The Yield and Diseases-Pest Performance of Breeding Materials for Tomatoes (Lycopersicon esculentum) Sourced from Different Exotic Sources

A study was conducted with 36 tomato germplasm [PGRC (19), The Netherlands (7), Japan (2), and Bangladesh (9)] with 3 check varieties in the research field of the Olericulture Division of Horticulture Research Centre (HRC), Bangladesh Agricultural Research Institute (BARI), Gazipur during the winter season of 2022-23 to identify promising tomato breeding germplasm. All the germplasm showed differences in most of the parameters studied. Considerable variation was observed for fruit yield per hectare varied from 39 to 144 tons, while the highest fruit yield per hectare was harvested from the germplasm viz., BD 7759B, BD 7757, BD 7751, BD 7301, QM, BD 7759A, BD 7762, QF, BD 7753, BD 8886, BD 10351, NL-1A, SLA-19. The number of locules, total soluble solids (TSS) and plant height at last harvest varied from 2 to 6.6, 2.6 to 5.9%, and 66 to 154cm, respectively. The TYLCV infection (%) and leaf-sucking pest infestation (%) were observed with a 1 to 20% range in the field condition in both cases. So, we can select that germplasm has zero per cent infestation. Considering the plant growth habit, earliness, different yield contributing horticultural traits, virus and pest infestation thirteen germplasm viz., BD 7759B, BD 7757, BD 7751, BD 7301, QM, BD 7759A, BD 7762, QF, BD 7753, BD 8886, BD 10351, NL-1A, SLA-19 were selected as breeding materials for further tomato improvement program.

Determining the Effects of Selected Organic Fertilizer on Growth and Yields of Tomato (Lycopersicon esculentum: Var. Rio Grande Tomatoes) in Mundri West County, Western Equatoria State, South Sudan

Worldwide, the demand for agro-organic foods that are healthy, nutritious, and environmentally friendly is increasing dramatically across all nations among consumers. Tomatoes being one of the dietary requirements in almost every meal is not exceptional and its availability in the market all year round is very important to farmers as well as consumers because it is highly demanded as a vegetable par excellence;which is either eaten raw in salads, cooked or processed into liquid ingredients. This study investigates the impact of chicken, goat, and cow manure treatments on tomato plant growth response to height, leaf length, and width, as well as fruit yield. The experimental field trials were conducted over two planting seasons in Mundri West County. It followed a Complete Randomized Design (CRD) approach, consisting of four blocks. Each block contained three treatments replicated four times and a control group. The data of measured parameters from all 16 plots were subjected to one-way Analysis of Variance (ANOVA) using the Gen Stat 14th Edition software. The findings indicate significant differences (P < 0.05) among all the different organic manure applications on tomato plant growth parameters compared to the control group. Chicken manure resulted in the tallest tomato plants (30.1 and 37.9 cm), longest leaves (9.9 and 10.4 cm), and widest leaves (2.1 and 2.5 cm) in both seasons respectively. The study showed plots treated with chicken manure had a highly significant impact (P < 0.05) on the prevalence of aphids (1.0) and white flies (1.4) with the lowest value compared to those with cow and goat manure applied. Additionally, chicken manure led to the highest yields (39.30 and 49.49 tons/ha) in both seasons. Based on these findings, it can be concluded that using chicken manure effectively improves the performance of Rio Grande Tomatoes, and thus, farmers are encouraged to utilize chicken manure to maximize their tomato yields.

