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[This corrects the article DOI: 10.3389/fpls.2025.1610552.].

In agricultural landscapes, the removal of semi‐natural habitats (SNH) and the intensive use of pesticides contribute to declines of biodiversity, including crop pollinators such as bees (Hymenoptera: Apoidea). However, effects of pesticide use and landscape characteristics on bees have rarely been studied together. In this study, we investigated how SNH in the surrounding landscape, organic and conventional management, and the reduction of fungicides affect wild bee diversity in 32 vineyards in southwest Germany. We used yellow pan traps to sample bees in a crossed design of management (organic vs. conventional) and fungicide use (reduced in fungus‐resistant grape varieties vs. regular) along a gradient with increasing proportions of SNH in the surrounding landscape. Higher proportions of SNH influenced species composition of bees and increased the abundance and richness of above‐ground‐nesting species. Organic vineyards had a 49% higher abundance of bees compared to conventional vineyards. The reduction of fungicides did not affect bee diversity nor abundance. The absence of a response to fungicide intensity suggests that the benefit of organically managed vineyards to wild bees was through differences in their vegetation management, which is in line with the positive response of bees to SNH in the surrounding landscape. Synthesis and applications: Our study underlines that the local provision of diverse vegetation in vineyards and the landscape‐scale provision of suitable SNH are key factors for wild bee conservation in viticulture. In agricultural landscapes, the clearing of semi‐natural habitats (SNH) and the intensive use of pesticides contribute to declines of biodiversity, including crop pollinators. Using yellow pan traps to sample wild bees, we investigated how SNH in the surrounding landscape, organic and conventional management, and the reduction of fungicides affect wild bee diversity in 32 vineyards in southwest Germany. Our study underlines that the local provision of diverse vegetation in vineyards and the landscape‐scale provision of suitable SNH are key factors for wild bee conservation in viticulture.

Innovation is essential for addressing the current challenges of the wine sector and ensuring its sustainable future. Law plays a pivotal role in fostering and disseminating innovation. At the same time, innovations can present legislators with significant challenges and cause legal disruption. This paper evaluates the innovativeness of European Wine Law in light of the ongoing sustainability transformation. The focus of EU regulations is wine quality and authenticity, mainly through the protection of Geographical Indications (GIs). In Regulation (EU) 2021/2117, the EU legislator recently introduced new rules on fungus-resistant grape varieties, de-alcoholised products, and digital labelling. We describe the effects of these rules on the respective innovation systems and assess how, vice versa, these innovations exert disruptive pressure on wine law. While the legal framework shows remarkable flexibility, a reconfiguration seems necessary at the level of GIs. The sustainability transformation implies an openness to innovation even for traditional producers. Regulatory Sandboxes in GI product specifications could allow for more experimentation without compromising heritage. A wine constitution could guide the transformation towards a more resilient and sustainable wine system.

Coffee leaf rust (CLR, Hemileia vastatrix) is considered the most damaging coffee disease worldwide, causing reduced yields and even plant death. CLR was detected in Hawaii for the first time in 2020, and quickly spread across the state. We initiated a CLR monitoring program in Kona, West Hawaii Island, to track the spread of this new invasive disease across a broad elevational gradient. The goals of the program were to assist growers in the early detection of CLR, to characterize patterns of disease incidence across the region, and to collect information on farm agronomics, management practices, and costs to apply fungicides, all of which can be used to develop Integrated Pest Management (IPM) strategies for this pathogen. We monitored 30 coffee lots in Kona, located between 204 and 875 m elevation. Average CLR incidence remained below 4% early in the season and increased to 36% during harvest. We observed no significant difference in CLR incidence between low-, mid- and high-elevation farms. A significant reduction in the number of leaves per branch was observed at the end of the harvest season, and a significant negative correlation was found between the number of leaves per branch and maximum CLR severity. Mean disease incidence and mean severity were observed to have a significant positive correlation. Incidence increased above threshold levels (5%), despite most growers applying preventative fungicides 3–10 times throughout the season, suggesting that improved coverage and timing of applications is needed along with the addition of systemic fungicides. Our study provides the first insights into CLR disease patterns under the unique and variable conditions under which Hawaiian coffee is grown, and will aid in the development of IPM programs that can be used to sustain Hawaii’s coffee industry under this new threat.

Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm−1) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.

The acquisition and expansion of apple varieties genetically resistant to diseases in cultivation have the effect of reducing the number of pesticide treatments, from 14-16 as is done in current plantations with classic varieties, to only 6-8 in orchards with genetically resistant varieties, positively reflecting in the reduction of production costs. Varieties susceptible to diseases, Ionathan, Golden delicious, Grupa Stark, represented the basis of the apple assortment 20-30 years ago, but in recent years, apple varieties with genetic resistance to diseases have increasingly appeared: Prima, Florina, Romus 3, Real, Revidar, Dacian, Inedit, etc., which will quickly enter cultivation and compete with sensitive apple varieties. Apple cultivation in our country has expanded into established fruit-growing areas, where they find the most favorable conditions for growth and fruiting. However, studies must be undertaken to highlight the influence of climatic factors on the quantity and quality of fruit production. In apple, as in other fruit species, a decisive role in increasing production potential is represented by the respect of genetic and technological elements, but also by appropriate zoning, depending on the recommended varieties and crop systems. Therefore, it is necessary to expand the cultivation of apple varieties that behave best with respect to the influence of climatic factors, but also in terms of productivity and fruit quality. Lately, the varieties that are starting to be part of the assortment of newly established orchards are apple varieties with genetic resistance to diseases. The Voinești Fruit Growing Research and Development Station, promoter of the disease-resistant apple variety, through the research undertaken and the newly obtained varieties, creates the premises for the development of modern fruit growing and the expansion of orchards, with possibilities for obtaining productions with reduced phytosanitary product residues, requested by consumers, and for protecting the environment.

KEY MESSAGE : This consensus map of stem rust genes, QTLs, and molecular markers will facilitate the identification of new resistance genes and provide a resource of in formation for development of new markers for breeding wheat varieties resistant to Ug99. The global effort to identify new sources of resistance to wheat stem rust, caused by Puccinia graminis f. sp. tritici race group Ug99 has resulted in numerous studies reporting both qualitative genes and quantitative trait loci. The purpose of our study was to assemble all available information on loci associated with stem rust resistance from 21 recent studies on Triticum aestivum L. (bread wheat) and Triticum turgidum subsp. durum desf. (durum wheat). The software LPmerge was used to construct a stem rust resistance loci consensus wheat map with 1,433 markers incorporating Single Nucleotide Polymorphism, Diversity Arrays Technology, Genotyping-by-Sequencing as well as Simple Sequence Repeat marker information. Most of the markers associated with stem rust resistance have been identified in more than one population. Several loci identified in these populations map to the same regions with known Sr genes including Sr2, SrND643, Sr25 and Sr57 (Lr34/Yr18/Pm38), while other significant markers were located in chromosome regions where no Sr genes have been previously reported. This consensus map provides a comprehensive source of information on 141 stem rust resistance loci conferring resistance to stem rust Ug99 as well as linked markers for use in marker-assisted selection.

As a globally important economic crop, cotton often faces yield and quality limitations due to drought stress. To elucidate drought tolerance mechanisms, this study screened a drought-tolerant variety (64-22-3) and a drought-sensitive variety (Anmian 3, A3) from five drought-resistant and five drought-sensitive materials, respectively. Integrated transcriptomic and metabolomic analyses revealed 7,351 differentially expressed genes (DEGs) in the drought-tolerant variety under drought treatment (5,034 upregulated, 2,317 downregulated), while the drought-sensitive variety exhibited 5,009 DEGs (3,222 upregulated, 1,787 downregulated). Metabolomic profiling identified 169 differentially accumulated metabolites (DAMs) (120 upregulated, 49 downregulated) in 64-22–3 and 173 DAMs (120 upregulated, 53 downregulated) in A3. KEGG enrichment analysis showed that DEGs and DAMs in both varieties were significantly enriched in secondary metabolite biosynthesis, flavonoid biosynthesis, and sesquiterpenoid/triterpenoid biosynthesis. Notably, the drought-tolerant variety displayed specific enrichment in phenylpropanoid biosynthesis, linoleic acid metabolism, and glucosinolate biosynthesis, suggesting their roles in drought adaptation. Weighted gene co-expression network analysis (WGCNA) of 2,064 unique DEGs and 20 key metabolites in the drought-tolerant variety identified blue and turquoise modules as strongly associated with metabolite accumulation, with core hub genes Ghi_D06G05631 and Ghi_A13G12271, which encode TOPLESS-related 1 protein and CIPK6 (CBL-interacting protein kinase 6) separately. Transcription factor (TF) analysis revealed seven high-connectivity TF families (HSF, Golden2-like, SNF2, mTERF, bHLH, C2H2, B3) in the blue module and six TF families (Tify, ARR-B, AUX/IAA, bHLH, Alfin-like, LUG) in the turquoise module, suggesting their coordinated regulation of drought responses. This study systematically elucidates the molecular network underlying cotton’s drought adaptation, providing critical insights for identifying key drought-resistant genes and developing resilient cultivars.

