Diversity and abundance of insects on Potato, Mustard and Tomato in winter at Mitchells farm, Okara, Pakistan

Abundance is defined as the relative representation of species in a particular area. It is usually measured as the number of individuals found per sample. The abundance of insects was recorded from the selected fields of mustard, potato and tomato fields. Samples were collected by applying quadrant method, simple tools were used i.e. sweep nets and direct handpicking. Hemiptera, Lepidoptera and Hymenoptera were the main orders of the insects that were most abundant and effecting the selected fields. Total collected specimens were numbered as 117, out of which 65 specimens were recorded from mustard 36 from tomato and 16 from potato field. The results indicate that insects have subsequent association with their host vegetables at leafy stage. A maximum abundance of insects was found in mustard fields and least in Potato field. A common insect found among all fields was the budworm. Abundance was recorded less because of some factors i.e. low temperature and pesticides.

Pan-genome analysis identifies intersecting roles for Pseudomonas specialized metabolites in potato pathogen inhibition

Agricultural soil harbors a diverse microbiome that can form beneficial relationships with plants, including the inhibition of plant pathogens. Pseudomonas spp. are one of the most abundant bacterial genera in the soil and rhizosphere and play important roles in promoting plant health. However, the genetic determinants of this beneficial activity are only partially understood. Here, we genetically and phenotypically characterize the Pseudomonas fluorescens population in a commercial potato field, where we identify strong correlations between specialized metabolite biosynthesis and antagonism of the potato pathogens Streptomyces scabies and Phytophthora infestans. Genetic and chemical analyses identified hydrogen cyanide and cyclic lipopeptides as key specialized metabolites associated with S. scabies inhibition, which was supported by in planta biocontrol experiments. We show that a single potato field contains a hugely diverse and dynamic population of Pseudomonas bacteria, whose capacity to produce specialized metabolites is shaped both by plant colonization and defined environmental inputs.

First report of late blight caused by Phytophthora infestans in potato in Tibet Autonomous Region of China

Late blight caused by Phytophthora infestans (Mont.) De Bary is the most destructive diseases in the potato field. Although it has been studied worldwide, it has not been reported in Tibet Autonomous Region of China, lying on the world’s highest plateau. To investigate whether the disease caused by P. infestans occurred in such region, a survey on potato disease was conducted in the summer in 2020. In August, potato (Solanum tuberosum) of the cultivar ‘Longshu 10’ with diseased leaves was observed in a potato field in Shigatse city in Tibet Autonomous Region (29.3N,88.8E). The necrotic brown lesions were shaped in round or irregularly with whitish growth of sporangium-producing structures on the underleaf surface, similar to typical late blight symptom. Affected leaves were collected for pathogen isolation. The abaxial side of the decayed leaves showed grey zones of sporulation. Upon isolation, three isolates were used for further investigation. The mycelium grew averagely at a linear rate of 4.35 mm per day at 19oC on Rye B agar (RBA, containing 50 g/L rye and 12 g/L agar), forming white colony. The opaque and lemon-shaped spores with a papilla at the distal end (Figure S1) had an average size of 36.2ⅹ20.3 µm, the shape and size consistent with P. infestans (Cardenas et al. 2011; Winton et al. 2007). The ribosomal ITS1-5.8S-ITS2 region was amplified from genomic DNA obtained from mycelium using primers ITS1 and ITS4 (Glass and Donaldson 1995). The sequences with 829 bp in size obtained from three isolates were identical, among which one of the sequences from Tibet isolate RKZ_27 was submitted to GenBank with Accession No. of MW559423. A BLAST search in NCBI (National Center for Biothchnology Information) revealed MW559423 had the highest similarity (100%) to P. infestans sequences (GenBank Accession No. of MK507866, MH401206 and KU992300). In addition, a partial nucleus DNA sequence from elongation factor 1-α (EF1-α) was amplified using primer set of EF_F/ EF_R (EF_F: 5’GGCCTTGACGACATCCAGAA3’; EF_R: 5’TAGCAGCTCAACCCGAAGTG3’), and a partial mitochondria DNA sequence (P2 region) including partial ATP synthase F1 subunit α gene (atp1), tRNA-Glu gene and partial NADH dehydrogenase subunit 4 (ND4) was amplified using primer set of P2F/P2R (P2F: 5’TTCCCTTTGTCCTCTACCGAT3’; P2R: 5’TTACGGCGGTTTAGCACATACA3’) (Vargas et al. 2009). The EF1-α and P2 region for three isolates were all identical and one of each sequence was submitted to GenBank with Accession No. of MZ189257 and MZ399710, respectively, which had 99.78% (XM_002998924.1) and 100% (MG869098) similarity with P. infestans, respectively. Phylogenetic analyses showed that the RKZ_27 was close to P. infestans (Figure S2). Pathogenicity was confirmed by inoculating ten potato leaves cv. ‘Favorita’ for each isolate with a 5 mm in diameter mycelium plug on each leaf. After 3 days of incubation at 19 oC in air-tight plastic bags, the inoculated leaves developed typical symptoms of late blight. All control leaves treated with distilled water remained healthy. The pathogenicity of three isolates were also confirmed by inoculating potato seedlings cv. ‘Favorita’ with sporangia suspension. The pathogen re-isolation on inoculated symptomatic leaves and seedlings were confirmed to be P. infestans by the morphological characteristics, which was fulfilled Koch postulates. The pathogenicity test both on leaves and seedlings were conducted twice. To our knowledge, this is the first report of P. infestans in potato field in Tibet Autonomous Region of China. The finding of potato late blight in this region have important epidemiological implications for the growers especially under favorable environmental conditions.

