Potato Research最新文献

India is the second largest producer of potato in the world. The present study aims at examining the growth, sustainability, market and export situations of Indian potatoes during the period 1966–1967 to 2019–2020 using time series data of area, production, productivity, market prices, export amount and values in major growing states, markets and importing countries, respectively. Descriptive, sustainability, price dependence analysis is taken up to study the internal production and market situation. Box Jenkin’s ARIMA methodology is taken up to forecast the future area, production and productivity of India and the major growing states. To analyse the export behaviour, Markov Chain analysis is taken up. The study reveals that although there have been growths in area, production and productivity, the average productivity is far below the world highest productivity. Sustainability analysis reveals differential sustainability status of major growing states with respect to area, production and productivity. Forecasting of area, production and productivity reveals that India is expected to produce 56 million tonnes of potato from 2.2 million hectares of area with an expected productivity of 25.24 tonnes per hectare, much below the present highest productivity of the world. Study of seasonality of prices and markets cointegration reveals seasonal and lag dependence of prices with only unidirectional market cointegration. The Markov Chain analysis reveals that excepting Saudi Arabia and Oman there will be reduced import of Indian potatoes by other major importing countries. Thus, the findings of the whole study suggest augmentation in the process of production and marketing (both internal and international) for Indian potatoes.

The most widely cultivated varieties of potato in Chile are Patagonia and Asterix. However, there is scarce information about the physical–chemical characteristics of starches isolated from these potatoes. In this study, the starches from two potato varieties, Patagonia and Asterix, were isolated and characterised. In addition, an exploratory study of the preparation of starch nanoparticles from these potato varieties by the flash nanoprecipitation method was performed. The morphology (scanning electron microscopy and optical microscopy), crystallinity (X-ray diffraction), thermal (differential scanning calorimetry), rheological (rapid visco analyser) and hydration properties are reported. Starches from Patagonia potato (PPS) and Asterix potato (APS) were isolated by the wet milling method. PPS and APS had similar starch content on fresh weight basis, around 15%. The granule particle sizes of Chilean potato starches showed a unimodal distribution, in the range of 10–90 µm. Amylose content varied between 23.8 and 25.3% for APS and PPS, respectively, making them normal starches. Gelatinisation temperature and enthalpy were 58.6 and 60.1 °C and 15.5 and 17.8 J/g for APS and PPS, respectively. Significant differences were obtained in the pasting parameters of Chilean potato starches; the rapid visco analyser pasting profiles of PPS exhibited a large viscosity peak and APS did not show a distinctive viscosity peak. The pasting profiles of APS are required for food products such as soups and sauces. Spherical nanoparticles were prepared from the Chilean potato starches by flash nanoprecipitation method using two micromixer devices: confined impinging jet mixer and multi-inlet vortex mixer. The size of potato nanoparticles depended on micromixer device, and the lowest particle size (100 nm) was obtained when the confined impinging jet mixer was used. The nanoparticles from Chilean potato starches are potential raw materials for the nutraceutical, food and pharmaceutical fields.

Raising quality hybrid potato true seedlings — derived from hybrid true potato seeds (TPS) — for field transplanting is a critical aspect contributing to the success in cultivating field-transplanted hybrid potato seedling-based crops. Various critical seedling vigour attributes must be defined and enhanced to improve plant performance as well as plant response and adaptation to field conditions after field transplanting. Moreover, additional attributes besides leaf number and stem length should be defined to design selection criteria for “transplantability” of potato seedlings. To assess these attributes and their robustness under different environmental conditions, seedlings of hybrid genotypes were raised under contrasting daylengths, light intensities and temperature regimes, and combinations of these factors, and the effects of these factors (or factor combinations) on seedling vigour and its attributes were quantified. Increased light intensity and daylight integral (DLI) enhanced leaf parameters and increased biomass under long-day conditions, but seedlings did not show conclusive responses under short-day conditions in most attributes. Higher temperatures increased biomass and constant day and night temperatures enhanced compaction of shoot architecture as did higher light intensities — to a greater extent. These results highlight additional seedling vigour attributes including leaf area parameters and seedling biomass which should be utilised to determine “transplantability” of hybrid potato seedlings. Additionally, the results provide a starting point for further research on optimising hybrid seedling production for field transplanting.

