Potato Research最新文献

{"title":"Enhancing Iron Content in Potatoes: a Critical Strategy for Combating Nutritional Deficiencies","authors":"Zain Mushtaq, Abdulrahman Alasmari, Cihan Demir, Mükerrem Atalay Oral, Korkmaz Bellitürk, Mehmet Fırat Baran","doi":"10.1007/s11540-024-09758-5","DOIUrl":"https://doi.org/10.1007/s11540-024-09758-5","url":null,"abstract":"<p>Despite recent advances in the prevention and control of nutritional deficiencies, estimates suggest that over two billion individuals worldwide are at risk for vitamin A, iodine and/or iron insufficiency. Pregnant women and small children are most at risk, and Southeast Asia and sub-Saharan Africa have very high incidence rates. Concerning public health are deficits in zinc, folate and the B vitamins, among other micronutrients. Micronutrient malnutrition, often referred to as hidden hunger, represents one of humanity’s most pressing challenges. Iron deficiency anaemia affects more individuals globally than any other prevalent disorder. However, iron supplementation can exacerbate infectious diseases, necessitating careful evaluation of iron therapy policies. In this review, we explore biofortification strategies to combat hidden hunger, considering recent medical and nutritional advancements. Enhancing iron content in edible plant parts can improve human nutrient status through crop consumption. Mineral and vitamin density in staple foods, particularly for impoverished populations, can be increased using traditional plant breeding or transgenic approaches, collectively known as biofortification. Microbial iron biofortification is especially valuable in developing countries where expensive supplements are unaffordable. Additionally, the current COVID-19 pandemic underscores the need for a robust immune system, with iron playing a crucial role in immune function enhancement.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"21 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141567558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Detection of Potato Disease Using an Enhanced Convolutional Neural Network-Long Short-Term Memory Deep Learning Model","authors":"Sarah A. Alzakari, Amel Ali Alhussan, Al-Seyday T. Qenawy, Ahmed M. Elshewey","doi":"10.1007/s11540-024-09760-x","DOIUrl":"https://doi.org/10.1007/s11540-024-09760-x","url":null,"abstract":"<p>Potato diseases pose a significant threat to farmers, impacting potato crops’ productivity, quality, and financial stability. Among the most notorious diseases is late blight, caused by <i>Phytophthora infestans</i>, famously responsible for triggering the Irish Potato Famine in the 1840s. Late blight swiftly devastates potato foliage and tubers, particularly in damp, humid conditions. Another common disease is early blight, attributed to <i>Alternaria solani</i>. This disease affects various parts of the potato plant—leaves, stems, and tubers. It mainly shows up in the form of dark stains around the center of a bull’s eye on the leaves, bringing down both the yield and the crop quality. A model consisting of a Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM) enhanced for potato disease detection was proposed in our paper. The dataset used was Z-score standardized before the training and testing process using the proposed CNN-LSTM model was started. The performance of the implemented model, CNN-LSTM, was analyzed alongside five traditional machine learning algorithms, namely Random Forest (RF), Extra Trees (ET), K-Nearest Neighbours (KNN), Adaptive Boosting (AdaBoost), and Support Vector Machine (SVM). Accuracy, sensitivity, specificity, F-score, and AUC were the metrics included in the evaluation, confirming the effectiveness of the models. The results of the experiments showed that our CNN-LSTM reached the highest accuracy at 97.1%.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"18 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141567559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical Gains from Growing Potato Under Contract Farming in Punjab, India","authors":"Pavneet Kaur, Naresh Singla","doi":"10.1007/s11540-024-09762-9","DOIUrl":"https://doi.org/10.1007/s11540-024-09762-9","url":null,"abstract":"<p>The persistence of agrarian crises in Punjab state of India has necessitated the policymakers to identify new institutional agri-businesses to make farm growth sustainable and inclusive. Contract farming in high-value crops such as potato is seen as one of the several ways to develop new market linkages with the farmers and improve farming income consistently through the dissemination of new production and post-harvest processing technologies. In this context, a comparative analysis of contract farmers associated with the PepsiCo company and non-contract farmers growing potato for local markets is carried out in Punjab to determine the empirical gains that accrue to contract farmers and the role of contract farming in farm diversification. The findings revealed that the company procures potatoes at farmers' fields through quad-partite and written contractual agreements, extends extension and training facilities at the farmers' doorstep, and provides yield-based incentives to the farmers. Contract farmers earned more profits than their counterpart non-contract farmers mainly due to their better price realization, although contract farmers had lower yields and higher cost of production than non-contract farmers. However, the imposition of the condition of growing at least 4 ha of area under potatoes led to the exclusion of small farmers and did not lead to diversification away from traditional crops to high-value crops such as potato. The study argues that the Punjab government needs to play a proactive role in facilitating the participation of small farmers through group contracts and Farmer Producer Organizations (FPOs) to enhance farmers' income and crop diversification through potato contract farming.