Search Results (121)

Apple represents one of the most economically significant fruit crops worldwide, and the performance of its scion is largely determined by the physiological and genetic characteristics of the rootstock. Despite their superior ecological adaptability and growth-controlling attributes, many dwarfing apple rootstocks exhibit inherently poor rooting competence, which poses a critical limitation to their large-scale clonal propagation and commercial utilization. Adventitious root (AR) formation is a pivotal yet highly intricate developmental process that governs the success of asexual propagation. It is orchestrated by a complex network of hormonal signaling, transcriptional regulation, metabolic reprogramming, and environmental cues. Over the past decade, remarkable advances have elucidated the physiological, biochemical, and molecular frameworks underpinning AR formation in apple rootstocks. This review provides an integrative synthesis of current progress in vegetative propagation techniques—including cutting, layering, and tissue culture—and systematically dissects the endogenous and exogenous factors influencing AR development. Particular emphasis is placed on the regulatory interplay among phytohormones, carbohydrate and nitrogen metabolism, phenolic compounds, transcription factors (such as WUSCHEL-RELATED HOMEOBOX (WOX), LATERAL ORGAN BOUNDARIES DOMAIN (LBD), and RESPONSE FACTOR (ARF families), and epigenetic modulators that collectively coordinate root induction and emergence. Furthermore, emerging insights into multi-omics integration and genotype-specific molecular regulation are discussed as strategic pathways toward enhancing propagation efficiency. Collectively, this review establishes a comprehensive theoretical framework for optimizing the asexual propagation of apple rootstocks and provides critical molecular guidance for breeding novel, easy-to-root genotypes that can drive the sustainable intensification of global apple production. Full article

Vegetative propagation through stem cuttings and in vitro microcuttings enables large-scale multiplication of superior genotypes in various crop species. This approach is widely used both to propagate and select trees with desirable genetic traits as well as to preserve a significant proportion of genetic diversity. However, successful plant regeneration using this technique requires the development of an adventitious root (AR) system at the base of cuttings or microcuttings. Reduced root formation and functionality strongly limit the application of vegetative propagation, both in vivo and in vitro. The complex process of AR development is greatly influenced by the physiological state of the donor plant, as well as by genetic and environmental factors. Among the environmental factors involved, light quality and intensity have been mainly studied empirically. This review summarizes advances in understanding how light quantity and quality influence in vitro rooting of micropropagated plants, emphasizing species-specific responses. Furthermore, medium components such as sugars and growth regulators, which interact significantly with light, are also considered. Based on existing studies across different plant species, particularly in the absence of growth regulators, the most effective spectrum for root induction is a temporary enrichment of red light, either alone or combined with small amounts of blue or green light. An efficient root growth occurs when the explants are re-exposed to white light, typically at intensities of 40–50 μmol m⁻² s⁻¹. After root development, exposing the microcuttings to higher intensities could help acclimatization. Finally, considering its capacity to precisely regulate light quality and intensity, LED technology offers a valuable tool for optimizing the rooting process and reducing production costs. Full article

Glycine betaine (GB) is a compatible solute that enhances plant tolerance to abiotic stresses, yet its role in fruit crops remains insufficiently explored. This study assessed whether GB improves drought tolerance in Passiflora edulis Sims f. flavicarpa, a crop sensitive to irregular rainfall. A 3 × 2 × 2 factorial design was employed, combining three drought levels (control, mild, and severe), two propagation methods (seedlings and cuttings), and two GB treatments (0 and 100 mM), with 60 plants and five replicates. Plants were grown under controlled conditions, and irrigation was adjusted to maintain target field capacities. Chlorophyll content was monitored daily, and agronomic and physiological traits were measured after 45 days. GB application influenced leaf water dynamics and stress responses. Cuttings generally showed clearer improvements in drought tolerance when treated with GB, while seedlings exhibited more variable outcomes. These differences appear linked to the propagation method and developmental stage as cuttings were at a more advanced phase, whereas seedlings remained vegetative. Overall, the results demonstrate that exogenous GB can enhance drought tolerance in passion fruit, although its effectiveness is propagation-dependent and context-specific, highlighting the need to tailor its application to cultivation practices. Full article

