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Novel Carbon quantum dots-graphite composite ink-based Screen-printed electrodes (CQDs/SPEs) were used to assemble a highly sensitive electrochemical aptasensor against chlorpyrifos (CPF). The aptasensor showed a broad linear range from 1 pM (0.445 ng/ml) to 500 nM (0.22 mg/ml) with a detection limit (LOD) 0.834 pM (0.37 ng/ml); sensitivity 21.39 μA pM−1 cm− 2 and with good linearity of R2 = 0.973. Moreover, the aptasensor's showed better selectivity among few other pesticides. Further, the aptasensor electrode showed high stability for five months when stored at 4 °C. In the final step, the aptasensor's ability to identify CPF in real samples was evaluated on spiked potato (Solanum tuberosum) extract samples. Potato extract spiked with CPF in the electrochemical aptasensing platform showed excellent linearity of R2 = 0.981. The developed aptasensor showed good response to without spiked potato extract with increasing volumes. Hence, the developed aptasensor demonstrated reasonable applicability in real food and agriculture samples. • Chlorpyrifos (CPF), an organophosphate pesticide, is known for detrimental effects on environment raising global health concern. • Electrochemical based disposable screen printed aptasensor is developed for the detection of chlorpyrifos pesticide. • The CQDs/SPE aptasensor was fabricated using carbon quantum dots (CQDs) through drop cast method. • The aptasensor exhibited a wide linear range (1 pM-500 nM) with LOD (0.834 pM) and high sensitivity (21.39 μA pM−1 cm− 2). [ABSTRACT FROM AUTHOR]

[Display omitted] • Fabrication of paper disc interfaced immunodevice for detecting diverse biomarker. • Highly sensitive and affordable disease detection tool. • Validated with range of spiked and real samples. • Universal sensing ability was accessed using C-reactive protein and potato viruses. The detection of specific biomarkers is used in various phases of the diagnosis of plant and human diseases, from prognosis to monitoring. Herein, we report a Prussian blue nanocube-modified immunodevice interfaced with a paper disc for the detection of plant biomarkers via streptavidin-biotin recognition. The detection ability of the immunodevice was assessed using Potato virus X as a model biomarker and analyzed using cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy. The immunodevice displayed excellent performance for Potato virus X detection with a detection limit of 0.92 nM (3S/N). The selectivity of the fabricated Potato virus X immunodevice was investigated using closely associated antigens, such as potato aucuba mosaic virus, Potato virus Y, and Potato virus A. The Potato virus X immunodevice exhibited ∼ 90 % recovery in spiked complex plant samples with a relative error of ∼ 9 %. Furthermore, the immunodevice was used to screen for Potato virus X in 10 samples from potato tubers and leaves. The paper-disc-interfaced immunodevice was also evaluated by detecting other biomarkers, such as potato aucuba mosaic virus in plant diseases and C-reactive protein in human ones. This immunodevice may allow the on-site monitoring of diverse biomarkers by simplifying the current point of care diagnostic tools. [ABSTRACT FROM AUTHOR]

The potato is a key crop in addressing global hunger, and deep learning is at the core of smart agriculture. Applying deep learning (e.g., YOLO series, ResNet, CNN, LSTM, etc.) in potato production can enhance both yield and economic efficiency. Therefore, researching efficient deep learning models for potato production is of great importance. Common application areas for deep learning in the potato production chain, aimed at improving yield, include pest and disease detection and diagnosis, plant health status monitoring, yield prediction and product quality detection, irrigation strategies, fertilization management, and price forecasting. The main objective of this review is to compile the research progress of deep learning in various processes of potato production and to provide direction for future research. Specifically, this paper categorizes the applications of deep learning in potato production into four types, thereby discussing and introducing the advantages and disadvantages of deep learning in the aforementioned fields, and it discusses future research directions. This paper provides an overview of deep learning and describes its current applications in various stages of the potato production chain. [ABSTRACT FROM AUTHOR]

Within a few years of the establishment of the convict settlement at Sydney Cove, the potato became one of the staple crops of the population due to its relatively high yield and the prior experience of the convicts and free settlers with growing the crop. In 1894, Henry Tryon described a new disease in southern Queensland that caused rapid wilting of plants, a ring of slightly translucent tissue just below the surface of affected tubers, oozing of a thick, white fluid from the 'eyes', and ultimately rotting of the tubers. It soon became known as 'Tryon's disease'. He found that a microbe (bacterium) was always associated with affected tubers and stems, provided a very brief description of the bacterial cells and named the microbe Bacillus vascularum solani. A few years later the American scientist Erwin Frink Smith wrote a paper on a new disease (brown rot) of solanaceous plants including the potato and tomato, in which he called the causal agent Pseudomonas solanacearum , now known as Ralstonia solanacearum. Smith dismissed Tryon's prior claim to the discovery of the disease with some of his comments being personal and scathing. Tryon had the last word, however, cloaking his response in restrained and somewhat convoluted tones. In 1894, the Queensland government entomologist, and later vegetable pathologist, Henry Tryon (1856–1943) discovered a new disease that caused potato tubers to become rotted and putrid. He consistently found bacterial cells in a thick mucilaginous gum in the vascular tissues of wilted stems and infected tubers, and gave it the name Bacillus vascularum solani. The American bacteriologist Erwin Frink Smith would not accept Tryon's discovery, instead naming the causal agent Pseudomonas solanacearum. That bacterium, now called Ralstonia solanacearum is a significant plant pathogen worldwide. Photograph by an unknown person. [ABSTRACT FROM AUTHOR]

Traditional potato grading in China relies mostly on manual sorting, which is labor-intensive, time-consuming, costly, and inefficient. To enhance the operational performance of potato-grading devices, this paper focuses on optimizing the slide rail structure, which is the key component of a self-developed first-generation potato-grading device. A five-factor, three-level orthogonal experiment was designed, with the experimental factors being the height of the horizontal slide rail, angle of the first-stage inclined slide, angle of the second-stage inclined rail, chain horizontal movement speed, and conveyor belt speed. The indoor experiments were conducted using grading accuracy and grading efficiency as the experimental indicators. On the basis of the analysis of the orthogonal experiment results, two relatively optimal solutions were obtained, and validation experiments were conducted. The validation results show that when the height of the horizontal slide rail was 185 mm, the angle of the first-stage inclined rail was 4°, the angle of the second-stage inclined rail was 2.5°, the horizontal movement speed of the chain was 700 mm/s, and the movement speed of the conveyor belt was 275.60 mm/s, the performance of the movable rotating plate (MRP)-type grading device for potatoes reached its optimum. At this point, the grading accuracy was 94.88%, and the grading efficiency was 13.9477 t/h. Compared with the first-generation grading device, the optimized grading device achieved an improvement of 3.84% in grading accuracy and 12.94% in grading efficiency. The research methodology provided in this paper serves as a reference for the performance optimization of potato-grading devices. [ABSTRACT FROM AUTHOR]