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"25 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141567560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential Yield of Potato Under Global Warming Based on an ARIMA-TR Model","authors":"Cai Chengzhi, Wei Sha, Duan Shengnan, Cao Wenfang","doi":"10.1007/s11540-024-09745-w","DOIUrl":"https://doi.org/10.1007/s11540-024-09745-w","url":null,"abstract":"<p>As an important food crop in the world, potato has been attracting scholarly attention to improve its yield in the future, particularly under climate change. Therefore, analyzing the potential yield of potato as affected by global warming is of great significance to direct the production of crops worldwide. However, up to now, most research reports estimated the potential yield of potatoes by models which are based on the theory of production functions while there are few theoretical studies on the time-series approach based on stationary stochastic processes. Thus, in this paper, both average and top (national) yields of potato between 2021 and 2030 are projected creatively using an auto-regressive integrated moving average and trend regression (ARIMA-TR) model basing the projection on historic yields from 1961 to 2020 to explore the potential yield of the crop in the future; the effects of global warming on both average and top (national) yields of potato from 1961 to 2020 are analyzed using binary regression models in which global mean temperature is treated as the independent variable and the yield as the dependent variable, to reveal how climatic events drive the variation trend of these two types of yield. Our results show that between 2021 and 2030, the average yield of potato is projected to be from 21,234 to 23,773 kg/ha while the top yield ranges from 50,240 to 51,452 kg/ha; the average will approach from 42.26 to 46.20% of the top, or the gap between these two yields will be gradually narrowed in the ensuing decade; from 1961 to 2020, global warming exerts a positive effect on the average yield of potato with a quadratic function (<i>R</i>-squared = 0.772 and <i>F</i> = 96.417) more than on the top yield with an inverse function (<i>R</i>-squared = 0.568 and <i>F</i> = 76.201), which partly makes the gap between these two types of yields shrink. Our study concludes that for potato by 2030, the opportunities for improving global production should be dependent on both high- and low-yield countries as the average yield is in the main body of an <i>S</i>-shaped curve in the evolutionary trend in the long run. These insights provide the academic circle with innovative comprehension of the potential yield of potato for global food security under climate change.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"51 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141567561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laboratory Efficacy of Essential Oils Against Pectobacterium carotovorum Subsp. carotovorum and Pectobacterium atrosepticum Causing Soft Rot of Potato Tubers","authors":"Barbora Jílková, Jana Víchová, Ludmila Holková, Helena Pluháčková, Markéta Michutová, Martin Kmoch","doi":"10.1007/s11540-024-09743-y","DOIUrl":"https://doi.org/10.1007/s11540-024-09743-y","url":null,"abstract":"<p>The antibacterial activity of essential oils (EOs) from <i>Carum carvi</i>, <i>Cinnamomum zeylanicum</i>, <i>Cuminum cyminum</i>, <i>Eugenia caryophyllus</i>, <i>Foeniculum vulgare</i>, <i>Melaleuca alternifolia</i>, <i>Mentha</i> × <i>piperita</i>, <i>Origanum vulgare</i>, <i>Rosmarinus officinalis</i> and <i>Thymus vulgaris</i> was tested against <i>Pectobacterium carotovorum</i> subsp. <i>carotovorum</i> (<i>Pcc</i>) and <i>Pectobacterium atrosepticum</i> (<i>Pa</i>), which cause soft rot of potato tubers. In disc diffusion, minimum inhibitory concentration and minimum bactericidal concentration (MBC) tests, cinnamon EO was found to be most effective against both bacteria. The inhibition zones ranged from 20.46 to 29.58 mm for a concentration of 100 μL/mL. The minimum inhibitory concentration was 0.5 μL/mL, and MBC was between 0.5 and 5 μL/mL. The higher sensitivity of bacteria was manifested in clove (<i>Pcc</i> and <i>Pa</i>), mint (<i>Pcc</i>), oregano (<i>Pa</i>) and thyme (<i>Pa</i>) EOs. Rosemary EO was the least effective. The results of the in vivo test were not entirely consistent with those of the in vitro tests. The most significant antibacterial effect was achieved with mint EO. The treatment of potato tuber discs with mint EO at a concentration of 3 μL/mL for <i>Pcc</i> and 3–10 μL/mL for <i>Pa</i> was 100% effective. The efficacy of the essential oils of caraway (5–10 μL/mL), thyme (10 μL/mL) and oregano (5 μL/mL) also ranged from 95.7 to 99.7%. Based on the results of the in vivo test, it may be recommended that mint EO and potentially caraway, oregano and thyme EOs be further tested for pickling potato tubers against bacteria of the genus <i>Pectobacterium</i>.