Potato Research最新文献

Potatoes are an essential crop cultivated in numerous regions around the globe, but they frequently get impacted by diseases that lower their production and quality. To ensure the crop reaches its maximum potential, controlling the diseases in the initial or early stages is necessary. Recent developments in deep learning algorithms have demonstrated significant improvements in predicting agricultural diseases at various stages. However, contemporary deep learning models frequently exhibit real-world performance and generalization capabilities limitations. This study proposes an ensemble convolutional neural network model that combines the three most widely used models, VGG16, MobileNetV2, and ResNet50, to increase generalizability and improve accuracy in the classification of potato crop diseases. The proposed model is trained on a large dataset containing 6644 images of potato leaves, which is constructed by merging three different publicly available datasets. These datasets are originally collected from three distinct locations around the globe (the USA, Ethiopia, and Pakistan). The model aims to achieve improvement in accuracy and maintain generalizability for classifying potato fungal diseases. The proposed ensemble architecture achieved an accuracy of 98.49%, surpassing the individual models. In this study, a web-based interface is developed for the evaluation of the model. The proposed model is tested on this web interface with the images obtained through the Google Image Search Engine. A plant pathologist supervised the selection of images and the pre-processing of the dataset. The results of the evaluation indicate that the model will perform better when deployed in real-world situations.

Potato (Solanum tuberosum) is a major staple food crop susceptible to numerous pathogens and pests. Utilising biotic elicitors offers a promising integrative approach for crop management, potentially reducing losses and chemical treatments. One such elicitor, an inactive suspension of Xanthomonas axonopodis (XTH), has previously been shown to enhance potato resistance against pathogens, like the bacterium causing blackleg disease. However, the underlying mechanism of this resistance remains unclear. Thus, this study investigated the effect of XTH on the defence metabolism in potato plants and compared it to the response elicited by exogenous salicylic acid (SA), a well-known defence-signalling molecule. We analysed the expression of marker genes for defence response pathways, including JA/ET-responsive genes (StPin2, StERF1, and StJAZ1/TIFY10A-like) and SA-responsive genes (StPR-1b, StPR-2, and StChtA). Potato plants were treated with either SA and XTH, and both treated and systemic leaves were analysed. XTH upregulated all analysed genes locally and systemically within the first 24 h, except for StChtA. The XTH-mediated upregulation of StPAL and Pin2 genes suggests this elicitor might trigger responses via the jasmonic acid pathway. Exogenous application of SA induced the systemic expression of StPR, StChtA, StJAZ1/TIFY10A-like, and StERF in potato plants. Our results indicate that XTH modulates the expression of defence-related genes in potato plants by simultaneously activating both the salicylic acid and jasmonic acid signalling pathways. This dual activation suggests that XTH could be a valuable resource for crop management in potato cultivation, potentially reducing the need for chemical pesticides.

The root lesion nematode (RLN), Pratylenchus penetrans (Cobb) Filipjev and Schuurmans-Stekhoven, a migratory endo-parasite has impacted potato yield and tuber’s quality across the world including Pakistan. The present study was designed to investigate the susceptibility of 16 potato cultivars to P. penetrans under screen house and field conditions. Population densities of P. penetrans in roots, soils and tuber peels of each cultivar were assessed. Findings revealed that three potato cultivars Lal Moti, Rodeo, and Raco were found “Resistant”, six cultivars Semi, Pirol, Ronaldo, Abelia, 5-Zena red and L-R were found “Moderately Resistant” and remaining cultivars were found “Moderately Susceptible or Susceptible”. Significantly (P = 0.00) lower number of nematode larvae or adults was observed within roots (53.75) and 100 g tubers peel (10.0) of cultivar Lal Moti. A marked reduction in the number of necrotic lesions per root system (1.25), 100 g tuber peel (3.0) and minute size necrotic lesions on tubers (1.06) and root system (0.62) were evident in cultivar Lal Moti. It was the only cultivar that sustained high inoculum pressure under field conditions, restricted the reproduction factor (Rf = 0.02) of RLN in roots and yielded significantly higher number of tubers (13.1 per plant) with maximum yield (35.5 g per three random tubers) as compared to Rodeo, Raco and L-R cultivars. A strong negative correlation between the number of egressed nematodes from peels or soil and weights of potato cultivars was evident with r = − 0.97 and − 0.87 under screen house and field conditions, respectively. Cultivar resistance offers a potential sustainable solution for the migratory RLN in potatoes and could be effectively integrated into nematode management strategies.

