Search Results (20)

The accurate classification of plant diseases is vital for global food security, as diseases can cause major yield losses and threaten sustainable and precision agriculture. The classification of plant diseases in low-light noisy environments is crucial because crops can be continuously monitored even at night. Important visual cues of disease symptoms can be lost due to the degraded quality of images captured under low-illumination, resulting in poor performance of conventional plant disease classifiers. However, researchers have proposed various techniques for classifying plant diseases in daylight, and no studies have been conducted for low-light noisy environments. Therefore, we propose a novel model for classifying plant diseases from low-light noisy images called dilated pixel attention network (DPA-Net). DPA-Net uses a pixel attention mechanism and multi-layer dilated convolution with a high receptive field, which obtains essential features while highlighting the most relevant information under this challenging condition, allowing more accurate classification results. Additionally, we performed fractal dimension estimation on diseased and healthy leaves to analyze the structural irregularities and complexities. For the performance evaluation, experiments were conducted on two public datasets: the PlantVillage and Potato Leaf Disease datasets. In both datasets, the image resolution is 256 × 256 pixels in joint photographic experts group (JPG) format. For the first dataset, DPA-Net achieved an average accuracy of 92.11% and harmonic mean of precision and recall (F1-score) of 89.11%. For the second dataset, it achieved an average accuracy of 88.92% and an F1-score of 88.60%. These results revealed that the proposed method outperforms state-of-the-art methods. On the first dataset, our method achieved an improvement of 2.27% in average accuracy and 2.86% in F1-score compared to the baseline. Similarly, on the second dataset, it attained an improvement of 6.32% in average accuracy and 6.37% in F1-score over the baseline. In addition, we confirm that our method is effective with the real low-illumination dataset self-constructed by capturing images at 0 lux using a smartphone at night. This approach provides farmers with an affordable practical tool for early disease detection, which can support crop protection worldwide. Full article

Accurate classification of plant disease by farming robot cameras can increase crop yield and reduce unnecessary agricultural chemicals, which is a fundamental task in the field of sustainable and precision agriculture. However, until now, disease classification has mostly been performed by manual methods, such as visual inspection, which are labor-intensive and often lead to misclassification of disease types. Therefore, previous studies have proposed disease classification methods based on machine learning or deep learning techniques; however, most did not consider real-world plant images with complex backgrounds and incurred high computational costs. To address these issues, this study proposes a computationally effective residual convolutional attention network (RCA-Net) for the disease classification of plants in field images with complex backgrounds. RCA-Net leverages attention mechanisms and multiscale feature extraction strategies to enhance salient features while reducing background noises. In addition, we introduce fractal dimension estimation to analyze the complexity and irregularity of class activation maps for both healthy plants and their diseases, confirming that our model can extract important features for the correct classification of plant disease. The experiments utilized two publicly available datasets: the sugarcane leaf disease and potato leaf disease datasets. Furthermore, to improve the capability of our proposed system, we performed fractal dimension estimation to evaluate the structural complexity of healthy and diseased leaf patterns. The experimental results show that RCA-Net outperforms state-of-the-art methods with an accuracy of 93.81% on the first dataset and 78.14% on the second dataset. Furthermore, we confirm that our method can be operated on an embedded system for farming robots or mobile devices at fast processing speed (78.7 frames per second). Full article