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"67 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141514242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Enhanced Long Short-Term Memory Recurrent Neural Network Deep Learning Model for Potato Price Prediction","authors":"Sarah A. Alzakari, Amel Ali Alhussan, Al-Seyday T. Qenawy, Ahmed M. Elshewey, Marwa Eed","doi":"10.1007/s11540-024-09744-x","DOIUrl":"https://doi.org/10.1007/s11540-024-09744-x","url":null,"abstract":"<p>Regarding the potato market, pricing fluctuations are a significant factor, and unfortunately, they cause many issues for producers and consumers. It happens to result in food insecurity and economic instability. This study brings in an advanced LSTM-RNN model built to predict potato prices, which might alleviate the mentioned challenges. We gathered a historical potato price database and other economic variables, normalized by the Z-score normalization method to ensure all the data was consistent and credible. The model’s effectiveness was benchmarked against five traditional machine learning models: we used K-nearest neighbor, random forest, support vector regressor, linear regression, and gradient boosting regressor to classify isolated households and determine their socioeconomic status. The empirical data implied that our proposed LSTM-RNN model was more efficient than all comparison models, leading to an <i>R</i>² value of 0.98. The paper not only substantiates the plausibility of applying deep learning to address the agricultural market prediction issue but also serves as a guideline noting the capabilities of the LSTM-RNN routine in improving the decision-making processes for the farmers participating in the sector. This model supports a sustainable food system and a balanced economy by bringing price stability integral to designing and implementing strategies to address food security.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"13 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141514241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Edible Coating with Encapsulated Antimicrobial and Antibrowning Agents via the Emerging Electrospinning Process and the Conventional Spray Drying: Effect on Quality and Shelf Life of Fresh-Cut Potatoes","authors":"Zoi Tsakiri-Mantzorou, Christina Drosou, Alexandra Mari, Marina Stramarkou, Konstantina Theodora Laina, Magdalini Krokida","doi":"10.1007/s11540-024-09756-7","DOIUrl":"https://doi.org/10.1007/s11540-024-09756-7","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The present study investigated the impact of edible coatings containing encapsulated antimicrobial and antibrowning agents on the quality and shelf life of fresh-cut potatoes. Polysaccharides extraction from potato peels using ultrasound/microwave-assisted extraction (UAE/MAE) was optimized via central composite design (CCD) and response surface methodology (RSM). Maximum starch recovery (216.55 ± 10.37 mg amylose/g potato peel) was achieved with UAE. Starch, pectin, and chitosan combination was the basis of the coatings. Rosemary essential oil (REO) and ascorbic acid (AA) were selected as antimicrobial and antioxidant agents, incorporated in free or encapsulated form via spray drying (SP) and electrospinning (EL). Over 14 days at 4 °C, coated potatoes exhibited improved appearance, reduced browning, enzyme activity, weight loss, hardness, and microbial load compared to controls. Notably, the potato starch-pectine coating with encapsulated REO/AA effectively inhibited browning and microbial growth, demonstrating the potential of edible coatings to enhance freshness and shelf life in fresh-cut potatoes.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"11 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141508749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Potato Disease Classification Using a Metaheuristics Algorithm for Deep Learning: A Novel Approach for Sustainable Agriculture","authors":"El-Sayed M. El-Kenawy, Amel Ali Alhussan, Doaa Sami Khafaga, Mostafa Abotaleb, Pradeep Mishra, Reham Arnous, Marwa M. Eid","doi":"10.1007/s11540-024-09755-8","DOIUrl":"https://doi.org/10.1007/s11540-024-09755-8","url":null,"abstract":"<p>Potato is a food crop at a global scale, bearing a hefty importance for the food security and nutrition of millions of people worldwide. Nonetheless, some obstacles have to be overcome in the cultivation of potatoes, such as susceptibility to a number of diseases that affect quality and yield. Thus, sound disease management approaches are critical to protect potato crops and support maximum production. In this perspective, optimization techniques are vital in improving disease classification accuracy, thus helping in early detection and timely intervention. In this research, we suggest the hybridization of the Greylag Goose Optimizer (GGO) with the Grey Wolf Optimizer (GWO), which is called GGGWO, for the optimization of convolutional neural network (CNN) models for potato disease classification. Through our approach, we are seeking to enhance precision and timeliness in the diagnosis of diseases that will eventually lead to the development of appropriate crop management practices and sustainable agriculture. The performance of the GGGWO-CNN model is assessed in terms of accuracy and is compared to other optimization algorithms using statistical testing methods like ANOVA and Wilcoxon signed rank tests. The results exhibit the excellent performance of the GGGWO-CNN model with an accuracy of 0.9904 and a sensitivity of 0.9421 in identifying potato diseases accurately, highlighting its potential to aid farmers and general agriculture practitioners. Utilizing optimization techniques and CNN models, our research helps in the development of precision agriculture as well as the improvement of resilient potato cropping systems. The proposed method’s approach provides an exciting way of dealing with the problem of potato diseases. It provides an excellent platform for carrying out further studies on improving agricultural decision-making processes aimed at better crop health and productivity.