Sweetpotato is a key staple crop in tropical and subtropical regions. Its vegetative propagation makes it a persistent reservoir, facilitating the emergence and spread of complex infections. Understanding its virome is crucial for disease management and food security. We investigated the sweetpotato virome in Burkina Faso using rolling circle amplification and Oxford Nanopore sequencing. Eight symptomatic leaf samples, previously undiagnosed using conventional methods, were analysed. Bioinformatic pipelines were employed followed by phylogenetic comparisons. Two viruses known to infect sweetpotato, namely sweet potato leaf curl virus (SPLCV) and sweet potato leaf curl deltasatellite 3 (SPLCD3), were consistently detected in all samples. Additionally, pepper yellow vein Mali virus (PepYVMV), cotton leaf curl Gezira alphasatellite (CLCuGeA) and cotton leaf curl Gezira betasatellite (CLCuGeB) were identified for the first time in this crop. Phylogenetic analysis confirmed their genetic proximity to isolates from tomato, okra and pepper. Their co-occurrence with SPLCV and SPLCD3 indicates a complex viral landscape that could influence disease severity. This study highlights the underestimated role of sweetpotato as a viral reservoir, influencing virus evolution and transmission. Further studies should assess their pathogenicity, co-infection dynamics and vector-mediated transmission to improve crop productivity. Full article

Assessing crop nitrogen status is crucial for optimizing fertilization strategies and promoting sustainable production. Although hyperspectral data offer significant advantages for monitoring subtle physiological changes in crops, accurately determining nitrogen status based on spectral information remains challenging. In this study, field experiments were conducted during the jointing stage of winter wheat on the Loess Plateau from 2018 to 2020. Concurrent measurements of leaf nitrogen concentration (LNC) and hyperspectral reflectance were collected to derive three types of spectral parameters: traditional vegetation indices, two-dimensional optimal spectral indices, and three-dimensional optimal spectral indices. Spectral parameters exhibiting a significant correlation with LNC (p < 0.05) were selected and combined as inputs for three machine learning models—extreme learning machine (ELM), back-propagation neural network (BPNN), and random forest (RF)—to develop LNC estimation models. The results demonstrated that, among the traditional indices, the Double Difference Index (DDn) showed the strongest correlation with LNC (r = 0.674). Within the multidimensional optimal indices, the differential three-dimensional scattering index (DTSI) exhibited the highest sensitivity to LNC (r = 0.721) at wavelength combinations of 833 nm, 755 nm, and 802 nm. Moreover, Model Input Combination 5 (comprising empirical indices plus three-dimensional optimal indices) further enhanced estimation accuracy. The RF model using Combination 5 achieved the best performance on the validation set (R² = 0.827, RMSE = 2.803 mg g⁻¹, MRE = 7.664%), significantly outperforming other model–input combinations. This study confirms the feasibility and high accuracy of winter wheat LNC inversion using novel multidimensional spectral indices and provides a new approach for real-time, non-destructive monitoring of nitrogen status in winter wheat. Full article

Most crops accumulate above-ground biomass (AGB) through photosynthesis, inspiring the development of the Photosynthetic Accumulation Model (PAM) and Simplified PAM (SPAM). Both models estimate AGB based on time-series optical vegetation indices (VIs) and canopy height. To further enhance the model performance and evaluate its applicability across different crop types, an improved PAM model (IPAM) is proposed with three strategies. They are as follows: (i) using numerical integration to reduce reliance on dense observations, ($ii$) introduction of Fibonacci sequence-based structural correction to improve model accuracy, and ($iii$) non-photosynthetic area masking to reduce overestimation. Results from both soybean and cotton demonstrate the strong performance of the PAM-series models. Among them, the proposed IPAM model achieved higher accuracy, with mean $R^2$ and RMSE values of 0.89 and 207 g/m² for soybean and 0.84 and 251 g/m² for cotton, respectively. Among the vegetation indices tested, the recently proposed Near-Infrared Reflectance of vegetation (NIRv) and Kernel-based normalized difference vegetation index (Kndvi) yielded the most accurate results. Both Monte Carlo simulations and theoretical error propagation analyses indicate a maximum deviation percentage of approximately 20% for both crops, which is considered acceptable given the expected inter-annual variation in model transferability. In addition, this paper discusses alternatives to height measurements and evaluates the feasibility of incorporating synthetic aperture radar (SAR) VIs, providing practical insights into the model’s adaptability across diverse data conditions. Full article