Characterizing potato cultivars is essential for diagnosing the specific production and management requirements. Employing techniques that facilitate rapid, objective, and cost-effective identification of various aspects of plant physiology is crucial for generating this valuable information. In this study, our goal was to identify different potato cultivars across three distinct phenological phases utilizing reflectance spectroscopy within the visible and near-infrared ranges. Reflectance spectra were measured using a portable spectrometer on leaves obtained from five different potato cultivars. We constructed classification models to determine the accurate classification percentages for each cultivar within specific phenological stages. General trends in the reflectance spectra were observed, which were consistent across all five cultivars within the measured range. During the vegetative phase, there was a uniform reflectance of around 5% in the green region. This value experienced a slight decrease during the flowering phase and subsequently rose to approximately 12% during the senescence phase. In the near-infrared (NIR) range, a reduction in reflectance from 50 to 30% was noted during the flowering phase, followed by a cultivar-dependent increase towards senescence. The specific wavelengths identified in the spectra enabled the accurate classification of plants from each cultivar across the vegetative, flowering, and senescence phases. The classification rates were notably high, with a success rate of 87% for Var. Paola, 96% for Var. Paysandú, 93% for Var. Violeta, and 100% for cv. 448 and 440. The Var. Paola exhibited superior correct classification rates, ranging from 85% for Paysandú and Violeta, 90% for cv. 440, to 100% for cv. 448. The characterization of potato cultivars using spectroscopy techniques yields valuable information that serves as fundamental input for precision agriculture systems.

In Ethiopia, fertilizer consumption has shown a linear increment. One-year-on-farm research was conducted in the Amhara region to identify major determinant nutrient types for potato (Solanum tuberosum L.) growth and tuber yields in Amhara region. The experiment was conducted in 2021 under rain fed conditions on eight farm fields in the Amhara region classified under three major potato-growing domains (Quarit-Yilmana Densa, Dembecha, and Baja-Sekela). A total of ten treatments (NPSZnBK, NPSZnK-B, NPSBK-Zn, NPZnBK-S, NPSZnB-K, NSZnBK-P, PSZnBK-N, NPS, NP, and control) were evaluated in the experiment. The treatments were laid out in a randomized complete block design (RCBD) and replicated three times. The improved potato variety “Gudenie (CIP-386423–13)” was used as a test crop. Urea, TSP (triple super phosphate), KCl (muriate of potash), MgSO₄ (magnesium sulfate), EDTA, and Borax were used for the sources of nitrogen (N), phosphorus (P), potassium (K), sulfur (S), zinc (Zn), and boron (B) nutrients, respectively. Except for urea, all fertilizer sources were applied once at planting, while urea was applied in three equal splits at different crop stages (planting, flowering, and tuber initiation). Before planting, one composite soil sample from each experimental site was taken at 0–20 cm depth, and analysed for some important soil parameters. Both potato yield components and biological yield (tuber yield) were taken. Marketable and total tuber yields of potato showed highly significant differences among treatment means at each experimental site as well as from combined analysis in the study domains. The main driving force for the occurrence of significant differences between treatment means in the ANOVA was due to omitting N and P nutrients. Tuber yield of potato showed quick and automatic responses to omitting N followed by omitting P. However, both marketable and total tuber yields did not show any significant differences, either due to adding or omitting S, Zn, B, and K nutrients. This showed that currently N and P nutrients are major potato yield-limiting nutrients in Amhara region, Ethiopia.

India is an agrarian country, and 70% of the rural population is engaged in agriculture for their livelihood. Consumption of potato is being part of the daily routine for many consumers in India and world. The area, production, and productivity of potato in India has been increasing, and export of potato also has been increasing. The production of quality potato is still an issue faced by the Indian farmers due to lack of credit to purchase quality seed tubers, fertilizers, pesticides and so on. These issues are tackled through contract farming which provides the credit, fertilizer, quality seed tubers, harvesting support and technical support to the farmers. PepsiCo is one of the biggest companies involved in contract farming in India for potato production and enhances the quality of potato production for their processing unit which provides quality of product to the consumers as well as good remuneration to the farmers through contract farming. Small and marginal farmers involve in contract farming to meet the global demand. Nowadays, potato production under contract farming has been increasing but violation of the contract by the companies is also increasing. Intervention of the government is required to monitor the contract between potato farmers and companies to avoid conflicts and violations. The involvement of the government in contract farming enhances the quality of the product for the consumers as well as the quality of lifestyle for the farmers through the availability of fair remuneration for their potato production.