Vegetative propagation of potatoes makes it possible for potato viruses to be transmitted through tubers. Potato virus A (PVA) is one of these viruses, which belongs to the Potyvirus genus in the Potyviridae family. Potato tuber yield can be reduced by 30–40% by PVA alone. Losses can be further exacerbated by potato virus X and/or potato virus Y infection. PVA is transmitted primarily by several species of aphids in non-persistent manner. With the aim of resolving this problem, we developed one-step reverse transcription-recombinase polymerase amplification (RT-RPA), a highly sensitive and cost-effective method for detecting PVA in both potato tubers and leaves. Detection and amplification are performed using isothermal conditions in this method. There was good amplification of the coat protein gene in PVA with all three primers tested. To conduct this study, a primer set that can amplify specific 185 base pair (bp) product was selected. PVA detection was optimized by 30-min amplification reactions, which showed no cross-reactivity with other potato viruses. A simple heating block or water bath was used to amplify PVA product using RT-RPA at a temperature range of 38–42 °C. In comparison to conventional reverse transcription-polymerase chain reaction (RT-PCR), the newly developed RT-RPA protocol exhibited high sensitivity for both potato leaves and tuber tissues. Using cellular paper-based simple RNA extraction procedure, the virus was detected in leaf samples as efficiently as purified total RNA. We also found that combining LiCl-based RNA precipitation with cellular paper discs allowed us to successfully optimize RNA extraction for one-step RT-RPA for detecting PVA in tubers. Tests using this simplified one-step RT-RPA method were successfully applied to 300 samples of both leaves and tubers from various potato cultivars. In our knowledge, this is the first report of an RT-RPA assay utilizing simple RNA obtained from either cellular disc paper or LiCl coupled with cellular disc paper to detect PVA. As a result, this method was equally sensitive and specific for detecting PVA in potatoes. The developed RT-RPA assay is more versatile, durable, and do not require highly purified RNA templates, thus providing an effective alternative to RT-PCR assays for screening of germplasm, certifying planting materials, breeding for virus resistance, and real-time monitoring of PVA. [ABSTRACT FROM AUTHOR]

Plastic film mulching technology occupies a prominent position in China's agricultural production and plays an important role in improving crop yields, which can increase farmers' income and ensure national food security. As the current residual film recycling mechanism is incomplete, the accumulation of residual film in the soil has gradually increased, and the problem of residual film pollution has posed a serious threat to agricultural production and the natural environment. Ridge mulching cultivation is one of the main planting patterns for grain and oil crops, such as peanuts, potatoes, and maize, in China. In this paper, the planting patterns, mulching conditions, characteristics, and distribution of residual film of the typical ridge mulching crops, such as peanut and potato, were analyzed. The merits and demerits of various kinds of residual film recycling machines and the application status and operation quality of peanut and potato residual film recycling machines are summarized. Problems and suggestions for the mechanized recycling of residual film were raised. This study may provide ideas for the development of residual film mechanization recycling of ridge mulching crops. The aim of this study is to propose practical solutions by analyzing the current status and existing problems of mechanized residual film recovery in order to reduce residual film pollution, protect the environment, and achieve sustainable agricultural development. [ABSTRACT FROM AUTHOR]

The Netherlands has a world-leading position in potato breeding, but little is known about the factors that led to this success. This paper analyses the factors that have influenced the development of potato breeding in the Netherlands. This study is based on research of the grey and scientific literature and interviews with various representatives from the Dutch potato breeding sector. We distinguish four periods: (i) Before 1888, no potato breeding in the Netherlands existed whereas in other countries first crosses occurred. (ii) 1888–1940, more individuals started breeding out of interest and hobby to overcome the commonly observed degeneration of potato. (iii) 1940–1967 the emergence of a corporate set up of breeding by private companies collaborating with small breeders. (iv) 1967–present, towards full-fledged breeding industry supported by the new Seeds and Planting Materials Act (ZPW) in 1967 including the breeders' rights. Many factors including cultural practices, diseases, and market that determine the strategy of breeding have been analysed. The development is most of all 'crop driven' to maintain the level of production. But it was also 'export driven' leading to the development of an export-oriented seed potato sector. The conclusion is that three elements were dominant in the development of a strong potato breeding sector: (1) the broad cooperation among all players in the potato chain, (2) the design of the institutional infrastructure, and (3) the remuneration of the breeding work through legislation regarding plant breeders' rights. The study ends with an outlook on future trends, one of them leading from an open to a more closed business culture. [ABSTRACT FROM AUTHOR]

Potato machinery has become more intelligent thanks to advancements in autonomous navigation technology. The effect of crop row segmentation directly affects the subsequent extraction work, which is an important part of navigation line detection. However, the shape differences of crops in different growth periods often lead to poor image segmentation. In addition, noise such as field weeds and light also affect it, and these problems are difficult to address using traditional threshold segmentation methods. To this end, this paper proposes an end-to-end potato crop row detection method. The first step is to replace the original U-Net's backbone feature extraction structure with VGG16 to segment the potato crop rows. Secondly, a fitting method of feature midpoint adaptation is proposed, which can realize the adaptive adjustment of the vision navigation line position according to the growth shape of a potato. The results show that the method used in this paper has strong robustness and can accurately detect navigation lines in different potato growth periods. Furthermore, compared with the original U-Net model, the crop row segmentation accuracy is improved by 3%, and the average deviation of the fitted navigation lines is 2.16°, which is superior to the traditional visual guidance method. [ABSTRACT FROM AUTHOR]

Appropriate water supply is crucial for high-yield and high-quality potato tuber production. However, potatoes are mainly planted in arid and semi-arid regions in China, where the precipitation usually cannot meet the water demand throughout the growth period. In view of the actual situation of water shortage in these areas, to monitor the water status of potato plants timely and accurately and thus precisely control the irrigation are of significance for water-saving management of potatoes. Hyperspectral remote sensing has unique advantages in diagnosing crop water stress. In this paper, the canopy spectral reflectance and plant water content were measured under five irrigation treatments. The spectral parameters that respond to plant water content were selected, and a hyperspectral water diagnosis model for leaf water content (LWC) and aboveground water content (AGWC) of potato plants was established. It was found that potato tuber yield was the highest during the entire growth period under sufficient irrigation, and the plant water content showed a downward trend as the degree of drought intensified. The peak hyperspectral reflectance of potato plant canopies appeared in the red wavelength, where the reflectance varied significantly under different water treatments and decreased with decreasing irrigation. Six models with sensitive bands, first-order derivatives, and moisture spectral indices were established to monitor water content of potato plants. The R2 values of partial least squares regression (PLSR), support vector machine (SVM), and BP neural network (BP) models are 0.8418, 0.9020, and 0.8926, respectively, between LWC and hyperspectral data; and 0.8003, 0.8167, and 0.8671, respectively, between the AGWC and hyperspectral data. These six models can all predict the water content of potato plants, but SVM is the best model for predicting LWC of potato plants. These results are of great significance for guiding precision irrigation of potato plants at different growth stages. [ABSTRACT FROM AUTHOR]

