Integrating agricultural, chemical, and technological knowledge is crucial for developing bio-nanotechnologies to improve agricultural production. This study explores the innovative use of biopolymeric coatings, based on sodium alginate and sodium alginate + Laponite® (nanoclay), containing biostimulants (tryptophol and thymol) or not, on garlic cloves. These coatings were analyzed using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR-ATR), and scanning electron microscopy (SEM). Greenhouse bioassays showed improvements in garlic shoot plant biomass with both treatments: sodium alginate biopolymer and sodium alginate biopolymer plus Laponite®. In the field experiment, garlic plants treated with sodium alginate, in combination with conventional pesticide treatments, resulted in better quality garlic bulbs, where larger garlics were harvested in this treatment, reducing commercial losses. In tropical garlic crops, obtaining plants with greater initial vigor is essential. Our results highlight the potential of these bio-nanotechnological strategies to enhance garlic propagation, ensuring environmental protection and food security.

Introduction history, including propagule pressure and residence time, has been proposed as a primary driver of biological invasions. However, it is unclear whether introduction history increases the likelihood that a species will be invasive or only the likelihood that it will be established. Using a dataset of non-native species historically available as ornamental plants in the conterminous United States, we investigated how introduction history relates to these stages of invasion. Introduction history was highly significant and a strong predictor of establishment, but only marginally significant and a poor predictor of invasive success. Propagule pressure predicted establishment better than residence time, with species likely to be established if they were introduced to only eight locations. These findings suggest that ongoing plant introductions will lead to widespread establishment but may not directly increase invasive success. Instead, other characteristics, like plant traits and local scale processes, may better predict whether a species becomes invasive.

Multiple Epiphyas species inhabit southwestern Western Australia, including Light Brown Apple Moth (LBAM) Epiphyas postvittana (Walker) (Lepidoptera: Tortricidae), a globally significant, polyphagous pest. This study evaluated the efficacy and specificity of lures designed for 3 Epiphyas species: E. postvittana, Epiphyas pulla (Turner), and the undescribed Epiphyas sp. (1) (Common). Additionally, the study sought to determine the presence and distribution of Epiphyas species in 3 significant apple-growing localities. Trapping, together with partial sequencing of the mitochondrial COI gene, found LBAM to be restricted to the Perth Hills and E. pulla, to apple orchards near Manjimup and Pemberton. This geographic disjunction remains unexplained. Epiphyas sp. (1) was not recorded despite using a specifically designed lure. The E. pulla and LBAM traps demonstrated superior efficacy in capturing their target species, while the catch in Epiphyas sp. (1) traps did not significantly differ between the 2. Both E. pulla and LBAM exhibited peak abundance from late spring to the end of summer (October-February), with variations in timing and peak catch of male moths across species, locations, and years. Surveys conducted in April during the harvest period (February-May), when moth traps caught an average of 1-1.8 moths/trap/week, found no Epiphyas larvae or damage on 140,400 mature apples or on 26,000 leaves. While E. pulla and LBAM traps effectively monitor their target moths, genetic identification of trap catch would be necessary if they co-occurred. Encouragingly, the results indicate that both species become relatively rare as harvest season approaches, and neither inflicts significant damage to mature apples under existing management.

The complexity of the agroecosystem can also be assessed by the different land uses in the system and the surroundings, being a relevant way to assess the heterogeneity of the landscape and the effects on the community of interest, in this case, entomofauna. Thus, the objective of this work is to verify how the use of soil in the surroundings of Chilean lettuce horticultural systems, in the Coquimbo Region, alters the entomological community of the crop. Insect sampling was conducted (February 2021 to March 2022) using yellow pan traps. Two sites will be sampled on each of the seven studied lettuce crops. Land use and land cover classes were defined: Forests, water bodies, shrub vegetation, grasslands, barren lands, impermeable surfaces, and urban areas. After land use and land cover classification, buffers of 500 to 5,000 m were created around each data collection point. For data analysis, the percentages of land use of different classes were compared with the ecological attributes: Abundance of insects, abundance of insect pests, richness of entomological families and types of oral apparatus (licker-sucker, mandible, picker-sucker, and sucker). Land uses at different distances from horticultural systems affected the entomological community.