基于改进ResNet模型的番茄叶片病虫害识别

识别早期番茄叶片的病虫害是预防番茄病虫害、提升产量的关键步骤之一。基于改进ResNet50识别番茄叶片病虫害。根据不同病虫害类别创建5种不同番茄病虫害数据集,并采用数据增强方式对数据进行预处理。在原始模型ResNet50的基础上,通过在网络模型结构中添加SE注意力机制模块让模型能够更准确地识别待检测目标。此外为了减少模型的参数量,实现更加轻量化的模型,利用深度可分离卷积替换传统卷积。为了说明改进模型的有效性,分析改进后的模型在番茄叶片病虫害数据集上的性能,将其与传统卷积神经网络ResNet50、AlexNet、VGG16、GoogLeNet进行对比。实验结果表明,改进后的模型相较于原模型参数量降低了37.5%,准确率达到了97.4%,与原模型相比,其准确率提升了4.4%。综上所述,本模型实现了性能与参数量之间的良好平衡,为后续在实际环境中番茄叶片病虫害识别系统部署提供可能。

基于超轻量化卷积神经网络的番茄病虫害诊断

针对番茄病虫害诊断中存在的传统卷积神经网络结构复杂、难以直接应用于便携终端,以及现有轻量化卷积神经网络特征提取能力弱、识别准确率低、难以满足实际需要等问题,本研究拟在原有轻量化卷积神经网络的基础上,定义超轻量化卷积神经网络,设计一种基于SqueezeNet网络改进的超轻量化卷积神经网络,将其用于番茄病虫害诊断任务中。首先,改进SqueezeNet网络中的Fire模块,生成2种适用于不同特征维度的Fire模块,并引入ECA(高效通道注意力)模块以提高模型的特征提取能力;其次,结合扩展型指数线性单元函数(SELU)和Mish函数,替代修正线性单元函数(ReLU)作为激活函数;再次,采用软池化(Softpool)替代原始的最大池化;最后,利用中心损失函数(Center loss)改进指数归一化损失函数(Softmax loss),提高对近似病虫害的识别准确率。本研究选择了8种害虫和9种病害,对害虫、病害、病虫害3类数据集进行数据增强,并探讨了数据的小样本性、不平衡性对模型性能的影响。结果表明,本研究提出的模型具有超轻量化的特点,对害虫、病害、病虫害的识别准确率最高分别可达98.83%、98.14%和97.71%,能够很好地满足番茄病虫害诊断需求。

设施农业臭氧杀菌闭环控制系统设计与试验

为更好地解决设施栽培过程中出现的病虫害问题,设计一款面向设施农业的臭氧杀菌闭环控制系统。该系统以STM32F103C8T6单片机为核心,由臭氧发生器、高速风机、臭氧浓度传感器、计时器和报警器组成闭环控制系统。当系统信号采集模块检测到设施空间中臭氧浓度时,通过检测电路将采样信号传递给控制器,控制器根据系统设定值判断并控制臭氧发生器等执行机构工作,实现臭氧浓度的精准控制,减轻臭氧浓度不适给设施蔬菜带来的严重伤害。系统设定浓度为60 mg/m^(3),系统稳定后工作时长30 min。以此为基础,应用臭氧杀菌闭环控制系统对温室番茄叶霉病、灰霉病进行防治试验。结果表明,使用该系统防控对番茄叶霉病、灰霉病的防效优于常规防治,在温室番茄全成长期,叶霉病、灰霉病发生率均显著下降,防治效果分别为89.3%、92.2%。

番茄种植技术及病虫害防治措施探讨

番茄深受人们的喜爱,在我国得到了广泛种植。为了给人们提供更加优质的番茄,需要借助全面系统的管理,使其整个生长过程不受外界因素的不利影响,促进其健康茁壮生长。对此,该文主要对番茄种植技术和病虫害防治措施进行了探讨,以供参考。

凌海市日光温室番茄冬春茬栽培模式探讨

日光温室番茄能够减少气候、温度等因素带给番茄生产的影响,有助于增加农户收入。阐述日光温室番茄的栽培要点,总结番茄种植中容易出现的病虫害及防治方法,以期为当地农户从事日光温室番茄的高效生产提供参考依据。