The study assesses the gender implications of a target product profile for table potato in Kenya. Breeding programs mostly emphasize farmers’ trait requirements and rarely pay attention to other value chain actors’ preferences. This partially contributes to the low uptake of improved varieties. Therefore, efforts are required to assess the gender implications of crop product profile proposals during development, testing, and dissemination. In this paper, we assess the gender implications of traits targeted by a potato breeding program in Kenya using the G+ tools. The study applies the G+ product profile tool to examine the instances the selected traits may exacerbate gender disparity along four domains: unpaid labor, access to employment opportunities, requiring extra inputs and control over benefits. We use mixed methods including a review by social scientists, key informant interviews and a multistakeholder workshop to gather insights from female and male farmers, breeders, and other stakeholders. Findings show that pest, disease resistance, and shelf-life traits benefit women and men in the target customer segments. On the other hand, earliness, dry matter, and yield could increase drudgery for women. The traits increase demand for women’s unpaid labor during harvesting, sorting and food preparation time while also displacing women from profitable nodes. We recommend that gender-responsive strategies accompany the release of the target variety to mitigate inequities and enhance adoption. [ABSTRACT FROM AUTHOR]

Aiming at the problems of large error and redundancy in the multi-node data acquisition of multi-greenhouse photo growth environmental information, a three-level fusion algorithm based on adaptive weighting, an LMBP network, and an improved D-S theory is proposed. The box-and-line graph method recognizes the original data and then replaces it based on the mean value method; the air temperature, humidity, and light intensity measurements are unbiased estimations of the true value to be estimated, so the first level of fusion chooses the adaptive weighted average algorithm to find the optimal weights of each sensor under the condition of minimizing the total mean-square error and obtains the optimal estimation of the weights of the homogeneous sensors of a greenhouse. The Levenberg–Marquardt algorithm was chosen for the second level of fusion to optimize the weight modification of the BP neural network, i.e., the LMBP network, and the three environmental factors corresponding to "suitable", "uncertain" and "unsuitable" potato growth environments were trained for the three environmental factors in the reproductive periods. The output of the hidden layer was converted into probability by the Softmax function. The third level is based on the global fusion of evidence theory (also known as D-S theory), and the network output is used as evidence to obtain a consistent description of the multi-greenhouse potato cultivation environment and the overall scheduling of farming activities, which better solves the problem of the difficulty in obtaining basic probability assignments in the evidence theory; in the case of a conflict between the evidence, the BPA of the conflicting evidence is reallocated, i.e., the D-S theory is improved. Example validation shows that the total mean square error of the adaptive weighted fusion value is smaller than the variance of each sensor estimation, and sensors with lower variance are assigned lower weights, which makes the fusion result not have a large deviation due to the failure of individual sensors; when the fusion result of a greenhouse feature level is "unsuitable", the fusion result of each data level is considered comprehensively, and the remote control agency makes a decision, which makes full use of the complementary nature of multi-sensor information resources and solves the problem of fusion of multi-source environmental information and the problem of combining conflicting environmental evaluation factors. Compared with the traditional D-S theory, the improved D-S theory reduces the probability of the "uncertainty" index in the fusion result again. The three-level fusion algorithm in this paper does not sacrifice data accuracy and greatly reduces the noise and redundancy of the original data, laying a foundation for big data analysis. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop a precise collision model of potatoes falling onto a separation sieve to assess their damage characteristics. A viscoelastic‐plastic mechanics model is created by integrating the collision process with the potato soil separation device. Test factors include fall height, potato mass, fall direction, and varieties. Potato deformation and damage volume serve as evaluation indices in single‐factor tests to explore their relationships with these factors. The model analyzes the collision loading and unloading process, studying relationships between parameters and test factors, examining the potato collision damage mechanism. Predictive equations for potato damage volume based on fall height, potato mass, and plasticity ratio λp are derived: V1 = 1606λp–537, V2 = 4751λp–2087, and V3 = 12617λp–5303. This study provides a theoretical foundation for analyzing potato collision damage and offers technical references for optimizing potato harvesting machinery. Practical applications: Damage resulting from the mechanical harvesting process significantly impacts the quality and economic worth of the tubers. Currently, research on constructing a mechanical model of potatoes, treating them as viscoelastic plastic bodies, and integrating the collision process with potato soil separation devices is limited. Thus, the objective of this paper is to investigate the correlation between various test factors and potato damage via drop tests, and to establish a viscoelastic–plastic mechanical model. Additionally, the study further explored the correlation between model parameters and tuber damage, resulting in the establishment of a mathematical model for predicting the extent of damage. This study provides a theoretical basis for an in‐depth analysis of the collision damage mechanism of potato, and a technical reference for the design and optimization of potato harvesting machinery. [ABSTRACT FROM AUTHOR]

Potatoes are developed vegetatively from tubers, and therefore potato virus transmission is always a possibility. The potato leafroll virus (PLRV) is a highly devastating virus of the genus Polerovirus and family Luteoviridae and is regarded as the second-most destructive virus after Potato virus Y. Multiple species of aphids are responsible for the persistent and non-propagating transmission of PLRV. Due to intrinsic tuber damage (net necrosis), the yield and quality are drastically diminished. PLRV is mostly found in phloem cells and in extremely low amounts. Therefore, we have attempted to detect PLRV in both potato tuber and leaves using a highly sensitive, reliable and cheap method of one-step reverse transcription-recombinase polymerase amplification (RT-RPA). In this study, an isothermal amplification and detection approach was used for efficient results. Out of the three tested primer sets, one efficiently amplified a 153-bp product based on the coat protein gene. In the present study, there was no cross-reactivity with other potato viruses and the optimal amplification reaction time was thirty minutes. The products of RT-RPA were amplified at a temperature between 38 and 42 °C using a simple heating block/water bath. The present developed protocol of one-step RT-RPA was reported to be highly sensitive for both leaves and tuber tissues equally in comparison to the conventional reverse transcription-polymerase chain reaction (RT-PCR) method. By using template RNA extracted employing a cellular disc paper-based extraction procedure, the method was not only simplified but it detected the virus as effectively as purified total RNA. The simplified one-step RT-RPA test was proven to be successful by detecting PLRV in 129 samples of various potato cultivars (each consisting of leaves and tubers). According to our knowledge, this is the first report of a one-step RT-RPA performed using simple RNA extracted from cellular disc paper that is equally sensitive and specific for detecting PLRV in potatoes. In terms of versatility, durability and the freedom of a highly purified RNA template, the one-step RT-RPA assay exceeds the RT-PCR assay, making it an effective alternative for the certification of planting materials, breeding for virus resistance and disease monitoring. [ABSTRACT FROM AUTHOR]

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Simple Summary: Crop switching is an important climate change adaptation strategy. New crops may need to be cultivated to provide food security as traditional staple crops become less suited to the changing climate in the bread baskets of many countries. For example, potato farming in the Philippines is being scaled up to supplement the cultivation of rice to meet the needs of a growing population. Since new crops introduced for this purpose can also be vulnerable to invasive pests, it is necessary to develop methods for planning pest management strategies that consider the complex interactions that can occur in farm ecosystems. In this paper, we develop a graph theoretic model for assessing pest management options for the prospective case of the entry of the Colorado potato beetle in potato farms in the Philippines. Two biological control agents and use of chemical pesticides are considered as alternative strategies. The model results indicate that the biological control strategies outperform the use of chemical pesticides. The concurrent use of both biological control agents could be less effective due to competition between the two species. Crop shifting is considered as an important strategy to secure future food supply in the face of climate change. However, use of this adaptation strategy needs to consider the risk posed by changes in the geographic range of pests that feed on selected crops. Failure to account for this threat can lead to disastrous results. Models can be used to give insights on how best to manage these risks. In this paper, the socioecological process graph technique is used to develop a network model of interactions among crops, invasive pests, and biological control agents. The model is applied to a prospective analysis of the potential entry of the Colorado potato beetle into the Philippines just as efforts are being made to scale up potato cultivation as a food security measure. The modeling scenarios indicate the existence of alternative viable pest control strategies based on the use of biological control agents. Insights drawn from the model can be used as the basis to ecologically engineer agricultural systems that are resistant to pests. [ABSTRACT FROM AUTHOR]