This study aims to explore the impacts of climate change on potato planting in Gansu Province so as to be able to adjust potato planting pattern scientifically and rationally. (1) Air precipitation and temperature time-series datasets were obtained from 87 meteorological stations in the study area over the past 50 years. The backpropagation neural network was employed to interpolate irregular and missing data in the time-series data. The altitude, the precipitation from June to July, the average temperature in July and the accumulated temperature above 10 °C were selected as the agricultural zoning indicators for the regionalization of potato planting. (2) The linear propensity rate method, cumulative anomaly method, ArcGIS technology and the Mann–Kendall mutation test were employed to examine the spatial–temporal variation in and mutation testing of the three zoning indicators. (3) The experimental results demonstrated that the amount of precipitation from June to July was registered at 139.94 mm, indicating a slight humidifying trend characterized by an annual increase rate of approximately 1.81 mm/10 a. Furthermore, a significant abrupt change was observed in 1998. The average temperature in July was registered at 20.53 °C, which showed an increasing trend at a rate of 0.55 °C/10 a, marked by a sudden shift in 1998. Lastly, the accumulated temperature above 10 °C was registered at 2917.05 °C, manifesting a significant warming trend at a rate of 161.96 °C/10 a, without any abrupt changes. For spatial distribution, the precipitation from June to July showed a decreasing spatial distribution pattern from south to north and from east to west, while its tendency rate showed a gradually decreasing trend from north to south and from east to west. The average temperature in July showed a decreasing spatial pattern from northeast to southwest, while its tendency rate showed a decreasing trend from west to east and from north to south. The accumulated temperature above 10 °C showed a spatial pattern of high accumulated temperatures in the northwestern and southeastern regions and low accumulated temperatures in the remaining regions, while its tendency rate showed a decreasing trend from west to east and from north to south. (4) The impacts of climate change on potato planting in Gansu Province were mainly manifested as a decrease of 0.30 × 10⁶ hm² in the cultivated land area in the most suitable region for potato planting post-1998, while the suitable area diminished by 0.96 × 10⁶ hm², the sub-suitable area expanded by 0.47 × 10⁶ hm², and the plantable area increased by 0.79 × 10⁶ hm². However, the unsuitable area experienced a reduction of 0.30 × 10⁴ hm². The findings of this study can provide a scientific foundation for optimizing and adjusting the potato planting structure, considering the backdrop of climate change. Moreover, they contribute to regional decision-making, thereby promoting sustainable agricultural development as well as enhancing both the yield and quality of potato in Gansu Province. Full article

Microbial agents such as the Bacillus species are recognized for their role as biocontrol agents against various phytopathogens through the production of diverse bioactive compounds. This study evaluates the effectiveness of Bacillus subtilis PE7 in inhibiting the growth of Didymella bryoniae, the pathogen responsible for gummy stem blight (GSB) in cucurbits. Dual culture assays demonstrate significant antifungal activity of strain PE7 against D. bryoniae. Volatile organic compounds (VOCs) produced by strain PE7 effectively impede mycelial formation in D. bryoniae, resulting in a high inhibition rate. Light microscopy revealed that D. bryoniae hyphae exposed to VOCs exhibited abnormal morphology, including swelling and excessive branching. Supplementing a potato dextrose agar (PDA) medium with a 30% B. subtilis PE7 culture filtrate significantly decreased mycelial growth. Moreover, combining a 30% culture filtrate with half the recommended concentration of a chemical fungicide yielded a more potent antifungal effect than using the full fungicide concentration alone, inducing dense mycelial formation and irregular hyphal morphology in D. bryoniae. Strain PE7 was highly resilient and was able to survive in fungicide solutions. Additionally, B. subtilis PE7 enhanced the nutrient content, growth, and development of melon plants while mitigating the severity of GSB compared to fungicide and fertilizer treatments. These findings highlight B. subtilis PE7 as a promising biocontrol candidate for integrated disease management in crop production. Full article

The anti-digestibility of resistant dextrin (RD) and resistant maltodextrin (RMD) is usually significantly affected by processing techniques, reaction conditions, and starch sources. The objective of this investigation is to elucidate the similarities and differences in the anti-digestive properties of RD and RMD prepared from three different tuber crop starches, namely, potato, cassava, and sweet potato, and to reveal the associated mechanisms. The results show that all RMDs have a microstructure characterized by irregular fragmentation and porous surfaces, no longer maintaining the original crystalline structure of starches. Conversely, RDs preserve the structural morphology of starches, featuring rough surfaces and similar crystalline structures. RDs exhibite hydrolysis rates of approximately 40%, whereas RMDs displaye rates lower than 8%. This disparity can be attributed to the reduction of α-1,4 and α-1,6 bonds and the development of a highly branched spatial structure in RMDs. The indigestible components of the three types of RDs range from 34% to 37%, whereas RMDs vary from 80% to 85%, with potato resistant maltodextrin displaying the highest content (84.96%, p < 0.05). In conclusion, there are significant differences in the processing performances between different tuber crop starches. For the preparation of RMDs, potato starch seems to be superior to sweet potato and cassava starches. These attributes lay the foundation for considering RDs and RMDs as suitable components for liquid beverages, solid dietary fiber supplements, and low glycemic index (low-GI) products. Full article