基于改进YOLOv7-tiny的番茄叶片病虫害检测方法

为解决自然环境中番茄叶片病虫害检测场景复杂、检测精度较低,计算复杂度高等问题,该研究提出一种SLPYOLOv7-tiny的深度学习算法。首先,将主干特征提取网络中部分3×3的卷积Conv2D(2D convolution)改为分布偏移卷积DSConv2D(2D Depthwise Separable Convolution),以减少网络的计算量,并且使计算速度更快,占用内存更少;其次,将无参数注意力机制(parameter-free attention module,SimAM)融合到骨干特征提取网络中,加强模型对病虫害特征的有效提取能力和特征整合能力;最后,将原始YOLOv7-tiny的CIOU损失函数,更替为Focal-EIOU损失函数,加快模型收敛并降低损失值。试验结果表明,SLP-YOLOv7-tiny模型整体识别精准度、召回率、平均精度均值mAP_(0.5)(IOU阈值为0.5时的平均精度)、mAP_(0.5~0.95)(IOU阈值从0.5到0.95之间的平均精度)分别为95.9%、94.6%、98.0%、91.4%,与改进前YOLOv7-tiny相比,分别提升14.7、29.2、20.2、30个百分点,同时,计算量降低了62.6%。与YOLOv5n、YOLOv5s、YOLOv5m、YOLOv7、YOLOv7-tiny、Faster-RCNN、SSD目标检测模型相比,mAP_(0.5)分别提升了2.0、1.6、2.0、2.2、20.2、6.1和5.3个百分点,而计算量大小仅为YOLOv5s、YOLOv5m、YOLOv7、Faster-RCNN、SSD的31.5%、10.6%、4.9%、4.3%、3.8%。结果表明SLP-YOLOv7-tiny可以准确快速地实现番茄叶片病虫害的检测,且模型较小,可为番茄叶片病虫害的快速精准检测的发展提供一定的技术支持。

Botanicals and plant strengtheners for potato and tomato cultivation in Africa

This review provides a summary of botanicals and plant strengtheners that have potential uses for disease and pest management in potato and tomato cultivation in African.We discuss their possible use to prevent major diseases and pests which infest potato and tomato,such as early and late blight,bacterial wilt,potato tuber moth,and tomato leafminer.There are several examples of the successful uses of botanicals for pathogen and pest control relevant for different African climatic conditions;however,most of these studies have been conducted in vitro and often lack field verification.Plant strengtheners(substances that induce and improve crop resistance,yield,and quality)are little studied and used in Africa in comparison to North America and Europe.The possible benefits of using botanicals and plant strengtheners instead of conventional pesticides are discussed here in relation to human health and the environment as well as their modes of action and accessibility to farmers.Lack of knowledge of the composition and active ingredients of extracts,environmental concerns,uncertainties regarding stability and formulation,lack of legislation and limited support from governments,hamper the development of botanicals and plant strengtheners for use in sustainable African agriculture.

基于物联网的番茄早疫病自动监测预警平台的应用与研究

早疫病是对番茄生产影响较大的一种病害,但现有检测手段落后。为此,利用无线传感器、物联网、数据分析等现代信息技术与传统农业相结合,开展番茄早疫病自动检测预警研究。采用传感网络对番茄病害环境因子进行数据采集,并通过数据融合分析,建立番茄早疫病发生等级与环境因子相关的预警模型,构建番茄早疫病自动监测预警平台,实现对产地番茄病害实时动态监测和预警,可为番茄早疫病测报防治提供一种高效、自动化的技术和手段。该研究既能为番茄早疫病测报提供重要的技术和信息支撑,又可为其他相关治理发展提供参考。