Motivation: Crop diseases pose a critical threat to global food security, causing substantial agricultural yield losses. Manual disease identification is labor-intensive and requires expertise, hindering timely and accurate detection. Problem Gap: Traditional methods for identifying plant diseases are time-consuming and demand specialized knowledge. The need for a more efficient, automated, and accurate approach is evident to minimize crop losses and ensure food security. Contribution: This research paper addresses the challenge of plant disease detection by proposing a novel approach that combines image processing and deep learning techniques. The primary contribution is a sophisticated deep neural network ensemble model, which integrates Residual Network, MobileNet, and Inception models. This ensemble architecture is designed to maximize accuracy and robustness in disease classification. The model is trained on an extensive dataset containing images of both healthy and infected potato leaves. It accomplishes the precise categorization of leaves into three classes: healthy potato leaves, infected potato leaves (two classes). The model's proficiency lies in its ability to discern intricate leaf features, colors, and types, enabling it to differentiate between healthy and potentially diseased leaves. This research makes a significant contribution to the development of automated disease detection systems. By bridging the gap between manual identification and advanced technology, it presents a promising solution for early disease detection and prevention. Ultimately, this approach can foster increased agricultural productivity, ensuring enhanced food security on a global scale. Results: Results demonstrate the proposed model's effectiveness, achieving an impressive overall accuracy of 98.86%. This high accuracy attests to the model's competence in precisely detecting and classifying potato diseases. By harnessing the potential of ensemble-based deep learning and image processing, this research introduces an innovative tool for agriculturalists and researchers. [ABSTRACT FROM AUTHOR]

Summary: Potato is a tuber that, due to its great variety, is available in the markets all year round. Moreover, it is a widely consumed product worldwide on the account of its affordability and versatility. Therefore, studying it in depth is significant from not only a nutritional or economic point of view, but also for considering its potential environmental impact. In this paper, a Life Cycle Assessment (LCA) model is developed to assess the environmental impact of a model 5 kg bag of fresh washed potatoes. It considers all phases of potato processing, from the time the potato enters the facility until it leaves the gate (gate‐to‐gate LCA). The phase of the process with the greatest environmental impact is the cleaning and classification phase, mainly due to the significant consumption of water used in the cleaning process. The general consumption and storage phases are also relevant environmental impact phases to consider. In the case of these phases, the electricity consumption resulting from the operation of the facilities and product cooling is particularly noteworthy. After establishing the critical points, based on the environmental impact perspective, this paper proposes three measures to reduce the environmental impact of the process. The application of these three measures would reduce the environmental impact by 40% in environmental impact categories such as acidification or by 32% in the global warming category. [ABSTRACT FROM AUTHOR]

Sustainable food and agriculture is emphasized in recent times to provide for present and future generations with a lesser impact on the environment. Equal importance is given to environmental impact assessment of crop production and related processes to understand their effect on the environment and natural resources and formulate measures and policies to mitigate the same. Water footprint assesses the impact of products and processes on freshwater resources. This paper is an attempt to review available research on water footprint assessment of root and tuber crops and their products majorly potatoes, cassava and sweet potatoes. Root and tuber crops are gaining importance as major food security crops and are a more sustainable alternative to cereal crops in terms of water footprint. Apart from this, root and tuber crops (majorly, cassava and potato) are also gaining importance as feedstocks for biofuel production; however, they have a higher water footprint than sugar crops (sugar beet, sugar cane) used. Further research is required on the water footprint assessment of root and tuber crops especially crops other than potato, cassava and sweet potato and their products to help to achieve their full potential as sustainable food and energy crops. Efforts to develop ecocrop models to assess the suitability of tuber crops in different agroecological locations and effective utilization of green water to achieve more crop per drop and to reduce the water footprint are to be strengthened. [ABSTRACT FROM AUTHOR]

Food tourism includes various activities and attractions linked to food. Potatoes can also be also linked to tourism, or food tourism as testified by special Victorian Potato Industry Tour organized in and around Melbourne, Australia or Rural Community Tourism in the Potato Park; a tour around Cusco, Peru; various culinary events dedicated to potatoes in Slovenia and many others. This paper contributes to the knowledge on tourism and specifically food tourism by proposing to "open" a new niche of research based on specific foods or their ingredients, which up to now seems to have touched only a very few specific foods (or drinks) and associated ingredients—for instance, the case of grape/wine is exemplar. However, many other specific foods or ingredients could be singularly one-by-one) researched to examine their role in tourism. This paper discusses the role in tourism/food tourism of a "humble tuber", the potato. This is a desktop research which draws on previous literature, organizational and institutional documents and information and data, such as the list of museums around the world. The aim is to analyse the knowledge from various disciplines linking the potato to tourism to understand the various ways in which it can directly or indirectly have a role in tourism. The article presents the potato including its (social) history, gastronomy in relation to tourism/food tourism. The article argues that the potato should be promoted given its various uses and universality of application as a food and as an ingredient. [ABSTRACT FROM AUTHOR]

The combined fertilizer application is a strategy that combines both organic and inorganic plant nutrients to achieve higher crop productivity, prevent soil degradation and thereby aid encounter future food supply needs. The main objective of this paper is to review the role of combined fertilizer application on soil fertility, growth and yield of potato. This paper is done by assessing various kinds of published and unpublished materials and relevant information from different literature sources like libraries, research report, journals, books and Internet center. It has integrated use of organic and inorganic fertilizer affects the tuber yield and its attributing characters like an average number of tuber/hills, average tuber weight/hill, marketable tuber number and total dry matter yield. The use of farmyard manure and vermicompost along with inorganic fertilizers is superior to the application of either farmyard manure or vermicompost alone. Application of organic manure along with inorganic fertilizer increased organic carbon, available P and K. But the application of inorganic fertilizer alone had no significant effect on the fertility status of the soil. The reports revealed that integrated use of organic manure and reduced rates of inorganic fertilizer significantly improved potato productivity and improved the fertility status of the soil and could save inorganic fertilizer for sustainable potato production in potato growing areas. [ABSTRACT FROM AUTHOR]