Quantification of Phytophthora infestans population densities and their changes in potato field soil using real-time PCR

Tuber infection of Phytophthora infestans often occurs at harvest. However, it is difficult to accurately estimate the population densities of P. infestans in soil, especially Japanese soil. In the present study, P. infestans DNA was extracted from soil samples using a modified CTAB-bead method and quantified using real-time PCR to accurately, rapidly and easily estimate the P. infestans population densities in upland soils in Japan. P. infestans was well quantified in eleven types of soil samples, including nine types of upland soils in Japan, that were artificially inoculated with a zoosporangia suspension. The amounts of P. infestans DNA estimated by the real-time PCR were proportional to the inoculum densities. In the non-controlled experimental potato field, P. infestans population densities in soil corresponded to the development of symptoms and were correlated with the number of lesions on the potato foliage. These results imply that the proposed real-time PCR assay is suitable for the estimation or monitoring of P. infestans population densities in upland soils in Japan. The population densities at the ridge bottoms were larger than those at any other location in commercial potato fields. These results were similar to those of a previous report using a bioassay. Moreover, a correlation between DNA quantity and inoculum potential was observed. In conclusion, the real-time PCR assay developed in this study is suitable for indirect estimation of the inoculum potential of P. infestans.

Growth Stages Classification of Potato Crop Based on Analysis of Spectral Response and Variables Optimization

Potato is the world’s fourth-largest food crop, following rice, wheat, and maize. Unlike other crops, it is a typical root crop with a special growth cycle pattern and underground tubers, which makes it harder to track the progress of potatoes and to provide automated crop management. The classification of growth stages has great significance for right time management in the potato field. This paper aims to study how to classify the growth stage of potato crops accurately on the basis of spectroscopy technology. To develop a classification model that monitors the growth stage of potato crops, the field experiments were conducted at the tillering stage (S1), tuber formation stage (S2), tuber bulking stage (S3), and tuber maturation stage (S4), respectively. After spectral data pre-processing, the dynamic changes in chlorophyll content and spectral response during growth were analyzed. A classification model was then established using the support vector machine (SVM) algorithm based on spectral bands and the wavelet coefficients obtained from the continuous wavelet transform (CWT) of reflectance spectra. The spectral variables, which include sensitive spectral bands and feature wavelet coefficients, were optimized using three selection algorithms to improve the classification performance of the model. The selection algorithms include correlation analysis (CA), the successive projection algorithm (SPA), and the random frog (RF) algorithm. The model results were used to compare the performance of various methods. The CWT-SPA-SVM model exhibited excellent performance. The classification accuracies on the training set (Atrain) and the test set (Atest) were respectively 100% and 97.37%, demonstrating the good classification capability of the model. The difference between the Atrain and accuracy of cross-validation (Acv) was 1%, which showed that the model has good stability. Therefore, the CWT-SPA-SVM model can be used to classify the growth stages of potato crops accurately. This study provides an important support method for the classification of growth stages in the potato field.

The spatial variability of soil water content in a potato field before and after spray irrigation in arid northwestern China

Assessing the spatial variability of soil water content is important for precision agriculture. To measure the spatial variability of the soil water content and to determine the optimal number of sampling sites for predicting the mean soil water content at different stages of the irrigation cycle, field experiments were carried out in a potato field in northwestern China. The soil water content was measured in 2016 and 2017 at depths of 0–20 and 20–40 cm at 116 georeferenced locations. The average coefficient of variation of the soil water content was 20.79% before irrigation and was 16.44% after irrigation at a depth of 0–20 cm. The spatial structure of the soil water content at a depth of 20–40 cm was similar throughout the irrigation cycle, but at a depth of 0–20 cm a relatively greater portion of the variation in the soil water content was spatially structured before irrigation than after irrigation. The autocorrelation of soil water contents was influenced by irrigation only in the surface soil layer. To accurately predict mean soil moisture content, 40 and 20 random sampling sites should be chosen with errors of 5% and 10%, respectively.