改进DCGAN数据增强的番茄叶子病害图像识别

针对番茄叶子病害图像难以采集的问题,提出一种基于生成对抗网络的番茄叶子病害图像增强方法——Residual Network and Wasserstein Attached Spectral Normalization DCGAN(RWS_DCGAN)。带有谱归一化的残差网络结构构建了新型的生成器模型和判别器模型,引入带有梯度惩罚项的Wasserstein距离。通过实验表明,改进的生成对抗网络RWS_DCGAN相较于常规增强方法和DCGAN增强方法,能生成病害明显的番茄叶子病害图像,扩充样本数据集,进而能提升分类网络的识别准确率。

设施番茄病虫害特点及绿色防控技术

番茄是我国重要的蔬菜,近年来随着集约化种植水平的提高,番茄病虫害越来越制约产业的高质量发展。为便于番茄种植者及时发现和诊断番茄病虫害发生情况,该文对目前番茄病虫害发生特点进行梳理分析,同时提出通过优化栽培措施,结合物理和生物防治手段,辅以高效、低毒、低残留的化学农药等构建番茄病虫害绿色防控体系,以期为番茄产业的绿色高效发展提供参考。

大棚西红柿常见病虫害的防治

为提升大棚西红柿常见病虫害的防治效果,对大棚西红柿病虫害防治注意事项进行了介绍,如合理确定药物的适用范围、加强预防性措施等。提出了灰霉病、炭疽病、脐腐病、白粉虱等西红柿常见病虫害的防治要点,以期为相关人员提供科学参考。

大棚番茄栽培技术研究

随着现代农业技术的发展,大棚番茄种植规模不断扩大,通过加强栽培管理,为番茄生长营造适宜的生长环境,可实现番茄品质、产量的协同提升,实现经济效益最大化。该文从番茄育苗管理、定植管理、田间管理等方面对番茄栽培技术进行分析和探讨,以期为大棚番茄栽培生产提供参考。

十堰地区茄科蔬菜主要病虫害发生情况调查

本文选取3个辣椒品种和1个番茄品种,调查十堰地区茄科蔬菜病虫害发生情况,以期摸清病虫害发生规律,为当地茄科蔬菜病虫害科学防治提供参考依据,保障蔬菜生产安全。结果表明:十堰地区辣椒发生真菌性病害5种、生理性病害1种、虫害1种;番茄发生真菌性病害2种;病害重于虫害。其中,重发病害为辣椒白绢病和番茄晚疫病,发病率分别高达89.09%、100.00%,病情指数分别为90.30、100.00。

外来入侵害虫番茄潜叶蛾在朝阳地区为害及防控研究

番茄潜叶蛾是我国新发现的一种对蔬菜生产危害程度极高的毁灭性入侵害虫,在朝阳地区首次发生为害。介绍番茄潜叶蛾的形态特征、为害特点、发生规律及生活习性,提出化学、生物、物理防治方法及需要采取的农业措施,以期为朝阳地区及临近地区番茄潜叶蛾发生及为害起到警示作用,达到早识别、早预防、精准防控目的。

温室秋冬茬番茄定植后主要病虫害及防治

由于高温干燥和阴雨天气交错变化频繁,且棚室几乎全部采用开放式管理方式,温室秋冬茬番茄定植后到温室全封闭管理期间属于病虫害发生流行高风险时段,是茎基腐病、灰叶斑病、病毒病发生流行的主要时期,也是蓟马和粉虱向棚内转移增殖、危害的关键时期。做好这一阶段病虫害防治工作,有利于降低后期番茄病虫害的防治压力。该文对这一时期主要发生的几种病虫害危害特点加以介绍,并从栽培、物理、生物、药剂等防治角度罗列针对性的防治措施,以期为相关工作者提供参考。

Efficacy of Beneficial Fungi Isolates in Solanum lycopersicum L. Protection against Lepidopteran Insects through a Leaf Inoculation Technique