The objective of this study was to investigate the effect of temperature changes during heat–moisture treatment (HMT) on the appearance, structure and digestibility of sweet potato starch (SPS). The results showed that after HMT, there were depressions, cavities and fragments on the surface of SPS particles. The polarized crosses of SPS were irregular and partially blurred. The relative crystallinity and short-range order of SPS decreased, while rearrangement and reorientation of the starch molecules occurred and the thermal stability increased. The resistant starch content of SPS reached the highest (24.77%) after 4 h treatment at 110 °C and 25% moisture. The obtained results can provide a reference for the modification of SPS. Full article

Zinc oxide nanoparticles (ZnO-NPs) have gained significant attention in nanotechnology due to their unique properties and potential applications in various fields, including insecticidal and antibacterial activities. The ZnO-NPs were biosynthesized by Eriobotrya japonica leaf extract and characterized by various techniques such as UV–visible (UV–vis) spectrophotometer, X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), and zeta potential analysis. The results of SEM revealed that NPs were irregular and spherical-shaped, with a diameter between 5 and 27 nm. Meanwhile, DLS supported that the measured size distributions were 202.8 and 94.7 nm at 11.1° and 90.0°, respectively, which supported the polydisperse nature of NPs, and the corresponding zeta potential was −20.4 mV. The insecticidal activity of the produced ZnO-NPs was determined against the adult stage of coleopteran pests, Sitophilus oryzae (Linnaeus) (Curculionidae) and Tribolium castaneum (Herbst) (Tenebrionidae). The LC₅₀ values of ZnO-NPs against adults of S. oryzae and T. castaneum at 24 h of exposure were 7125.35 and 5642.65 μg/mL, respectively, whereas the LC₉₀ values were 121,824.56 and 66,825.76 μg/mL, respectively. Moreover, the biosynthesized nanoparticles exhibited antibacterial activity against three potato bacterial pathogens, and the size of the inhibition zone was concentration-dependent. The data showed that the inhibition zone size increased with an increase in the concentration of nanoparticles for all bacterial isolates tested. The highest inhibition zone was observed for Ralstonia solanacearum at a concentration of 5 µg/mL, followed by Pectobacterium atrosepticum and P. carotovorum. Eventually, ZnO-NPs could be successfully used as an influential agent in pest management programs against stored-product pests and potato bacterial diseases. Full article

The main reserve polysaccharide of plants—starch—is undoubtedly important for humans. One of the main sources of starch is the potato tuber, which is able to preserve starch for a long time during the so-called dormancy period. However, accumulated data show that this dormancy is only relative, which raises the question of the possibility of some kind of starch restructuring during dormancy periods. Here, the effect of long-term periods of tuber rest (at 2–4 °C) on main parameters of starches of potato tubers grown in vivo or in vitro were studied. Along with non-transgenic potatoes, Arabidopsis phytochrome B (AtPHYB) transformants were investigated. Distinct changes in starch micro and macro structures—an increase in proportion of amorphous lamellae and of large-sized and irregular-shaped granules, as well as shifts in thickness of the crystalline lamellae—were detected. The degree of such alterations, more pronounced in AtPHYB-transgenic tubers, increased with the longevity of tuber dormancy. By contrast, the polymorphic crystalline structure (B-type) of starch remained unchanged regardless of dormancy duration. Collectively, our data support the hypothesis that potato starch remains metabolically and structurally labile during the entire tuber life including the dormancy period. The revealed starch remodeling may be considered a process of tuber preadaptation to the upcoming sprouting stage. Full article

