WEI ZHOU, MENGMENG ZHANG, KEZHANG TAO, XIANCAN ZHU^*

BIOCELL, Vol.46, No.12, pp. 2575-2582, 2022, DOI:10.32604/biocell.2022.021910

Abstract Land salinization is a major form of land degradation, which is not conducive to the growth and quality of fruits and vegetables. Plant salt tolerance can be enhanced by arbuscular mycorrhizal fungi (AMF) or plant growth-promoting rhizobacteria (PGPR). This study examined the effects of inoculation with PGPR singly or in combination with AMF, on the growth and quality of tomato fruits under low saline conditions. Tomatoes were cultivated in a greenhouse with sterilized soil, inoculated with PGPR, AMF, or co-inoculated with PGPR and AMF, and NaCl solution (1%) was added to the soil. The results indicated that AMF + PGPR… More >

Xun Li¹, Wenzhe Ma^1,*, Zhengfan Zhao², Muhammad Bashir¹, Wenjie Wang¹, Xiaohua Wang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 67-92, 2022, DOI:10.32604/cmes.2022.020019

Abstract In a multi-lane area, the increasing randomness of lane changes contributes to traffic insecurity and local traffic flow instability. A study on safe lane shifting activity that focuses on threat assessment under real-time knowledge is necessary to enhance smooth vehicle flow. This paper proposed a more comprehensive lane changing guidance rule to investigate the status of surrounding vehicles to accommodate future vehicle-on-road collaborative environments based on these parameters 1) lane change demand and 2) treat assessment function. The collaborative relationships between vehicles are analyzed using a cellular automata model based on their location, velocity, and acceleration. We analyze and examine… More >

Yanjiao Zheng¹, Zaiqiang Yang^1,2,*, Tingting Wei¹, Heli Zhao¹

Phyton-International Journal of Experimental Botany, Vol.91, No.9, pp. 2033-2054, 2022, DOI:10.32604/phyton.2022.019468

Abstract The combined stress of high temperature and high relative air humidity is one of the most serious agrometeorological disasters that restricts the production capacity of protected agriculture. However, there is little information about the precise interaction between them on tomato fruit quality. The objectives of this study were to explore the effects of the combined stress of high temperature and relative humidity on the sugar and acid metabolism and fruit quality of tomato fruits, and to determine the best relative air humidity for fruit quality under high temperature environments. Four temperature treatments (32°C, 35°C, 38°C, 41°C), three relative air humidity… More >

Wan Hyun Cho¹, Sang Kyoon Kim², Myung Hwan Na¹, In Seop Na^3,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4003-4024, 2021, DOI:10.32604/cmc.2021.018758

Abstract Fruit processing devices, that automatically detect the freshness and ripening stages of fruits are very important in precision agriculture. Recently, based on deep learning, many attempts have been made in computer image processing, to monitor the ripening stage of fruits. However, it is time-consuming to acquire images of the various ripening stages to be used for training, and it is difficult to measure the ripening stages of fruits accurately with a small number of images. In this paper, we propose a prediction system that can automatically determine the ripening stage of fruit by a combination of deep neural networks (DNNs)… More >

Shafiul Islam, Lutful Hassan, Mohammad Anwar Hossain

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 97-114, 2022, DOI:10.32604/phyton.2022.017251

Abstract Tomato (Solanum lycopersicum L.) is called ‘the poor man’s orange’ due to its low price and improved nutritional values. An experiment was conducted to study the breeding potential of some exotic tomato lines by assessing various qualitative and quantitative traits conferring yield and quality attributes. Among the qualitative traits, greater variability was observed for growth type, stem hairiness, and fruit shape and size. A determinate growth habit was observed in the genotype AVTO9802 while the genotype AVTO0102 produced yellow color fruits. A significant (p ≤ 0.01) variation was also observed for the studied quantitative traits. Based on yield and traits… More >

Ali Abdelmoteleb¹, Daniel Gonzalez-Mendoza^2,*, Ahmed Mohamed Elbaalawy³

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 21-32, 2022, DOI:10.32604/phyton.2022.016227