Saffron (Crocus sativus L.) is a vegetatively propagated crop of high economic and cultural value, potentially affected by viral infections that may impact its productivity. Despite Iran’s dominance in global saffron production, knowledge of its virome remains limited. In this study, we conducted the first nationwide virome survey of saffron in Iran employing a high-throughput sequencing (HTS) approach on pooled samples obtained from eleven provinces in Iran and one location in Afghanistan. Members of three virus families were detected—Potyviridae (Potyvirus), Solemoviridae (Polerovirus), and Geminiviridae (Mastrevirus)—as well as one satellite from the family Alphasatellitidae (Clecrusatellite). A novel Potyvirus, tentatively named saffron Iran virus (SaIRV) and detected in three provinces, shares less than 68% nucleotide identity with known Potyvirus species, thus meeting the ICTV criteria for designation as a new species. Genetic diversity analyses revealed substantial intrapopulation SNP variation but no clear geographical clustering. Among the two wild Crocus species sampled, only Crocus speciosus harbored turnip mosaic virus. Virome network and phylogenetic analyses confirmed widespread viral circulation likely driven by corm-mediated propagation. Our findings highlight the need for targeted certification programs and biological characterization of key viruses to mitigate potential impacts on saffron yield and quality. Full article

Optimized in vitro cultivation offers a sustainable solution to enhance blackberry (Rubus spp.) production while reducing pathogen contamination during propagation. This study developed and validated protocols for in vitro cultivation and ex vitro acclimatization of the Tupy, Brazos, and Kiowa cultivars at the Instituto Tecnológico Superior de Los Reyes, Michoacán. A 20 min treatment with 2% sodium hypochlorite (NaOCl) reduced contamination by below 10% and achieved explant survival rates exceeding 95%. Temporary Immersion Systems (TIS) with four to six immersion cycles of 5 min each maximized survival (above 95%) while minimizing necrosis and hyperhydricity and increasing fresh mass. Shoot development was significantly enhanced with 2 mg L⁻¹ 6-benzylaminopurine, and 1 mg L⁻¹ indole-3-butyric acid promoted optimal root formation. Acclimatization success rates exceeded 90% in covered trays compared to significant losses in uncovered trays during early stages. These protocols enabled robust plant development and yields exceeding 10 t ha ⁻¹ during vegetative and reproductive stages, providing a scalable framework for sustainable blackberry production and broader applications in crop propagation. Full article

The rapid and accurate prediction of crop yield and the construction of optimal yield prediction models are important for guiding field-scale agronomic management practices in precision agriculture. This study selected the leaf area index (LAI) of winter wheat (Triticum aestivum L.) at four different stages, and collected canopy spectral information and extracted vegetation indexes through unmanned aerial vehicle (UAV) multi-spectral sensors to establish the yield prediction model under the condition of slow-release nitrogen fertilizer and proposed optimal fertilization strategies for sustainable yield increase in wheat. The prediction results were evaluated using random forest (RF), support vector machine (SVM) and back propagation neural network (BPNN) methods to select the optimal spectral index and establish yield prediction models. The results showed that LAI has a significantly positive correlation with yield across four growth stages of winter wheat, and the correlation coefficient at the anthesis stage reached 0.96 in 2018–2019 and 0.83 in 2019–2020. Therefore, yield prediction for winter wheat could be achieved through a remote sensing estimation of LAI at the anthesis stage. Six vegetation indexes calculated from UAV-derived reflectance data were modeled against LAI, demonstrating that the red-edge vegetation index (CI_{red edge}) achieved superior accuracy in estimating LAI for winter wheat yield prediction. RF, SVM and BPNN models were used to evaluate the accuracy and precision of CI_{red edge} in predicting yield, respectively. It was found that RF outperformed both SVM and BPNN in predicting yield accuracy. The CI_{red edge} of the anthesis stage was the best vegetation index and stage for estimating yield of winter wheat based on UAV remote sensing. Under different N application rates, both predicted and measured yields exhibited a consistent trend that followed the order of SRF (slow-release N fertilizer) > SRFU1 (mixed TU and SRF at a ratio of 2:8) > SRFU2 (mixed TU and SRF at a ratio of 3:7) > TU (traditional urea). The optimum N fertilizer rate and N fertilizer type for winter wheat in this study were 220 kg ha⁻¹ and SRF, respectively. The results of this study will provide significant technical support for regional crop growth monitoring and yield prediction. Full article