The effects of pullulanase debranching combined with autoclaving (PDA) at various debranching times (0 h, 5 h, 10 h, 15 h, 20 h, and 25 h) and 121 °C/20 min of autoclave treatment on the structural and physicochemical characteristics of purple sweet potato (Jinshu No.17) starch were investigated. The results indicated that the native starch (NS) was polygonal, round, and bell-shaped with smooth surfaces. After debranching treatment, the surface of the starch samples became rough and irregular. The molecular weight became smaller after treatments. X-ray diffraction C-type pattern was transformed into a B-type structure in treated samples with increased relative crystallinity. ¹³C NMR indicated an increased propensity for double helix formation and new shift at C1, 3, 5 region compared to NS. The apparent amylose content was 21.53% in the NS. As the swelling power decreased, the percentage of soluble solids increased and different thermal properties were observed. A higher yield of the resistant starch (RS) was observed in all treated starch except PDA 25 h. The findings of our study reveal that a combination of pullulanase debranching time (15 h) and autoclaving (121 °C for 20 min) is a great technique that can be used to produce a higher amount of resistant starch in the Jinshu No.17 starch. Full article

Further processing and the added value of potatoes are limited by irregular potatoes. An ellipse-fitting-based Hausdorff distance and intersection over union (IoU) method for identifying irregular potatoes is proposed to solve the problem. First, the acquired potato image is resized, translated, segmented, and filtered to obtain the potato contour information. Secondly, a least-squares fitting method fits the extracted contour to an ellipse. Then, the similarity between the irregular potato contour and the fitted ellipse is characterized using the perimeter ratio, area ratio, Hausdorff distance, and IoU. Next, the characterization ability of the four features is analyzed, and an identification standard of irregular potatoes is established. Finally, we discuss the algorithm’s shortcomings in this paper and draw the advantages of the algorithm by comparison. The experimental results showed that the characterization ability of perimeter ratio and area ratio was inferior to that of Hausdorff distance and IoU, and using Hausdorff distance and IoU as feature parameters can effectively identify irregular potatoes. Using Hausdorff distance separately as a feature parameter, the algorithm achieved excellent performance, with precision, recall, and F1 scores reaching 0.9423, 0.98, and 0.9608, respectively. Using IoU separately as a feature parameter, the algorithm achieved a higher overall recognition rate, with precision, recall, and F1 scores of 1, 0.96, and 0.9796, respectively. Compared with existing studies, the proposed algorithm identifies irregular potatoes using only one feature, avoiding the complexity of high-dimensional features and significantly reducing the computing effort. Moreover, simple threshold segmentation does not require data training and saves algorithm execution time. Full article

Tuber shape is one of the most important quality traits in potato appearance. Since poor or irregular shape results in higher costs for processing and influences the consumers’ willingness to purchase, breeding for shape uniformity and shallow eye depth is highly important. Previous studies showed that the major round tuber shape controlling locus, the Ro locus, is located on chromosome 10. However, fine mapping and cloning of tuber shape genes have not been reported. In this study, the analyses of tissue sectioning and transcriptome sequencing showed that the developmental differences between round and elongated tuber shapes begin as early as the hook stage of the stolon. To fine map tuber shape genes, a high-density genetic linkage map of the Ro region on chromosome 10 based on a diploid segregating population was constructed. The total length of the genetic linkage map was 25.8 cM and the average marker interval was 1.98 cM. Combined with phenotypic data collected from 2014 to 2017, one major quantitative trait locus (QTL) for tuber shape was identified, which explained 61.7–72.9% of the tuber shape variation. Through the results of genotyping and phenotypic investigation of recombinant individuals, Ro was fine mapped in a 193.43 kb interval, which contained 18 genes. Five candidate genes were preliminarily predicted based on tissue sections and transcriptome sequencing. This study provides an important basis for cloning Ro gene(s). Full article