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"41 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141508750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Titanium Dioxide Nanoparticles in Irrigation Water on Potato Growth and Yield","authors":"Ali Mawof, Shiv O. Prasher, Kevin J. Wilkinson, Stéphane Bayen, Emma C. Anderson, Saji George","doi":"10.1007/s11540-024-09754-9","DOIUrl":"https://doi.org/10.1007/s11540-024-09754-9","url":null,"abstract":"<p>A 2-year (2017 and 2018) field lysimeter study was carried out to examine the effect of titanium dioxide nanoparticles (TiO₂ NPs) in irrigation wastewater on soil characteristics and potato (<i>Solanum tuberosum</i> L.) yield. Potatoes were planted in lysimeters (1.00 m × 0.45 m) in sandy soil and subjected to four treatments: freshwater (FW), wastewater (WW), freshwater + TiO₂ NPs (FW + NP) and wastewater + TiO₂ NPs (WW + NP), in triplicate. Potato tubers were harvested at maturity (120 days after planting). Both the TiO₂ NPs (with/without 1 mg L⁻¹ TiO₂ NPs) and irrigation treatments (FW <i>vs.</i> WW) had a significant effect (<i>p </i>≤ 0.05) on chlorophyll content; however, they had little or no effect on soil physicochemical parameters (cation exchange capacity (CEC), pH and soil organic matter (SOM)), plant growth parameters (plant height, above-ground and root fresh weight) or yield (tuber weight, number of tubers and tuber grading). For both years, the total nitrogen content of the leaves increased consistently together with leaf chlorophyll content. Furthermore, tuber yield under FW, WW and WW + NP treatments were higher in the first year than in the second, likely due to higher growing season temperatures in the second year. This study furthers the knowledge on the impact of TiO₂ NPs on plant growth by showing that at 1 mg L⁻¹, irrigation water can increase greenness without inhibiting plant growth and yield. In addition, the potato plants, irrigated with water containing TiO₂ NPs, did not become infected with early and late blight diseases either year.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"14 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141508752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Morphological and Pathological Variability of Intra-field Rhizoctonia solani Isolates in a Rice-Potato Rotation and their Sensitivity to Fungicides","authors":"Mehi Lal, Shivam Yadav, Sorabh Chaudhary, Sanjeev Sharma, Manoj Kumar","doi":"10.1007/s11540-024-09746-9","DOIUrl":"https://doi.org/10.1007/s11540-024-09746-9","url":null,"abstract":"<p><i>Rhizoctonia solani</i> is a destructive soil-borne plant pathogen having a vast host range that infects various agricultural and horticultural crops. A total of 25 <i>R. solani</i> isolates were collected from a field of rice-potato rotation to determine their morphological variability, mycelial compatibility, cross-infectivity and fungicide sensitivity. Considerable variability in cultural and morphological features was observed among <i>R. solani</i> isolates collected from rice and potato crops. Rice isolates grew faster than potato isolates and hyphal width of both the host isolates varied from 6.67 to 9.37 μm. Significant variability was observed in sclerotial characteristics such as sclerotia colour, size, intensity and sclerotial distribution pattern on the Petri plates. Most of the isolates from both hosts produced micro (≤ 1.25 mm) size sclerotia and only few isolates produced macro (&gt; 1.25 mm) size sclerotia. The sclerotial colour of most of the rice isolates was brown and some isolates exhibited black sclerotial colour. All the potato isolates produced brown-coloured sclerotia. Hyphal interaction studies revealed that potato isolates belonged to AG-3 and rice isolates belonged to AG1-IA group. Mycelial compatibility studies showed that 80.7% of the pairings were non-compatible, while 19.3% of the pairings exhibited a compatible interaction. Cross-infectivity revealed that <i>R. solani</i> potato isolates did not infect rice plants whereas rice isolates showed a varied degree of pathogenicity on potatoes and <i>Rhizoctonia</i>-like atypical symptoms were observed on the tuber surface. The EC₅₀ and EC₉₀ values of representative isolates from both hosts exhibited considerable variation with regard to sensitivity level against fungicides thifluzamide 24% SC and mancozeb 50% + carbendazim 25% WS. The outcomes of this study will help to develop management strategies and breeding programmes on varietal evaluation for effective management of <i>Rhizoctonia</i> diseases of potatoes and rice.</p>","PeriodicalId":20378,"journal":{"name":"Potato Research","volume":"33 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141508751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}