Vaccinium floribundum Kunth, also known as mortiño, is of cultural, gastronomic, pharmaceutical and ecological importance in the Andes due to its regenerative capacity to preserve vegetation after destructive fires. The main limitation for the production of mortiño fruits is that the plant has not been domesticated or cultivated, which could pose risks to the species and the paramos where it lives. In vitro culture is a crucial technique for propagating horticultural crops where factors such as the concentration, growth regulators, medium and explant parameters must be optimized to ensure the success of in vitro propagation techniques. This review uses the Prisma methodology, identifying 47 studies on the in vitro cultivation of Vaccinium, but only five studies on the domestication of V. floribundum Kunth using three in vitro cultivation techniques (axillary buds, seed germination and induced callogenesis) were published in Scopus and ScienceDirect. Therefore, the objective is to provide information on in vitro propagation techniques for the domestication of V. floribundum Kunth. Full article

Taro (Colocasia esculenta (L.) Schott) is the fifth largest rhizome crop, and it is widely distributed in tropical and subtropical areas in the world. Vegetative propagation with virus-infected corms can lead to cultivar degradation, yield decline, and quality deterioration. In this study, the shoot apical meristems excised from taro corms infected with dasheen mosaic virus, which belongs to the genus Potyvirus in the family Potyviridae, were cultured and treated with exogenous abscisic acid and high sucrose concentrations to induce micro-corm formation. Subsequently, candidate genes involved in micro-corm expansion were screened via transcriptome sequencing analysis. The results revealed that the shoot apical meristems could grow into adventitious shoots on the medium 1 mg/L 6-benzylaminopurine + 0.3 mg/L 1-naphthaleneacetic acid, and reverse transcription–polymerase chain reaction detection indicated that dasheen mosaic virus had been successfully eliminated from the test-tube plantlets. Moreover, 8% sucrose or 3% sucrose + 5 μM abscisic acid likewise induced taro corm formation, and genes related to cell division and the cell cycle, as well as starch and sucrose metabolism pathways, were significantly enriched during taro corm expansion. Furthermore, the cyclin-dependent kinases genes, cell cycle protein kinase subunit genes, and cyclin B2 genes, which are related to cell division and the cell cycle, were upregulated with abscisic acid treatment on the 3rd day. The sucrose synthase genes, β-amylase genes, glycogen branching enzyme genes, and soluble starch synthase genes, which are related to starch and sucrose metabolism, were upregulated on the 15th day, indicating that cell division largely occurs during taro corm formation, whereas carbohydrates are synthesized during taro corm expansion. Full article

Plant moisture content (PMC) serves as a crucial indicator of crop water status, directly affecting agricultural productivity, product quality, and the effectiveness of precision irrigation. Conventional methods for PMC assessment predominantly rely on destructive sampling techniques, which are labor-intensive and impede real-time monitoring. This study investigates silage maize cultivated in the Hexi region of China, leveraging multispectral data acquired via an unmanned aerial vehicle (UAV) to estimate PMC across different phenological stages. A stacked ensemble learning framework was developed, integrating Back Propagation Neural Network (BPNN), Random Forest Regression (RFR), and Support Vector Regression (SVR), with Partial Least Squares Regression (PLSR) employed for feature fusion. The findings indicate that incorporating vegetation indices into spectral variables significantly improved prediction performance. The standalone models demonstrated coefficient of determination (R²) values ranging from 0.43 to 0.69, with root mean square error (RMSE) spanning 0.61% to 1.43%. In contrast, the ensemble model exhibited superior accuracy, achieving R² values between 0.61 and 0.87 and RMSE values from 0.54% to 1.38%. This methodology offers a scalable, non-invasive alternative for PMC estimation, facilitating data-driven irrigation optimization in regions facing water scarcity. Full article