SITE SPECIFIC is a farming management practice with the potential to address management challenges, this approach leverages precise and timely information on agricultural resources to observe and measure variability in field crops. Site -Specific management zones one of the most important pillars of precision agriculture. This technology is designed to enhance management practices by tailoring agricultural treatments to specific production zones within a field, thereby conserving resources, protecting the environment, and improving crop quality. This paper aims to developed spatial modeling for Site-Specific Management Zones based on soil and plant parameters. This work was done in Agrofood Company with an area approximately 18.69 hectares (ha) planted with potato crop (DITTA variety) in winter session 2019. 21 soil samples were taken before planting the crop and 21 plant samples were taken during the three growth stages based on the grid system, Soil and plant variability maps were produced based on Geostatistical Analysis of laboratory analyses of the samples. Spatial Model was developed to delineate site-specific management zones using ArcGIS 10.8, the input factors to developed this model were soil maps for Nitrogen (N), Phosphors (P), Potassium (K), pH, electrical conductivity (ECe), calcium carbonate (CaCO3) and soil organic carbon (SOM), plant maps for NPK, Chlorophyll a, Chlorophyll b, Carotenoids (Car) yield data maps and normalized difference vegetation index (NDVI) to create Site -Specific management zones for the study area. The results showed that management zones were classified into two zones, which zone (I) with an area 10.94 Hectares and its was characterized by high crop yield and good soil parameters, on the other hand zone (II) with an area 7.75 hectares and it was characterized by low crop yield, low soil and plants parameters. [ABSTRACT FROM AUTHOR]

The effectiveness of agroecological management strategies (AEMS) in controlling bacterial wilt caused by Ralstonia solanacearum species complex (RSSC) remains a critical question. A quantitative review was conducted based on publications reporting agroecological bacterial wilt management practices under on‐station or on‐farm field conditions in electronic libraries, without geographical restrictions, on tomato, pepper, eggplant and potato. After applying inclusion and exclusion criteria, 48 papers were retained, resulting in 644 and 146 observations of bacterial wilt incidence (BWI) and yield, respectively. The effectiveness of AEMS for each crop was evaluated based on BWI and crop yield. The effect size was calculated as the natural logarithm of the response ratio, and confidence intervals were determined by bootstrapping. Varietal control, biological control (used of biological control agents) and combinations of many AEMS were the most reported practices, both under on‐station and on‐farm conditions. The use of plant extracts (Thymus spp., Crotalaria spp.), grafting, solarization, soil amendments (manure, compost) and crop rotations (with maize, beans) were also reported. All AEMS significantly reduced bacterial wilt incidence and increased yields compared to the untreated plots. Grafting, combinations of control methods, varietal control and biological control were the most effective agroecological practices in reducing BWI and increasing yield in tomato and eggplant. Varietal control was the most effective compared to biological control on pepper. The effectiveness of AEMS also varied with crop susceptibility and origin, climatic zone and soil acidity. This study highlights the potential of AEMS in reducing BWI and increasing crop yield in infested soils. [ABSTRACT FROM AUTHOR]

Potato virus S (PVS) is a noteworthy threat to the propagation of healthy seed potatoes. Accurate and speedy detection is critical for effective PVS management. In the present study, an isothermal-based one-step reverse transcription-recombinase polymerase amplification (RT-RPA) approach was developed to detect PVS infection in potato leaves and tubers. A primer set based on the coat protein gene successfully amplified a 158 bp product out of three primer sets examined. The amplification reaction took less than 30 min to complete with no account of cross-reactivity with major potato viruses. Additionally, amplification of RT-RPA products was performed on the heating system and/or water bath at 38–42 °C. The results of sensitivity analysis revealed that one-step RT-RPA has shown 100 times higher sensitivity than routine RT-PCR for the detection of PVS in infected leaves. Furthermore, ten times higher sensitivity of RT-RPA was observed in infected tubers. The methodology was simplified further by the use of template RNA extracted using a cellular disc paper-based extraction method that detected the PVS more effectively than purified total RNA. PVS was detected in 175 samples (leaves and tubers each) of several potato varieties using this innovative technique. To our acquaintance, this is the first report of one-step RT-RPA using a basic RNA extract derived through cellular disc paper that is significantly sensitive and precise for PVS detection in potatoes. The advantages of one-step RT-RPA in terms of proficiency, robustness, and the availability of a highly pure RNA template make it an attractive choice for seed accreditation, resistance breeding, and field inspections. • A single step RT-RPA has been developed for the detection of PVS in potato leaves and tubers. • The RPA technique was standardized with simple RNA extract which altogether showed higher sensitivity than other PCR assays. • The method was validated using 175 field samples of infected potato that demonstrated its suitability for large scale use. [ABSTRACT FROM AUTHOR]

Continuous improvements in potato harvesting and storage techniques in recent years have reduced external potato damage such as shatter or skinning. However, the internal tuber damage caused by mechanical stress, i.e. blackspot, cannot be sufficiently reduced with conventional development tools such as field trials. Due to the approximately two-day duration of the blackspot development following the mechanical stress, it is offen unclear in which process step and under what environmental conditions the damage occurs. Particle simulation of agricultural harvesting processes offier extensive opportunities to improve machine processes and reduce harvesting losses. Using the Discrete Element Method (DEM), it is possible to gain a deep understanding of the harvesting and transportation processes of potatoes. The DEM represents potato tubers as particles and machine components as geometry elements. The geometry elements can be stationary or follow predefined movements, while the particle motion is calculated based on contact laws and material properties. The global particle model of DEM can predict contact stresses on a particle level, but is unable to describe local damages such as blackspot. This paper introduces a test rig for investigating mechanically induced discoloration of potato tissue and describes a model for representing local blackspot damage in DEM. Due to the inhomogeneous composition of the potato tuber with multiple tissue types, the three primary tissue types: cortex, perimedullary parenchyma and pith tissue are examined separately on the developed test rig. The mechanical stress on the tissue samples is applied up to a maximum compression strain of 20, 40, and 50%, with a defined strain rate ranging from 0.1 to 10000% per second, relative to the sample height. The colour change of the samples is examined affer approximately 48 hours against unloaded reference tissue. The tests were conducted at a tuber and ambient temperature of 14--20°C. The correlation between the colour change and the load parameters, compression strain and strain rate, can be described by an empirical equation. By implementing this equation as a damage model in the DEM contact model, the origination of blackspot in real processing stages can be predicted and investigated in simulations. The damage value of individual particles can be compared with the damage observed in real potatoes, allowing for the validation of the damage model. [ABSTRACT FROM AUTHOR]

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The application of solar dryer through greenhouse (GH) model as drying method for crops-based product is extremely important in industrial scale agriculture, especially in developed country. The drying model is considered environmentally friendly since it utilizes solar power as the main drying energy. However, the fundamental operational aspect of the basic GH is less discussed according to the drying mechanism of the dried product. In this work, three small-scale drying model are evaluated: open drying (OD), natural convection GH (NCGH), and forced convection GH (FCGH). The drying product is potato, which can be taken as an essential agricultural product in modern world. The OD model has the lowest mass loss rate which less than 50 % of the water from product can be evaporated. The operation of both GH is satisfactory, resulting more than 60 % moisture evaporation. The drying characteristic indicates the two-step failing rate which makes the mass loss fluctuation from the process. The highest mass loss is observed during the constant rate period around 21 % for FCGH and 18 % for NCGH. In addition, the detailed analysis on the effect of each process is discussed in this work. For example, the presence of hair-like structure and the movement of the pith of dried potato during the process. Also, a higher drying rate from NCGH and FCGH initiate the gelatinization and compartmentalization, resulting a substantial water evaporation of the product. It confirms the important correlation of the drying process and water diffusion mechanism of the dried product. The finding from this study can be taken as a vital reference for improving the operation of GH solar dryer. [ABSTRACT FROM AUTHOR]