Crop growth monitoring is essential for both crop and supply chain management. Conventional manual sampling is not feasible for assessing the spatial variability of crop growth within an entire field or across all fields. Meanwhile, UAV-based remote sensing enables the efficient and nondestructive investigation of crop growth. A variety of crop-specific training image datasets are needed to detect crops from UAV imagery using a deep learning model. Specifically, the training dataset of cabbage is limited. This data article includes annotated cabbage images in the fields to recognize cabbages using machine learning models. This dataset contains 458 images with 17,621 annotated cabbages. Image sizes are approximately 500 to 1000 pixel squares. Since these cabbage images were collected from different cultivars during the whole growing season over the years, deep learning models trained with this dataset will be able to recognize a wide variety of cabbage shapes. In the future, this dataset can be used not only in UAVs but also in land-based robot applications for crop sensing or associated plant-specific management.

Melatonin (N-acetyl-5-methoxytryptamine), a well-known mammalian hormone, has been having a great relevance in the Plant World in recent years. Many of its physiological actions in plants are leading to possible features of agronomic interest, especially those related to improvements in tolerance to stressors and in the postharvest life of fruits and vegetables. Thus, through the exogenous application of melatonin or by modifying the endogenous biosynthesis of phytomelatonin, some change can be made in the functional levels of melatonin in tissues and their responses. Also, acting in the respective phytomelatonin biosynthesis enzymes, regulating the expression of tryptophan decarboxylase (TDC), tryptamine 5-hydroxylase (T5H), serotonin N-acetyltransferase (SNAT), N-acetylserotonin O-methyltransferase (ASMT), and caffeic acid O-methyltransferase (COMT), and recently the possible action of deacetylases on some intermediates offers promising opportunities for improving fruits and vegetables in postharvest and its marketability. Other regulators/effectors such as different transcription factors, protein kinases, phosphatases, miRNAs, protein-protein interactions, and some gasotransmitters such as nitric oxide or hydrogen sulfide were also considered in an exhaustive vision. Other interesting aspects such as the role of phytomelatonin in autophagic responses, the posttranslational reprogramming by protein-phosphorylation, ubiquitylation, SUMOylation, PARylation, persulfidation, and nitrosylation described in the phytomelatonin-mediated responses were also discussed, including the relationship of phytomelatonin and several plant hormones, for chilling injury and fungal decay alleviating. The current data about the phytomelatonin receptor in plants (CAND2/PMTR1), the effect of UV-B light and cold storage on the postharvest damage are presented and discussed. All this on the focus of a possible new action in the preservation of the quality of fruits and vegetables.

Mismanagement of the nitrogen (N) fertilization in agriculture leads to low N use efficiency (NUE) and therefore pollution of waters and atmosphere due to NO3- leaching, and N2O and NH3 emissions. The use of N simulation models of the soil-plant system can help improve the N fertilizer management increasing NUE and decreasing N pollution issues. However, many N simulation models lack balance between complexity and uncertainty with the result that they are not applied in actual practice. The NITIRSOIL is a one-dimensional transient-state model with a monthly time step that aims at addressing this lack in the estimation of, mainly, dry matter yield (DMY), crop N uptake (Nupt), soil mineral N (Nmin), and NO3- leaching in agricultural fields. According to its global sensitivity analysis for horticulture, the NITIRSOIL simulations of the aforementioned outputs mostly depend on the critical N dilution curve, harvest index, dry matter fraction, potential fresh yield and nitrification coefficients. According to its validation for 35 nitrogen fertilization trials with 11 vegetables under semi-arid Mediterranean climate in Eastern Spain, the NITIRSOIL presents indices of agreement between 0.87 and 0.97 for the prediction of total dry matter, DMY, Nupt, NO3- leaching and soil Nmin at crop season end. Therefore, the NITIRSOIL model can be used in actual practice to improve the sustainability of the N management in, particularly horticulture, due to the balance it features between complexity and prediction uncertainty. For this aim, the NITRISOIL can be used either on its own, or in combination with \"Nmin\" on-site N fertilization recommendation methods, or even could be implemented as the calculation core of decision support systems.