Potato virus Y (PVY) is a significant pathogen affecting potato and other crops globally. Current research on PVY primarily concentrates on strain analysis and protein interactions with the host. However, studies on PVY replication in vitro remain limited, primarily due to the absence of a dedicated in vitro replication system for PVY. This study aimed to develop an in vitro replication system mediated by the nuclear inclusion protein B (NIb) of PVY. Through IPTG gradient experiments, we determined that the optimal expression concentration of MBP-NIb is 0.2 mM. The results indicate that the optimal temperature for NIb expression in Escherichia coli is 37 °C, yielding approximately 10% solubility, which is sufficient for subsequent affinity chromatography using the MBP tag. The purified MBP-NIb specifically recognizes the 3′ terminal region of the positive-sense RNA and the 5′ terminal region of the negative-sense RNA of PVY in vitro, facilitating the synthesis of complementary strands of the viral RNAs. To our knowledge, this is the first successful establishment of an in vitro replication system for PVY. This system will advance the study of PVY replication mechanisms.

The tomato leaf miner Tuta absoluta Meyrick is the most serious pest of potato worldwide. In the present study, we explored an alternate approach to induce resistance in potatoes against T. absoluta by engineering Jaburetox-2Ec, an insecticidal peptide derived from an isoform of urease from Jack bean (Canavalia ensiformis L.). The construct was developed by cloning a PCR-amplified fragment of Jaburetox-2Ec (270 bp) in a pBIN61 vector under the control of a 35S promoter and was named pBIN-JBTX. Furthermore, the recombinant plasmid expressing Jaburetox-2Ec was transformed into potato cv. Lady Olympia using Agrobacterium tumefaciens strain EHA105. The results showed the proper integration of the T-DNA region in primary transformants. Quantitative PCR assays showed the independent transgenic lines had enhanced transcript levels of Jaburetox. The leaf biotoxicity assays were performed by releasing pre-starved 2nd, 3rd, and 4th instar larvae of T. absoluta on transgenic potato plants. As a result, depending on the larval stage, the mortality rate of larvae feeding on transgenic plants ranged from 11 to 33%. Additionally, it was found that larvae feeding on control plants gained more weight than those feeding on transgenic plants. Besides that, deformities in larvae feeding on transgenic plants were also recorded. Overall, the results exhibited the insecticidal activity of Jaburetox 2-Ec against T. absoluta. The transgenic lines can be used as a source of germplasm for an efficient potato breeding programme.

Genetic gain in potato breeding is limited by the heterozygous tetraploid genome of cultivated potato. Recent efforts to breed potato at the diploid level promise to improve genetic gain and allow more straightforward genetics and introgression breeding. Diploid F1 hybrid potato breeding relies on the ability to create diploid inbred lines via repeated self-fertilization. However, self-fertilization of diploid potato is hampered by a gametophytic self-incompatibility system encoded by the S-locus that prevents fertilization by self-pollen. Nonetheless, self-compatible diploid potato genotypes exist and have been used to create inbred lines. The S-locus inhibitor (Sli) gene is a dominant gene that provides strong self-compatibility in diploid potato and was previously mapped to Chromosome 12. While the Sli gene has already been identified and characterized, the most tedious challenge was to develop the optimal phenotyping methods and genetic populations preceding the cloning of this gene. To this end, we developed an effective phenotyping protocol to identify suitable parents and create diploid populations segregating for Sli. We show that an accurate phenotyping method is crucial to discriminate between confounding fertility factors and self-compatibility. In addition, we found that the Sli locus shows extreme segregation distortion on Chromosome 12. Finally, we used these insights to develop three F1 populations that segregate for Sli, which we later used for the identification of the Sli gene.