The ascomycete Erysiphe necator is a serious pathogen in viticulture. Despite the fact that some grapevine genotypes exhibit mono-locus or pyramided resistance to this fungus, the lipidomics basis of these genotypes’ defense mechanisms remains unknown. Lipid molecules have critical functions in plant defenses, acting as structural barriers in the cell wall that limit pathogen access or as signaling molecules after stress responses that may regulate innate plant immunity. To unravel and better understand their involvement in plant defense, we used a novel approach of ultra-high performance liquid chromatography (UHPLC)-MS/MS to study how E. necator infection changes the lipid profile of genotypes with different sources of resistance, including BC4 (Run1), “Kishmish vatkhana” (Ren1), F26P92 (Ren3; Ren9), and “Teroldego” (a susceptible genotype), at 0, 24, and 48 hpi. The lipidome alterations were most visible at 24 hpi for BC4 and F26P92, and at 48 hpi for “Kishmish vatkhana”. Among the most abundant lipids in grapevine leaves were the extra-plastidial lipids: glycerophosphocholine (PCs), glycerophosphoethanolamine (PEs) and the signaling lipids: glycerophosphates (Pas) and glycerophosphoinositols (PIs), followed by the plastid lipids: glycerophosphoglycerols (PGs), monogalactosyldiacylglycerols (MGDGs), and digalactosyldiacylglycerols (DGDGs) and, in lower amounts lyso-glycerophosphocholines (LPCs), lyso-glycerophosphoglycerols (LPGs), lyso-glycerophosphoinositols (LPIs), and lyso-glycerophosphoethanolamine (LPEs). Furthermore, the three resistant genotypes had the most prevalent down-accumulated lipid classes, while the susceptible genotype had the most prevalent up-accumulated lipid classes.

Shallot as a horticultural crop has various benefits and important uses as a provider of nutritional needs. Its uniqueness in aroma and flavor makes it commonly used as a seasoning so that it has a good economic value as an increase in farmers’ income. Sandy land on the coast has the potential for shallot cultivation. The presence of wind that airborne salinity on coastal land requires the selection of tolerant varieties and knowledge of the level of airborne salinity concentration that shallot plants can tolerate. Experiments have been conducted from July to December 2023 in the screenhouse and horticultural agronomy lab, Faculty of Agriculture, Jenderal Soedirman University, Purwokerto (7°24’27.7”S, 109°15’19.1”E). Treatments consisted of the use of shallot varieties Bali Karet (B₁) and Bima Brebes (B₂), with the application of several concentrations of airborne salinity consisting of 0, 6, 12, and 18 mS cm−1. The Bali Karet variety excels in plant height and root dry weight morphologically. Physiologically, Bima Brebes has higher levels of chlorophyll a and stomatal density, while Bali Karet is superior in chlorophyll b. Harvest results show Bima Brebes produces more tubers, while Bali Karet produces higher fresh tuber weight per clump. Morphological parameters (plant height, root dry weight), physiology (chlorophyll a, chlorophyll b, stomatal aperture, stomatal density), and yield showed the highest value at the lowest air salinity concentration (0 mS cm−1). Both varieties increased proline as a tolerance mechanism to 18 mS cm−1 air salinity. The best interaction occurred between Bali Karet and 0 mS cm−1 salinity on stomatal opening, and between Bima Brebes and 0 mS cm ¹ salinity on stomatal density. Both varieties were classified as having moderate tolerance to 18 mS cm−1 salinity, but total chlorophyll was very sensitive to this salinity concentration.