A simple, effective and economically cheaper method for mass rearing of the brinjal shoot and fruit borer, Leucinodes orbonalis Guenee was developed using both modified artificial diet fortified with brinjal powder and natural diet - potato. A comparison of the various biological parameters such as egg incubation period, larval period, larval weight (12-day old), pre-pupal period, pupal period, pupal weight (1-day old), adult longevity, fecundity, oviposition period and sex ratio of different life stages of the test-insect were studied for both the food sources in this investigation. The larval and pupal periods on natural (potato) diet were 14.58± 1.51 and 6.7± 1.22 days respectively, with a mean fecundity of 165.55± 36.26 per female and a mean life cycle of 26.91days. The larval and pupal period of shoot and fruit borer reared on modified diet were 15.97± 1.24 and 6.25± 1.23 days respectively with a mean fecundity of 149.45± 25.83 per female and a mean life cycle of 25.26 days. Provision of a suitable site for adult mating and oviposition was attained by designing a separate mating chamber along with a suitable egg laying substratum. Thus, an easy and economical rearing technique could successfully support the rearing to six generations of target-insect in laboratory. [ABSTRACT FROM AUTHOR]

Ciliates are an important component of the rhizosphere microorganism community, but their nutritional contribution to plants has not been fully revealed. In this paper, we investigated the rhizosphere ciliate community of potatoes during six growth stages, illustrated the spatial–temporal dynamics of composition and diversity, and analyzed the correlation between soil physicochemical properties. The contributions of ciliates to the carbon- and nitrogen-derived nutrition of potatoes were calculated. Fifteen species of ciliates were identified, with higher diversity in the top soil, which increased as the potatoes grew, while they were more abundant in the deep soil, and the number decreased as the potatoes grew. The highest number of species of ciliates appeared in July (seedling stage). Among the five core species of ciliates, Colpoda sp. was the dominant species in all six growth stages. Multiple physicochemical properties affected the rhizosphere ciliate community, with ammonium nitrogen (NH4+-N) and the soil water content (SWC) greatly influencing ciliate abundance. The key correlation factors of ciliates diversity were NH4+-N, available phosphorus (AP), and soil organic matter (SOM). The annual average contribution rates of carbon and nitrogen by rhizosphere ciliates to potatoes were 30.57% and 23.31%, respectively, with the highest C/N contribution rates reaching 94.36% and 72.29% in the seedling stage. This study established a method for estimating the contributions of carbon and nitrogen by ciliates to crops and found that ciliates could be potential organic fertilizer organisms. These results might be used to improve water and nitrogen management in potato cultivation and promote ecological agriculture. [ABSTRACT FROM AUTHOR]

Potatoes play an important role in ensuring food security. During the COVID-19 epidemic, consumption of processed potato products decreased, and consumption of fresh potatoes increased. China is the world's largest potato producer with more than 4.81 million hectares of area under potato production and 90.32 million metric tonnes of potatoes produced in 2018. This accounts for 27.36% of the world's planting area and 24.53% of the world's potato production. The proportion of potatoes processed in China was about 12% in 2017, mostly dominated by starch production. However, the recent policy of the Chinese government to popularise potato as a staple food has created new markets for processed potato products other than starch. A very few reports have analysed these future trends of the rapidly growing Chinese potato processing industry and its impact within and outside China. This paper provides an overview of the latest developments with a focus on processed potato products such as potato chips, French fries and dehydrated potatoes, and also, due to the unique Chinese diet culture, it highlights the need for more scientific research dedicated towards the development of novel potato-based healthy foods. [ABSTRACT FROM AUTHOR]

Agricultural production is the main area of human activity that affects both food security and well-being, as well as the environment, in which people live. The modern economy tries to combine economic and environmental goals, because uncontrolled intensive production growth can lead to irreversible changes in the environment. This paper addresses the issue of evaluating one of the methods in search of the golden mean of sustainable agricultural production, on the example of the potato-microbiome interaction leading to the development of an innovative strategy of potato breeding and production. The aim was to apprise the economic and environmental effects of innovative potato cultivation with the use of beneficial microorganisms in Poland based on the field data. The data for the analyses were obtained from experimental field work carried out in 2021–2022 under the PotatoMetaBiome project. The analysis of the collected data allowed us to conclude that from the economic point of view, the most profitable was the strategy that included the use of practices based on synthetic means of production (with mineral fertilizers and chemical protection). On the other hand, the use of innovative preparations with beneficial microorganisms slightly increased the profitability in relation to the strategy without means of production and with the use of synthetic means of production. At the same time, it had the least negative impact on the environment than other agricultural practices. The obtained results indicate that the use of beneficial microorganisms may be a viable alternative agricultural strategy in potato production. It allows farmers to obtain satisfactory economic results while maintaining the environmental regime. Their use, however, requires further research in terms of the impact on the economics and organisation of agricultural production. [ABSTRACT FROM AUTHOR]

Seed systems for vegetatively propagated crops (VPCs) are frequently governed by regulatory blueprints designed for major cereal crops. This approach tends to disregard the distinct biological characteristics of VPCs, thus limiting farmers' access to high-quality planting material and increasing the risk of pest and disease transmission. In this paper, we ask what type of regulatory framework is appropriate for improving farmers' access to quality VPC planting material and what the costs, benefits, risks, and unintended consequences are of alternative regulations. We explore this in the context of cassava (Manihot esculenta) and potato (Solanum tuberosum) in Vietnam through secondary data, key informant interviews, and focus-group discussions. Findings indicate that despite a regulatory regime that imposes strict rules on the production and trade of planting material for VPCs, the market is largely unregulated because of weak enforcement capacity. Instead, producers and traders of VPC planting material signal quality to farmers through trust, reputation, and long-term relationships. Though effective at a localized scale, these informal systems are unlikely to accommodate expansion of the cassava and potato sectors and unlikely to prove effective in managing increases in pest and disease pressures that result from cross-border trade or climate change. We discuss alternative policy approaches and argue that the most appropriate policy regime requires a careful balance between a permissive regime at the local level and strict regulatory surveillance and enforcement at the national and regional levels. These approaches provide lessons for other developing countries where VPCs are important for economic growth and agricultural development. [ABSTRACT FROM AUTHOR]

The aim of this paper was to provide a more scientific and effective analysis of the fluctuation pattern of the Chinese potato market by extracting the characteristics of the price fluctuation cycle to effectively grasp the characteristics of price changes in the potato market, thus promoting the stable and healthy development of the Chinese potato industry, and to expand the application scenarios of the EEMD model to provide a reference for the study of price fluctuation patterns in other agricultural markets. This study used an ensemble empirical modal decomposition (EEMD) model to examine time-series data on Chinese wholesale potato market prices from January 2005 to December 2021. The results showed that (1) Chinese wholesale potato market prices are characterized by some rigidity, with sharp changes in growth rates; (2) Chinese wholesale potato market prices are dominated by short- and medium-term fluctuations, and the decomposed components can better reflect the characteristics of the original series fluctuations; (3) Chinese wholesale potato market monthly prices have long- and short-term fluctuations with a 6- and 19-month cycle, and are dominated by short-term high-frequency fluctuations; (4) monthly price fluctuations in the Chinese wholesale potato market are more intense in high-frequency than low-frequency fluctuations, and there is a strong correlation between high- and low-frequency fluctuations in precipitation, temperature and potato prices. Finally, suggestions were made for creating and improving a national potato price information platform and strengthening the information early warning mechanism; improving the potato production interest linkage mechanism and enhancing potato farmers' ability to cope with market and natural risks; and improving the potato reserve system and potato storage facilities. [ABSTRACT FROM AUTHOR]