Agricultural commodity prices have unique characteristics and tend to fluctuate more due to seasonality, inelastic demand, and production uncertainty. Additionally, the considerable volatility observed in time series data amplifies the complexity, presenting a notable challenge. This paper addresses the intricate challenges associated with forecasting agricultural commodity prices, which are characterized by seasonality, inelastic demand, and production uncertainty. We introduce deep learning (DL) models to navigate the complexities of nonlinear and nonstationary price data in the agricultural sector. Despite the success of DL models in handling intricate data, their original design for tasks like image processing and natural language processing necessitates specialized architectures for time series forecasting. To meet this demand, we evaluate the neural basis expansion analysis for interpretable time series forecasting (N-BEATS) model, a novel architecture designed specifically for time series forecasting, on weekly potato price data collected from the Farrukhabad market in Uttar Pradesh between January 2003 and August 2023. A comparative analysis is conducted with three other models: convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent units (GRU) using the same dataset. Various forecasting evaluation criteria, including root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), are employed to assess and compare the models’ performance. Empirical results demonstrate that the N-BEATS model consistently outperforms the other models across all evaluation criteria. Furthermore, the Diebold–Mariano (DM) test confirms the significant forecasting advantage of the N-BEATS model over the other sequential models. This research showcases the potential of the N-BEATS model in enhancing the precision of agricultural commodity price forecasting, with implications for stakeholders such as farmers and planners. The findings contribute to advancing the understanding of deep learning applications in the agricultural domain, offering a promising avenue for more accurate and reliable forecasting methods.

Potato (Solanum tuberosum L.) is a nutritious starchy tuber crop consumed as a staple food in most potato growing countries. Its productivity and production are limited by climate change; thus, it is of utmost importance to tap into the diversity of germplasm resources, therefore, diversifying the potato varieties available for production. The objectives of this study were to determine the phenotypic diversity among the selected Agricultural Research Council-Vegetable, Industrial and Medicinal Plants (ARC-VIMP) potato varieties for tuber yields and processing quality and to determine the correlation between measured traits. Two imported and 22 local potato varieties were planted in three different environments in South Africa. Significant (P < 0.001) differences in the tested varieties across all environments were observed for all measured traits. High broad-sense heritability (> 0.6) was observed for most of the traits, except for fry colour and the yield of unmarketable tubers. Nine ARC varieties and three standard varieties were associated with high tuber yield and quality traits, indicating their suitability for the fresh market and processing industry. Variety Mondial and five ARC varieties were associated with high tuber yield, indicating their suitability for the fresh market. Varieties released between 2004 and 2021 had high tuber yield, dry matter and specific gravity compared to the standard varieties and varieties released between 1980 and 1999, although there were slight differences in the magnitudes of their traits measured. These varieties could be recommended for commercial production for specific markets and for use as potential parents for further genetic improvement of the potato crop.

Potato yields in the Netherlands are highly variable. Although variability in yield has previously been attributed to several crop management factors, part of the variability remains unexplained. It is hypothesized that part of this unexplained yield variability is influenced by seed potato origin, encompassing where and under what conditions seed potatoes have been cultivated. In this study, we investigated the effect of seed potato origin on crop characteristics and tuber yield in interaction with and in comparison to planting date and field type in a two-year on-farm experiment on a large-scale potato farm. We evaluated three different seed potato origins of the variety Fontane, three different planting dates (early, intermediate, late), and two different field types (wet rainfed and dry irrigated). Origin significantly affected the number of stems per plant and the number of tubers per stem in both years. This resulted in a significant effect of origin on the number of tubers per plant in the first year. In that year, the origin with the lowest number of tubers per plant also produced the highest yield of tubers larger than 50 mm. Despite these (small) effects of seed potato origin on crop characteristics, origin did not significantly affect gross and marketable yield. Moreover, there was no interaction between origin and planting date and/or field type. However, planting date and field type had a significant effect on yield. Ware potato yield in the wet rainfed field was up to 17 t ha⁻¹ higher than in the dry irrigated field, and late planting resulted in a yield reduction of up to 10 t ha⁻¹. We conclude that for maximizing ware potato yield of the variety Fontane in the Netherlands, the effects of planting date and field type outweighed the effects of seed tuber origin.

This work focuses on the study of the physicochemical changes that take place during a short germination period in flours and starches of the Creole potato tuber. To this end, the changes in the composition of flours and the structural, thermal, vibrational, functional and pasting changes of the isolated starches from germinated potatoes were evaluated during the 12-day germination period, measured every 4 days. The water absorption index (WAI) and the swelling powder showed no significant changes. Germination resulted in a decrease in fat and ash content, but an increase in protein and amylose content. Scanning electron microscopy (SEM) showed no changes in the morphology of the starch during germination. X-ray diffraction showed that isolated Creole potato starch contains nanocrystals with hexagonal crystal structure, which are not affected by germination. Differential scanning calorimetry (DSC) shows a shift of the gelatinization peak to the right, which could be attributed to the concentration effect. The pasting profiles of the isolated starches show no significant changes, indicating that the starch granules do not suffer any external damage due to the enzymatic process during germination and that the final viscosity behaves like a hydrogel.