confronts with great challenge to mitigate GHG.

Teaching Reform and Practice of Plant Growth Environment Course in the Context of Application Transformation Development

Through the personnel training program,revising the syllabus,optimizing teaching contents,reforming teaching methods,strengthening practical teaching links and reforming examination methods,this paper explored the teaching reform and practice of Plant Growth Environment Course,in order to improve the teaching effect,stimulate learning interests of students,and cultivate application type talents meeting social demands.

Application Potential of Quinoa as Forage

Quinoa is a crop as both food and forage.It has a tolerance to cold,drought,and salt.It is rich in vitamins,polyphenols,flavonoids,phytosterols and other substances,and has rich nutritional value and health care,which provides great potential for being as forage.In this paper,the application potential and prospects of quinoa as forage are studied.

Effects of Irrigation and Drought on Growth and Essential Oil Production in O. vulgare and R. officinalis

The essential oil industry has led a rapidly growing market in American herbal medicine. The global essential oil industry was valued at an estimated 18.6 billion USD in 2020 and is expected to have a compound annual growth rate of 7.6% from 2020 to 2027. “Essential oil” is a broad term used to describe volatile organic compounds (VOCs) that are often associated with a plant’s essence or aroma. These molecules are commonly extracted from a variety of different plant structures by steam distillation and cold pressing. Essential oils function as a defense against insects, bacteria, fungi, and other stressors, such as drought and cold. The most industrially important of this class of compounds are monoterpenes, steam-volatile constituents which are the most abundant terpenes throughout plants. Essential oils may include monoterpenes (two isoprene units), sesquiterpenes (three isoprene units), ketones, and phenolics. Phenolics include flavonoids, anthocyanins, and tannins.

A size-gradient hypothesis for alpine treeline ecotones

Research on the stress gradient hypothesis recognizes that positive(i.e. facilitative) and negative(i.e. competitive) plant interactions change in intensity and effect relative to abiotic stress experienced on a gradient. Motivated by observations of alpine treeline ecotones, we suggest that this switch in interaction could operate along a gradient of relative size of individual plants. We propose that as neighbors increase in size relative to a focal plant they improve the environment for that plant up to a critical point. After this critical point is surpassed, however, increasing relative size of neighbors will degrade the environment such that the net interaction intensity becomes negative. We developed a conceptual(not site or species specific) individual based model to simulate a single species with recruitment, growth, and mortality dependent on the environment mediated by the relative size of neighbors. Growth and size form a feedback. Simulation results show that the size gradient model produces metrics similar to that of a stress gradient model. Visualizations reveal that the size gradient model produces spatial patterns that are similar to the complex ones observed at alpine treelines. Size-mediated interaction could be a mechanism of the stress gradient hypothesis or it could operate independent of abiotic stress.

New insights into plant nutrient signaling and adaptation to fluctuating environments

Over the past 50 years, the Green Revolution and exploitation of heterosis have allowed cereal grain yield to keep pace with world- wide population growth. Unfortunately, plant growth and crop productivity are heavily dependent on the application of synthetic fertilizers.

Plants and Global Environmental Change:A Special Issue Highlighting Younger Scientists

Humans are changing the global environment to such an extent that they are changing global climate （IPCC 2007; http：//www.ipcc.ch/）. The pace, if not the eventual extent, of this climate change may be rare in Earth＇s history, and these rapid changes in climate will have profound negative impacts on biodiversity of the planet and on the quality of human life （Millennium Ecosystem Assessment; http：llwww.maweb.orgll en/Index.aspx）. It is already widely believed that the Earth has entered a new geological period termed the Anthropocene, in recognition of the impact that humans are having on the Earth, and it is predicted that human-caused changes to Earth＇s environment and climate will likely be the foremost problems facing humans in the coming decades.

Ractopamine up take by alfalfa (Medicago sativa) and wheat (Triticum aestivum) from soil

Ractopamine is a beta adrenergic agonist used as a growth promoter in swine, cattle and turkeys. To test whether ractopamine has the potential to accumulate in plants grown in contaminated soil, a greenhouse study was conducted with alfalfa（Medicago sativa） and wheat（Triticum aestivum） grown in two soils having different concentrations of organic matter（1.3% and 2.1%）, amended with 0, 0.5, and 10 μg/g of ractopamine. Plant growth ranged from 2.7 to 8.8 g dry weight（dw） for alfalfa, and 8.7 to 40 g dw for wheat and was generally greater in the higher organic matter content soil. The uptake of ractopamine in plant tissues ranged from non-detectable to 897 ng/g and was strongly dependent on soil ractopamine concentration across soil and plant tissue. When adjusted to the total fortified quantities, the amount of ractopamine taken up by the plant tissue was low, 〈 0.01% for either soil.

Rhynchophorus ferrugineus attack affects a group of compounds rather than rearranging Phoenix canariensis metabolic pathways

The red palm weevil（RPW; Rhynchophorus ferrugineus） is spreading worldwide and severely harming many palm species. However, most studies on RPW focused on insect biology, and little information is available about the plant response to the attack. In the present experiment, we used metabolomics to study the alteration of the leaf metabolome of Phoenix canariensis at initial（1^（st） stage） or advanced（2^（nd） stage）attack by RPW compared with healthy（unattacked） plants.The leaf metabolome significantly varied among treatments. At the 1^（st） stage of attack, plants showed a reprogramming of carbohydrate and organic acid metabolism; in contrast, peptides and lipid metabolic pathways underwent more changes during the 2^（nd） than 1^（st） stage of attack. Enrichment metabolomics analysis indicated that RPW attack mostly affected a particular group of compounds rather than rearranging plant metabolic pathways. Some compounds selectively affected during the 1^（st） rather than 2^（nd） stage（e.g. phenylalanine; tryptophan; cellobiose;xylose; quinate; xylonite; idonate; and iso-threonate; cellobiotol and arbutine） are upstream events in the phenylpropanoid,terpenoid and alkaloid biosynthesis. These compounds could be designated as potential markers of initial RPW attack. However,further investigation is needed to determine efficient early screening methods of RPW attack based on the concentrations of these molecules.