Food defect detection is crucial for the automation of food production and processing. Potato surface defect detection remains challenging due to the irregular shape of potato individuals and various types of defects. This paper employs deep convolutional neural network (DCNN) models for potato surface defect detection. In particular, we applied transfer learning by fine-tuning a base model through three DCNN models—SSD Inception V2, RFCN ResNet101, and Faster RCNN ResNet101—on a self-developed dataset, and achieved an accuracy of 92.5%, 95.6%, and 98.7%, respectively. RFCN ResNet101 presented the best overall performance in detection speed and accuracy. It was selected as the final model for out-of-sample testing, further demonstrating the model’s ability to generalize. Full article

One of the most important problems of the modern world is food wastage. The issue occurs at every stage of the food chain, requiring new sustainable production and processing technologies. The processing of production waste and making it a wholesome ingredient may be a good opportunity to promote more sustainable development. This study analyzes the process of enrichment of model by-product (irregular potatoes cubes) with a functional compound (ascorbic acid) through vacuum impregnation, with two experiments on variants of the process, standard (VI) and ultrasonic-assisted (UVI). The research covers complete processing, including the stage of preserving impregnated products by convective drying. The analysis includes the impregnation efficiency, drying kinetics, and energy consumption, and selected quality parameters of the material, namely color and water activity. Based on the results, ultrasound increased the impregnation efficiency, but the quantitative effect depends on the application period. Ultrasound had a positive effect on the kinetics and energy consumption of convective drying. Ultrasound did not reduce quality. The proposed technology may be useful during the processing of by-products. Full article

Plants produce a huge array of secondary metabolites that play a key role in defense mechanisms against detrimental microorganisms and herbivores, and represent a suitable alternative to synthetic fungicides in sustainable agriculture. In this work, twelve crude hydroethanolic extracts derived from leaves of different potato cultivars were chemically characterized by LC/MS and their antioxidant properties were investigated in vitro. Furthermore, the biological activity against the fungal pathogen Rhizoctonia solani was evaluated both in vitro and in vivo. Extracts showed the ability to inhibit R. solani growth in vitro and significantly reduced damping-off incidence in in vivo experiments. Furthermore, R. solani mycelia exposed to the extracts showed an altered morphology (low translucency, irregular silhouette, and cytoplasmatic content coagulation) compared to the untreated control in light microscopy examination. Principal component analysis conducted on identified chemical compounds highlighted significant metabolic variations across the different extracts. In particular, those that inhibited most of the growth of the pathogen were found to be enriched in α-chaconine or α-solanine content, indicating that their biological activity is affected by the abundance of these metabolites. These results clearly indicated that plant-derived compounds represent a suitable alternative to chemicals and could lead to the development of new formulates for sustainable control of plant diseases. Full article

Potato plants are liable to PVY infection without efficient control. Therefore, they were cultivated under greenhouse and open field conditions, artificially infected with PVY and then treated after 15 days of infection with native lactoferrin (LF) and native β-lactoglobulin (BL) and their esterified forms, MLF (methylated lactoferrin) and BLM (methylated β-lactoglobulin) to test the efficiency of this approach. Viral replication was inhibited by the applied substances, particularly the methylated forms, in a concentration-dependent manner, where the concentration of 500 μg·mL⁻¹ was sufficient for plant protection against the PVY infection. An open field experiment showed that one single application of the antiviral substance was enough for maximum inhibitory action against PVY. The modified milk proteins induced higher inhibitory action on PVY virus replication in the plants, compared to their native forms, which was reflected by potato growth and yield. Using the dot blot hybridization and RT-PCR techniques to detect PVY in the experimental plants showed the supremacy of native and esterified LF in inhibiting the targeted virus. The generally observed scanning electronic microscopy (SEM) structural deformations and irregular appearance in PVY particles when treated with MLF and BLM revealed their direct action. BLM, MLF and LF are efficient antiviral agents against PVY. They can not only abolish the observed PVY-induced reduction in potato growth and tuber yield, but also further increase them to higher levels than negative control. Full article