This paper presents the results of the authors' own research and literature research on the impact of selected environmental and agronomical factors on the yield of potato grown under the organic system and the possibility of increasing the yield. The results are based on research conducted for several years at the Institute of Plant Breeding and Acclimatization in Jadwisin, Poland. The influence of factors such as soil quality and climatic conditions, selection of varieties, seed potato preparation, irrigation of plantations, complementary fertilization, and protection against the late blight was described. The aim of this work was to indicate which of these factors affect the yield increase and to what extent. It was stated that it is possible to increase the yield of potato tubers grown under the organic system through all of the proposed treatments. In our studies, using drip irrigation and complementary fertilization had the greatest effect (25.5% and 19%, respectively). Seed potato presprouting had a smaller influence (4.3%) on the final tuber yield. In the years with high pressure of the pathogen Phytophthora infestans, the selection of cultivars with high resistance was very important. Most of the agronomical treatments not only improved the total yield of tubers, but also increased the share of tubers with a larger diameter. A very high variability of potato yielding depending on weather conditions and a selection of cultivars was emphasized. We can say that a proper agronomical practice carried out on an organic potato plantation can largely eliminate the yielding gap between a conventional and an organic system. [ABSTRACT FROM AUTHOR]

In view of the problem that the research of potato friction damage is not sufficiently systematic and the characteristics of potato friction damage and energy loss are not clear, this paper investigates the initial height, potato mass, potato varieties, friction materials and temperature as experimental factors and the epidermal damage proportion as the evaluation index, filtering for significant factors by a factorial test. On this basis, the proportion of epidermal damage and the ratio of energy consumption loss were used as evaluation indicators to conduct a single factor test for significant factors. Thereby, the influence of these factors on friction damage and energy loss characteristics of potato were further investigated. The results show that the initial height, potato mass and potato varieties were the significant factors affecting the proportion of epidermal damage of potatoes. With the increase in initial height, the proportion of epidermal damage and ratio of energy consumption loss gradually increased. With the increment in potato mass, the proportion of epidermal damage gradually increased, and the energy consumption loss ratio gradually decreased. The epidermal damage proportion and energy consumption loss ratio of potato varieties were ranked as Xisen 1 > Jizhang 12 > Xisen 6 > Xuechuanhong > Netherlands 15, and Netherlands 15 > Xisen 6 > Xisen 1 > Xuechuanhong > Jizhang 12, respectively. The energy loss ratio and epidermal damage proportion were highly correlated at initial height and potato mass. A mathematical model for predicting the proportion of epidermal damage using energy consumption loss ratio is proposed: η1 = 0.8861ζ − 0.2062 (R2 = 0.8626), η2 = −0.5813ζ + 0.2394 (R2 = 0.8537). [ABSTRACT FROM AUTHOR]

The current discrete-element simulation models for potatoes are multisphere polymer models derived from the Hertz–Mindlin (no slip) contact model in the discrete-element simulation software (EDEM). These models oversimplify by considering potato peel and flesh as sharing identical mechanical properties within the structure. This oversimplification impedes a thorough investigation of the characteristics and mechanisms underlying potato peel-breaking damage during mechanized harvesting, making in-depth exploration challenging through simulation experiments. Consequently, this study conducted laboratory tests to determine the water content of potato peel and flesh, as well as the friction coefficients and collision recovery coefficients for various material pairs: flesh–steel, peel–steel, peel–peel, peel–flesh, and flesh–flesh. Subsequently, based on these findings, a double-layer flexible bonding model for potato samples and whole stems under specific water content conditions was developed using EDEM software. The bonding parameters of the double-layer flexible model for potato samples were refined through virtual shear calibration tests, leading to the identification of the optimal parameter combination: Flesh particle–flesh particle normal stiffness(tangential stiffness) per unit area X1 = 4.39 × 108 N/m³, peel particle–flesh particle normal stiffness(shear stiffness) per unit area X3 = 1.81 × 109 N/m³, peel particle–peel particle shear stiffness per unit area X6 = 1.99 × 109 N/m³, peel particle–peel particle critical normal stress X7 = 2.06 × 109 Pa. To validate the accuracy of the bonding parameters, shear and compression validation tests were conducted on entire potato stems. Comparison of the validation results from laboratory tests and simulation tests revealed an average relative error of e = 3.25%, signifying the feasibility of the constructed double-layer flexible bond model for potatoes. This model meets the requirements for studying the characteristics and mechanisms of peel-breaking damage in potatoes. Practical Applications The paper introduces a novel double-layer flexible bonding model for potatoes using the discrete-element method (DEM), which accurately simulates the mechanical properties and damage characteristics of potato peels and flesh. This research has significant practical applications in agricultural machinery design, improving the efficiency and reducing the damage during mechanical harvesting. By providing a more realistic simulation of potato behavior under mechanical stress, it can guide the development of gentler handling equipment, reduce waste, and enhance the quality of harvested potatoes. This contributes to optimizing the post-harvest process, ensuring better storage, and extending the marketable life of potatoes. [ABSTRACT FROM AUTHOR]

Potato (Solanum tuberosum L.) is a key crop for global food security. Therefore, under actual climatic changes, it is important to search for genotypes with steady characteristics in contrasting weather conditions. The aim of the present study was to establish the relationship between the development of the biomass and the number, respectively, the weight of the tubers in order to introduce into the breeding program new genotypes, future varieties, with increased adaptability to environmental factors. The paper presents the results of a field study conducted to NIRDPSB Braşov, Romania, between 2021-2022, to evaluate some agronomic traits in potato genotpyes. A total of 15 potato genotypes (1901/6, 1930/3, 1901/12, 1927/1, 1897/2, 1979/5, 1891/1, 1927/3, 1901/11, 1941/8, 1895/4, 19-1876/7, 1939/2, 21-1895/1, 21-1901/7) along with one commercial cultivar (Braşovia) were evaluated. The experiment was laid out in a randomized complete block design with three replications. Data was recorded on plant height, main stem number per plant, tuber number and weight per plant and total tuber yield. Significantly positive phenotypic correlations for the height and mass of the plants were observed to the both determinations in the both years (r=0.90175, r=0.889, r=0.54505, r=0.562). The number and the weight of tubers were in an evolutionary process during the two experimental years. Genotypes 21-1901/7 (45.55 t/ha in 2021 and 34.17 t/ha in 2022) and 1939/2 (47.93 t/ha in 2021, respectively, 30.70 t/ha in 2022) recorded significantly high productions and even in the extreme conditions of 2022 maintained their high production capacity. The present findings show the existence of proper genetic variability and divergence among traits, and the identified traits can be used in a potato improvement program. [ABSTRACT FROM AUTHOR]