Azole-resistant Aspergillus fumigatus (ARAf) fungi have been found inconsistently in the environment in Denmark since 2010. During 2018-2020, nationwide surveillance of clinical A. fumigatus fungi reported environmental TR34/L98H or TR46/Y121F/T289A resistance mutations in 3.6% of isolates, prompting environmental sampling for ARAf and azole fungicides and investigation for selection of ARAf in field and microcosmos experiments. ARAf was ubiquitous (20% of 366 samples; 16% TR34/L98H- and 4% TR46/Y121F/T289A-related mechanisms), constituting 4.2% of 4,538 A. fumigatus isolates. The highest proportions were in flower- and compost-related samples but were not correlated with azole-fungicide application concentrations. Genotyping showed clustering of tandem repeat-related ARAf and overlaps with clinical isolates in Denmark. A. fumigatus fungi grew poorly in the field experiment with no postapplication change in ARAf proportions. However, in microcosmos experiments, a sustained complete (tebuconazole) or partial (prothioconazole) inhibition against wild-type A. fumigatus but not ARAf indicated that, under some conditions, azole fungicides may favor growth of ARAf in soil.

The postharvest end-quality of citrus is significantly impacted by pre-harvest factors such as weather, which varies among growing regions. Despite the importance of these factors, the influence of regional weather variations, such as variations in temperature, humidity, wind, vapor pressure deficit (VPD), and solar radiation on postharvest citrus quality, is largely unknown. This study aims to quantify this impact through a physics-driven digital replica of the entire value chain of Valencia oranges, from orchards in South Africa to retail in Europe. Predicted fruit properties data at harvest and hygrothermal sensor data from orchard to retail for different production regions are coupled to a physics-based fruit model to simulate key postharvest fruit quality metrics. These metrics include mass loss, chilling injury, fruit quality index (FQI), remaining shelf life (RSL), total soluble solids (TSS), and titratable acidity (TA). Our digital fruit model reveals that regional weather variability significantly affects fruit quality evolution when comparing data from Nelspruit, Letsitele, and Sunday\'s River Valley (SRV). The impact of weather variations is most pronounced in the temperate oceanic climate of SRV compared to the hotter climates of Letsitele and Nelspruit. Our findings indicate that differences in weather conditions between these growing regions impact postharvest mass loss, FQI, RSL, TSS, and TA of Valencia oranges at retail. The impact is up to 10% variation in mass loss and RSL, 4% in TSS, and 1% in TA among oranges grown in different regions. We show that temperature and humidity variations in the postharvest local transport of oranges between different regions largely increase mass loss by up to twofold, FQI by up to ~ 12%, and RSL by up to ~ 15% at retail. Our research also shows that weather temperature is the most important metric during fruit growth affecting various aspects of postharvest orange quality. This study offers valuable insights into the impact of regional weather variations on the quality of oranges available to consumers. These findings could help the citrus industry enhance growing practices, postharvest logistics, retail marketing, and cold chain strategies, thereby improving product quality and consumer satisfaction.

Genetic and epigenetic variations produced via cell and tissue culture open up new sources of variability intra-species which can be used to improve crops. The use of in vitro generated somaclonal variations for selecting novel variants aids in the development of novel genotypes having desirable agronomic traits that can be released as varieties or utilized for breeding purposes. Horticultural crops give higher yield and productivity per unit area than other crops, as well as provide good economic returns which have led to an increase in their potential benefits throughout time. The last three to four decades have seen the selection and release of a number of valuable somaclonal variants, many of which possess remarkable features including disease resistance, high yield, improved nutritional quality and abiotic stress tolerance. Generating somaclonal variations has given breeders a novel alternative option for obtaining genetic diversity in horticultural crops and without advanced technologies. The variations introduced through tissue culture process, methods to determine and validate genetic changes in vitro regenerated plantlets, along with prospective application of such variations in horticultural crops\' improvement are reviewed in the present work.