Abstract The salinity stress is one of the most relevant abiotic stresses that affects the agricultural production. The present study was performed to study the improvement of the salt tolerance of tomato plants which is known for their susceptibility to salt stress. The present study aimed to assess to what extent strain Azospirillum brasilense (N040) and Saccharomyces cerevisiae improve the salt tolerance to tomato plants treated with different salt concentration. The inoculant strain A. brasilense (N040) was previously adapted to survive up to 7% NaCl in the basal media. A greenhouse experiment was conducted to evaluate the effect of this inoculation… More >

Xiaomei Zhang, Junliang Li, Bin Liang^*

Phyton-International Journal of Experimental Botany, Vol.90, No.4, pp. 1233-1246, 2021, DOI:10.32604/phyton.2021.014962

Abstract Greenhouse vegetable cultivation (GVC) is an example of intensive agriculture aiming to increase crop yields by extending cultivation seasons and intensifying agricultural input. Compared with cropland, studies on the effects of farming management regimes on soil microorganisms of the GVC system are rare, and our knowledge is limited. In the present study, we assessed the impacts of different long-term fertilization regimes on soil fungal community structure changes in a greenhouse that has been applied in tomato (Solanum lycopersicum L.) cultivation for 11 consecutive years. Results showed that, when taking the non-fertilizer treatment of CK as a benchmark, both treatments of… More >

MOHAMMAD FAIZAN¹, AHMAD FARAZ², SHAMSUL HAYAT³, JAVAID A. BHAT^4,*, FANGYUAN YU^1,*

BIOCELL, Vol.45, No.4, pp. 1081-1093, 2021, DOI:10.32604/biocell.2021.015363

Abstract Nanotechnology has greatly expanded the applications of nanoparticles (NPs) domain in the scientific field. In this context, the zinc oxide nanoparticles (ZnO-NPs) and 24-epibrassinolide (EBL) has been revealed to positively regulate plant metabolism and growth. In the present study, we investigated the role of ZnO-NPs and EBL in the regulation of plant growth, photosynthetic efficiency, enzymes activities and fruit yield in tomato. Foliar treatment of ZnO-NPs at three levels (10, 50 or 100 ppm) and EBL (10⁻⁸ M) were applied separately or in combination to the foliage of plant at 35–39 days after sowing (DAS); and the control plants were… More >

THARANGANI WELEGAMA¹, MOHD Y. RAFII^1,2,*, KHAIRULMAZMI AHMAD^1,3, SHAIRUL I. RAMLEE^1,2, YUSUFF OLADOSU¹

BIOCELL, Vol.45, No.4, pp. 1069-1079, 2021, DOI:10.32604/biocell.2021.014354

Abstract Tomato (Solanum lycopersicum L.) belonging to the family Solanaceae is the second most consumed and cultivated vegetable globally. Since the ancient time of its domestication, thousands of cultivated tomato varieties have been developed targeting an array of aspects. Among which breeding for yield and yield-related traits are mostly focused. Cultivated tomato is extremely genetically poor and hence it is a victim for several biotic and abiotic stresses. Among the biotic stresses, the impact of viral diseases is critical all over tomato cultivating areas. Improvement of tomato still largely rely on conventional methods worldwide while molecular approaches, particularly Marker Assisted Selection… More >

Yang Wu¹, Lihong Xu^1,*, Erik D. Goodman²

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 561-576, 2021, DOI:10.32604/iasc.2021.016415

Abstract Deep convolutional neural network (DCNN) requires a lot of data for training, but there has always been data vacuum in agriculture, making it difficult to label all existing data accurately. Therefore, a lightweight tomato leaf disease identification network supported by Variational auto-Encoder (VAE) is proposed to improve the accuracy of crop leaf disease identification. In the lightweight network, multi-scale convolution can expand the network width, enrich the extracted features, and reduce model parameters such as deep separable convolution. VAE makes full use of a large amount of unlabeled data to achieve unsupervised learning, and then uses labeled data for supervised… More >