Kiwifruit, with its unique flavor, nutritional value, and economic benefits, has gained significant attention in agriculture production. Kiwifruit plants have traditionally been propagated without grafting, but recently, grafting has become a more common practice. A new and complex disease called Kiwifruit Vine Decline Syndrome (KVDS) has emerged in different kiwifruit-growing areas. The syndrome was first recognized in Italy, although similar symptoms had been observed in New Zealand during the 1990s before subsequently spreading worldwide. While kiwifruit was not initially grafted in commercial orchards, the expansion of cultivation into regions with heavy soils or other challenging environmental conditions may make grafting selected kiwifruit cultivars onto KVDS-resistant or -tolerant rootstocks essential for the future of this crop. Grafting is a common horticultural practice, widely used to propagate several commercially important fruit crops, including kiwifruits, apples, grapes, citrus, peaches, apricots, and vegetables. Grafting methods and genetic compatibility have a crucial impact on fruit quality, yield, environmental adaptability, and disease resistance. Achieving successful compatibility involves a series of steps. During grafting, some scion/rootstock combinations exhibit poor graft compatibility, preventing the formation of a successful graft union. Identifying symptoms of graft incompatibility can be challenging, as they are not always evident in the first year after grafting. The causes of graft incompatibility are still largely unknown, especially in the case of kiwifruit. This review aims to examine the mechanisms of graft compatibility and incompatibility across different fruit crops. This review’s goal is to identify potential markers and techniques that could enhance grafting success and boost the commercial production of kiwifruit. Full article

Cultivated yam (Dioscorea rotundata) is a staple tuber crop in West Africa which is mainly vegetatively propagated. Although the majority of yam cultivars flower, the control of their sexual reproduction remains largely unknown despite its importance for plant-breeding programs. While described as a dioecious species, yam has several monoecious (mix) cultivars that are often subject to spontaneous sex changes. This study aims to evaluate the impact of phytohormones on sex expression and flower development in cultivated yams D. rotundata. Exogenous applications of 1 mM 6-benzylaminopurine (BAP) and 1 mM methyl jasmonate (MeJa) were performed on seedlings of female (Gnidou, Anago), male (Flou) and mix (Katala and Laboko) cultivars. The mix cultivars produced monoecious, male and female plants while the female and male cultivars had rather stable sex. Our results showed that MeJa exhibited a significant masculinising effect in mix cultivars and induced inflorescence and flower malformations in female cultivars (56% in Gnidou and 37% in Anago). Most malformations were inflorescence branching and sterile flowers (non-differentiated ovary) with extra cycles of sepals. Moreover, MeJa reduced flowering time in the cultivars of all sexes and increased the number of inflorescences per plant as well as the number of flowers per plant. Our results showed that BAP reduced the flowering time, synchronized flowering in female plants and increased the number of inflorescences per plant in monoecious plants. However, our results did not allow for strong conclusions regarding the effect of BAP on sex expression due to the high proportion of female flowering in both the control and BAP-sprayed plants. Nevertheless, we did not observe any masculinising effect for BAP. Further research that would highlight hormone and homeotic gene interactions in flowering could be of key interest in understanding the hormonal control of sex in cultivated yams D. rotundata. Full article

Canopy water interception is a key parameter to study the hydrological cycle, water utilization efficiency, and energy balance in terrestrial ecosystems. Especially in sprinkler-irrigated farmlands, the canopy interception further influences field energy distribution and microclimate, then plant transpiration and photosynthesis, and finally crop yield and water productivity. To reduce the field damage and increase measurement accuracy under traditional canopy water interception measurement, UAVs equipped with multispectral cameras were used to extract in situ crop canopy information. Based on the correlation coefficient (r), vegetative indices that are sensitive to canopy interception were screened out and then used to develop canopy interception models using linear regression (LR), random forest (RF), and back propagation neural network (BPNN) methods, and lastly these models were evaluated by root mean square error (RMSE) and mean relative error (MRE). Results show the canopy water interception is first closely related to relative normalized difference vegetation index (R_△NDVI) with r of 0.76. The first seven indices with r from high to low are R_△NDVI, reflectance values of the blue band (Blue), reflectance values of the near-infrared band (Nir), three-band gradient difference vegetation index (TGDVI), difference vegetation index (DVI), normalized difference red edge index (NDRE), and soil-adjusted vegetation index (SAVI) were chosen to develop canopy interception models. All the developed linear regression models based on three indices (R_△NDVI, Blue, and NDRE), the RF model, and the BPNN model performed well in canopy water interception estimation (r: 0.53–0.76, RMSE: 0.18–0.27 mm, MRE: 21–27%) when the interception is less than 1.4 mm. The three methods underestimate the canopy interception by 18–32% when interception is higher than 1.4 mm, which could be due to the saturation of NDVI when leaf area index is higher than 4.0. Because linear regression is easy to perform, then the linear regression method with NDVI is recommended for canopy interception estimation of sprinkler-irrigated winter wheat. The proposed linear regression method and the R_△NDVI index can further be used to estimate the canopy water interception of other plants as well as forest canopy. Full article