Helicoverpa armigera is a key insect pest of tomatoes reducing drastically yields. The effect of the endophytic colonization of tomato plants by Beauveria bassiana using leaf spray as an inoculation method on damage and survival of H. armigera was assessed in a screen house. Two B. bassiana isolates (Bb 115 and Bb 11) and two tomato varieties (a local variety Tounvi and an improved variety Padma) were included in the study. The adaxial and abaxial leaf surfaces were sprayed at a concentration of 107 conidia/ml and 109 conidia/ml for each isolate and each of the two tomato varieties. Thirty days after inoculation, five discs of tomato leaf and tomato root were cut for each isolate, each concentration per isolate and for each variety. The samples were incubated at room temperature (28°C ± 2°C) and periodically checked for fungal growth. Larval survival was checked and a damage assessment was done on tomato flowers and the leaves. The results show that the lowest Mean Survival Times (MSTs) were recorded on larvae feeding on plants inoculated with Bb 11 (4.2 ± 0.8 days against 11.5 ± 0.2 days for control). Compared to the other treatments, low damage rates of the flowers of the improved variety inoculated with Bb 11 at 109 conidia/ml were recorded from the 6th Day After Inoculation (DAI). This rate remains low until the end of treatment. Overall flower damage was lower than leaf damage. The results showed large differences in pathogenicity, with most endophytic isolate belonging to Bb 11 when inoculated at 109 conidia/ml using the leaf spraying technique. Data were discussed with regard to the use of endophytism B. bassiana in an integrated tomato pest control approach.

基于BIGRU的番茄病虫害问答系统问句分类研究

问句分类作为问答系统的关键模块,对系统检索效率具有决定性作用。为了对番茄病虫害智能问答系统用户问句进行高效分类,构建了基于word2vec和双向门控循环单元神经网络(Bi-directional gated recurrent unit,BIGRU)的番茄病虫害问句分类模型。针对问答系统对用户问句的语义信息有较高要求的特点,首先利用word2vec将句子中的词转换为具有语法、语义信息的词向量,利用训练得到的词向量和BIGRU神经网络进行问句分类模型的训练。实验选取了2 000个番茄病虫害相关的用户问句,主要分为番茄病害和番茄虫害两类。结果表明,采用BIGRU的番茄病虫害问句分类模型,其分类准确率、召回率和准确率与召回率的调和平均值F1分别高于卷积神经网络(CNN)、K最近邻等分类算法2~5个百分点。BIGRU模型结构简单,模型训练参数较少,模型训练速度快,符合问答系统对响应时间的要求。

基于高光谱的番茄叶片斑潜蝇虫害检测

番茄植株在生长过程中受病虫害的侵染,将导致番茄减产和种植户的经济效益降低,该研究用高光谱技术结合化学计量学方法,实现了番茄叶片斑潜蝇虫害的快速识别。搭建了简易的高光谱成像系统,包括光源单元、高光谱图像采集单元和数据处理单元,用该系统获取番茄叶片的高光谱图像,对高光谱图像进行校准,并从每一幅图像中提取光谱信息。分别采用了光谱角匹配(SAM)分析方法和光谱红边参数判别分析(DA)方法识别番茄叶片斑潜蝇虫害。在SAM分析中,对高光谱数据进行了归一化预处理,以消除多余信息,增加样品之间的差异。比较了以不同番茄叶片样品的反射光谱作为测试光谱时,虫害识别效果的差异,当以受到斑潜蝇侵染的番茄叶片的平均反射光谱作为测试光谱时,虫害识别的正确率较高,达到96.5%。在光谱红边参数判别分析中,从光谱数据中提取了红边位置、红边振幅、最小振幅、红边面积、红谷位置和红边振幅/最小振幅6组红边信息,利用判别分析方法建立番茄叶片斑潜蝇虫害的判别模型,比较了距离判别、Fisher判别、Bayes判别分析方法的判别效果,使用距离判别分析建模的判别正确率最低,判别正确率为88.0%,使用Fisher判别分析建模的效果最佳,判别正确率为96.0%。研究结果表明,采用高光谱技术识别番茄叶片斑潜蝇虫害具有可行性。