This study analyzed and forecasted potato production in eight major South Asian countries from 1961 to 2028 using advanced time series and machine learning approaches. Annual potato production data was modelled with autoregressive integrated moving average (ARIMA), state space, and extreme gradient boosting (XGBoost) models. The models were trained on 1961–2009 data and evaluated on a 2010–2021 validation set. On the training set, XGBoost showed the best performance. However, on the validation set, ARIMA and state space models significantly outperformed XGBoost, indicating issues with overfitting. The ARIMA models produced the lowest forecast errors for Afghanistan, Bangladesh, China, and Myanmar. Meanwhile, state space models were optimal for India, Nepal, Pakistan, and Sri Lanka, demonstrating that no one approach was uniformly best. The top performing models forecast potato production up to 2028, Afghanistan’s production is expected to remain stable at around 860–862 thousand metric tons. Bangladesh’s output is forecasted to stay constant at 9887 thousand metric tons. In contrast, China is predicted to see a steady increase from 94,625 to 96,193 thousand metric tons. India’s production is anticipated to grow significantly from 54,704 to 62,396 thousand metric tons. Conversely, Myanmar’s production is projected to decline from 460 to 426 thousand metric tons. Nepal’s output is expected to steadily increase from 3395 to 4011 thousand metric tons. Pakistan’s production is forecasted to rise substantially from 5573 to 7045 thousand metric tons. Lastly, Sri Lanka’s potato production is projected to experience a modest increase from 77 to 84 thousand metric tons. These forecasts reflect the different levels of potato demand, consumption, and trade in each country, as well as the effects of climate change, pests, and diseases on potato yields. The rigorous comparative application of advanced time series and machine learning techniques provides valuable data-driven insights into future South Asian potato supply. The forecasts can assist food security planning and agricultural policymaking in the region.

Fifteen commonly grown potato varieties in Meghalaya, consisting of nine local and six commercial varieties, were screened for their susceptibility against potato tuber moth, Phthorimaea operculella. Based on four parameters, oviposition preference, feeding preference, percentage of survival and number of mines, the varieties were categorised into highly susceptible (HS), moderately susceptible (MS), slightly susceptible (SS), and slightly resistant (SR). Among the 15 varieties, two varieties, Kufri Jyoti and Kufri Megha, were highly susceptible (HS) and only one variety, Lah Ksain, was slightly resistant (SR) based on all the tested parameters. Number of eggs laid had a significantly positive correlation with number of eyes and number of mines. The varieties preferred for feeding had more mines compared to the less preferred ones as indicated by the high positive value of the correlation coefficient between penetrating larvae percentage and number of mines. Overall, the results indicated that the local varieties performed comparatively better than the commercial varieties in terms of the parameters studied.

Abstract

The paper is devoted to study the dynamics of the infestation of potatoes owing to the occurrence of late blight disease over two successive years (2014 and 2015) in the Terai region of West Bengal. Nonlinear models have been fitted on the potato late blight data (i.e. percent disease index data). The goodness-of-fit tests on different models have been performed by the application of the following criteria, namely coefficient of determination, mean absolute error, mean absolute percentage error, average relative predictive error, Akaike’s information criterion and Bayesian information criterion, respectively. The validation of the models has been carried out by the Shapiro-Wilk test and running test for conforming to the assumptions of normality and independence of the errors, respectively. Based on the application of the goodness-of-fit tests on the models, it was found that for 2014 and 2015, cubic and Gompertz models provided the best-fitted models based on the above sets of data, respectively. Using the best-fitted models referred to above, the values of two important parameters, namely (1) maximum rate of growth of the disease and (2) maximum disease severity, were determined. For the year 2014, it was observed that the maximum rate of growth of the disease occurred at 31 days after planting (DAP) and the maximum disease severity occurred at 48 DAP; however, even after the attainment of the maximum rate of the growth of the disease, the severity of the disease may increase, so it can be concluded that an additional application of fungicidal spray is necessary (when the disease is located in the field). On the other hand, for 2015, we observed that the maximum rate of growth of the disease occurred at 43 DAP. It indicates that any protection measure should be adopted at this stage (here, 43 DAP). Importantly, in an unprotected field, the late blight disease grows indefinitely as time advances infinitely.

Potato snacks are a promising nutrient delivery strategy, given their global popularity. This study aimed to compare potato cultivars (S.M Kaghan, Rocco, Kuroda, and Desiree) for chips production. Proximate, physicochemical, microbial, and sensory evaluations were conducted on chips made from these varieties. Rocco had the highest moisture content (1.39%), followed by Kuroda (1.35%). Significant variations (p < 0.05) in fat, carbohydrate, ash, fiber, pH, and acidity were observed between control and all varieties. Mold counts were highest in Rocco (1.11 log CFU/g), while S.M Kaghan, Desiree, and Kuroda had counts of 1.04, 0.85, and 0.99 log CFU/g, respectively. Total plate count increased significantly during storage, reaching 3.27, 3.38, 3.51, 3.62, and 3.72 log CFU/g on days 0, 15, 30, 45, and 60, respectively. Sensory evaluation indicated that the chips were well-accepted, with Desiree variety scoring highest in all attributes.