The availability of water for agricultural production is under threat from climate change and rising demands from various sectors. In this paper, a simulation-optimization model for optimizing the irrigation schedule in the Bilate watershed was developed, to save irrigation water and maximize the yield of deficit irrigation. The model integrated the Soil and Water Assessment Tool (SWAT) and an irrigation-scheduling optimization model. The SWAT model was used to simulate crop yield and evapotranspiration. The Jensen crop-water-production function was applied to solve potato and wheat irrigation-scheduling-optimization problems. Results showed that the model can be applied to manage the complicated simulation-optimization irrigation-scheduling problems for potato and wheat. The optimization result indicated that optimizing irrigation-scheduling based on moisture-stress-sensitivity levels can save up to 25.6% of irrigation water in the study area, with insignificant yield-reduction. Furthermore, optimizing deficit-irrigation-scheduling based on moisture-stress-sensitivity levels can maximize the yield of potato and wheat by up to 25% and 34%, respectively. The model developed in this study can provide technical support for effective irrigation-scheduling to save irrigation water and maximize yield production. [ABSTRACT FROM AUTHOR]

Afforestation of agriculturally used land has many benefits which are described in different publications. As stated in these publications, afforestation of agricultural land can influence soil water content because of rainfall interception and concentration, transpiration, and properties of forest floor layer and soil; also, hydraulic lift may occur. In this study, we attempted to find changes in volumetric soil water content values (at depths of 20 cm, 40 cm, and 60 cm) on agriculturally used land afforested with a mixture of forest tree species (Quercus robur L., Quercus rubra L., and Acer platanoides L.) or Pinus sylvestris L. in the year 2011 (and on agriculturally used land = control). This study was performed in the period from the end of March 2021 to the beginning of April 2022. In this study, we proved our hypothesis on the reduction of volumetric soil water content after afforestation; it is probably because of higher rainfall interception and evapotranspiration as described in different studies. Concerning the afforestation, the average volumetric water content was higher on the plot afforested with broadleaves compared with Scots pine. It was especially in the period after defoliation when the proportion of throughfall (and stemflow) increased on the plot with broadleaves. Our results indicate a higher water-storage capacity of forests compared with agriculturally used land. During the leafless period, this capacity was found to be higher after afforestation with Scots pine. [ABSTRACT FROM AUTHOR]

The present paper presents a method for analyzing the impact between potatoes transported by belt conveyors at specific velocity 30, 50, 70 m/min and two materials from the potato harvesting chain using a digital potato . The results obtained with this device are important in the harvest and post-harvest potato management for obtaining quality potato for people consumption. [ABSTRACT FROM AUTHOR]

There is an urgent need to explore climate-resilient alternative agriculture production systems that focus on resilience, resource efficiency, and disease management. Hydroponics, a soilless cultivation system, gaining interest as it reduces the dependency on agricultural land, and pesticides, and can be implemented in areas with poor soil quality, thus mitigating the negative effects of extreme weather events. Potato is an essential dietary staple crop grown throughout the world and is a major source of food security in underdeveloped countries. However, due to the climatic changes, it is predicted that a significant loss in the suitability of land for potato production would occur, thus leading to potato yield loss. Recently, many case studies have emerged to highlight the advancement of agricultural hydroponic systems that provide a promising solution to the massive production of potato mini tuber at high efficiency. This review paper evaluates popular hydroponic methods and demonstrates how hydroponic has emerged as the go-to, long-term, sustainable answer to the perennial problem of insufficient access to high-quality potato seed stock. The paper discusses the research and innovation possibilities (such as artificial intelligence, nanoparticles, and plant growth-promoting rhizobacteria) that potentially increase tuber production per plant under optimal hydroponic growth circumstances. These approaches are examined considering new scientific discoveries and practical applications. Furthermore, it emphasizes that by enduring significant reforms in soilless food production systems (particularly for potatoes), the food supply of a rapidly growing population can be addressed. Since hydroponics systems are productive and easily automated without soil and optimal environmental conditions, future hydroponics farming is promising. In conclusion, the hydroponics system provides better yield and crop productivity by saving water, energy, and space. Henceforth, it can be the alternate choice for modern sustainable agriculture.

The paper presents the research results of the response of "Ramos" potatoes under impact loading conditions. The parameters characterizing the impact such as: maximum stress, maximum force, impact time, maximum deformation, permanent deformation and restitution coefficient were determined. The extent of the damage was also assessed on the basis of the parameters describing the particular bruise such as: bruise depth and width. The impact parameters were related to the bruise size in order to determine the damage threshold for the potatoes under impact loading conditions and to show which parameters describe the bruise beginning to manifest itself. For the tested potato cultivar with a weight of 160-190 g the initiation of the bruise was found to occur at an impact velocity of 1 m s-1. This corresponded to a bruise threshold (drop height) of 50 mm. The restitution coefficient changed to an insignificant extent which amounted to 0.44-0.49 in the tested range of the impact velocity which proves that the energy losses during the potato impact are constant and independent of the impact velocity. The maximum stress increased with increasing impact velocity, reaching a constant value of 0.9 MPa for the highest impact velocities. The stabilization of the maximum stress indicates that the damage to the potato tissue was determined by exceeding the specified stress value. [ABSTRACT FROM AUTHOR]

Plastid DNA holds a substantial amount of plant genetic information, including maternal ancestry information. It helps to uncover interrelations between a wide variety of tuberous species of the genus Solanum to search for promising sources of high-yielding potato varieties resistant to bio- and abiotic stressors. This paper demonstrated the opportunities of de novo assembly of potato plastid DNA and its phylogenetic and genome type identification based only on Oxford Nanopore Technologies (ONT) long reads. According to our results, of 28 potato varieties developed at the Ural Research Institute of Agriculture, 16 varieties had one of the most primitive W-type plastomes. Ten varieties' plastomes belonged to the T-type of cultivated Solanum tuberosum subsp. tuberosum. The varieties Legenda and 15-27-1 were the closest to the wild species Solanum chacoense plastome. Using long-sequencing reads, we confirmed the presence of two isoforms of the plastid genome differing in the orientation of SSC region. We should note that irrespective of sequencing depth and improvements in software for working with ONT reads, a correct de novo plastome assembly and its annotation using only long-reads is impossible. The most problematic regions are homopolymers longer than 5 bp—they account for all detected indels, leading to a change in the reading frame or the deletion of entire genes. [ABSTRACT FROM AUTHOR]

The potato is a key crop in addressing global hunger, and deep learning is at the core of smart agriculture. Applying deep learning (e.g., YOLO series, ResNet, CNN, LSTM, etc.) in potato production can enhance both yield and economic efficiency. Therefore, researching efficient deep learning models for potato production is of great importance. Common application areas for deep learning in the potato production chain, aimed at improving yield, include pest and disease detection and diagnosis, plant health status monitoring, yield prediction and product quality detection, irrigation strategies, fertilization management, and price forecasting. The main objective of this review is to compile the research progress of deep learning in various processes of potato production and to provide direction for future research. Specifically, this paper categorizes the applications of deep learning in potato production into four types, thereby discussing and introducing the advantages and disadvantages of deep learning in the aforementioned fields, and it discusses future research directions. This paper provides an overview of deep learning and describes its current applications in various stages of the potato production chain.