Performance of High Yielding Promising Sugarcane Variety for Western Zone of Tamilnadu

Sugarcane is an important commercial crop cultivated in over 23,000 ha in Erode district of TamilNadu state. Attempts were made by researchers and extension workers to improve the productivity of sugarcane by adopting high yielding varieties and improved production technologies. The on-farm trials were conducted during Kharif 2017 and 2018 in five farmers’ field to assess the performance of high yielding promising sugarcane varieties suitable for Western Zone of TamilNadu. The varieties selected for trial were Co 86032 and Co 0212. The study revealed that Co 0212 recorded more number of productive tillers per plant (10.4), intermodal length (14.51 cm), stem girth (11.22) and individual cane weight (1.511 kg) which was superiorly higher than the existing variety Co 86032. Similarly Co 0212 recorded the yield of 127.5 ton / ha during 2017 which was 17.24 per cent higher yield than the existing variety and 138.86 ton / ha recorded and 30.68 per cent yield advantage was noticed in the ratoon crop. The highest benefit cost ratio of 2.44 was recorded in Co 0212 in ratoon crop and 2.05 in first crop where as 1.73 and 1.86 BCR observed in Co 86032 in first and ratoon crop respectively. Considering the above facts, Co 0212 would be identified as a better alternate variety suitable for the Western Zone of TamilNadu

Performance of genetic imputation across commercial crop species

We show that accurate imputation can be carried out in three commercial plant species (maize, sugar beet and wheat) and that accurate imputation does not require a pedigree, although pedigree information can improve accuracy and speed. Our approach uses a hidden Markov model to build a haplotype library from individuals genotyped at high-density and then uses this library to impute low-density genotyped individuals to high-density. To build the library, we use founders when the pedigree is known, or a sample of progeny when the pedigree is unknown. Without a pedigree, and with 50 individuals genotyped at high-density and 100 low-density markers per chromosome, the median accuracies were 0.97 (maize), 0.96 (sugar beet), and 0.94 (wheat). We obtained similar accuracies with a pedigree. For biparental crosses with 100 markers per chromosome, median accuracies were 0.96 (maize), 0.96 (sugar beet) and 0.94 (wheat). For the imputation scenarios without a pedigree, we compared accuracies with those obtained by running Beagle 5.1. In all but one scenario, our method outperformed Beagle. We believe that plant breeders can effectively apply imputation in many crop species.

Learning of a mimic odor combined with nectar nonsugar compounds enhances honeybee pollination of a commercial crop

The increasing demand on pollination services leads food industry to consider new strategies for management of pollinators to improve their efficiency in agroecosystems. Recently, it was demonstrated that feeding beehives food scented with an odorant mixture mimicking the floral scent of a crop (sunflower mimic, SM) enhanced foraging activity and improved recruitment to the target inflorescences, which led to higher density of bees on the crop and significantly increased yields. Besides, the oral administration of nonsugar compounds (NSC) naturally found in nectars (caffeine and arginine) improved short and long-term olfactory memory retention in conditioned bees under laboratory conditions. To test the effect of offering of SM-scented food supplemented with NSC on honeybees pollinating sunflower for hybrid seed production, in a commercial plantation we fed colonies SM-scented food (control), and SM-scented food supplemented with either caffeine, arginine, or a mixture of both, in field realistic concentrations. Their foraging activity was assessed at the hive and on the crop up to 90 h after treatment, and sunflower yield was estimated prior to harvest. Our field results show that SM + Mix-treated colonies exhibited the highest incoming rates and densities on the crop. Additionally, overall seed mass was significantly higher by 20% on inflorescences close to these colonies than control colonies. Such results suggest that combined NSC potentiate olfactory learning of a mimic floral odor inside the hive, promoting faster colony-level foraging responses and increasing crop production.

Knowledge of Farmers on Improved Cotton Production Practices in Yadadri Bhuvanagiri District of Telangana

India is the pioneer country for the commercial cultivation of cotton. Cotton is one of the principal commercial crops and has been one of the main sources of India's economic growth and foreign exchange earner. It is popularly known as ‘White Gold’. In india it is important cash and commercial crop valued for its fiber and vegetable oil. The study was conducted in Ramannapet block of Yadadri Bhuvanagiri District was selected purposively based on the maximum cotton grower and 120 respondents were selected randomly from six villages of the ramannapet block. The data was collected with the help of structured schedule analyzed statistically. The study revealed that majority of respondents had medium level of socio-economic status and knowledge on recommended improved production practices of cotton. To access the knowledge of the respondents about improved cotton production practices.

Understanding Root Biology for Enhancing Cotton Production

Cotton is an important commercial crop grown in India. It occupies an area of about 12.7 million hectares and is grown both in irrigated as well as rainfed tracts. In such situations, roots are very important organ for plant growth and development, since they act as anchors, providing mechanical support, and chemical extractors for the growing plant. Root length density sets the proportion of water uptake both under wet conditions and dry soils. Cotton plants with efficient root system capture water and nutrients from soil having these features of longer tap root. It is widely accepted that breeding efforts on aboveground traits are not sufficient to the necessary yield advantage. Shifting the emphasis to analyzing the root system would provide an additional means to enhance yield under changing climatic condition. Belowground image analysis studies point to the importance of root system architecture for optimizing roots and rhizosphere dynamics for sustainable cotton production. In this review, we describe the cotton root biological context in which root-environment interactions providing an overview of the root growth morphology species wise, phytohormone action that control root growth, root anatomical significance in drying soils, biotic and abiotic stresses involved in controlling root growth and environmental responses.

Genomic diversity of Areca Palm Velarivirus 1 (APV1) in Areca palm (Areca catechu) plantations in Hainan, China

Background Areca palm (Areca catechu L.) is an important commercial crop in southeast Asia, but its cultivation is threatened by yellowing leaf disease (YLD). Areca palm velarivirus 1 (APV1) was recently associated with YLD, but little is known regarding its population and genetic diversity. To assess the diversity of YLD, the APV1 genome was sequenced in YLD samples collected from different sites in Hainan. Results Twenty new and complete APV1 genomes were identified. The APV1 isolates had highly conserved sequences in seven open reading frames (ORFs; > 95% nucleotide [nt] identity) at the 3′ terminal, but there was diversity (81–87% nt identity) in three ORFs at the 5′ terminal. Phylogenetic analysis divided the APV1 isolates into three phylogroups, with 16 isolates (> 70%) in phylogroup A. Mixed infections with different genotypes in the same tree were identified; this was closely correlated with higher levels of genetic recombination. Conclusions Phylogroup A is the most prevalent APV1 genotype in areca palm plantations in Hainan, China. Mixed infection with different genotypes can lead to genomic recombination of APV1. Our data provide a foundation for accurate diagnostics, characterization of etiology, and elucidation of the evolutionary relationships of APV1 populations.

Compartment Niche Shapes the Assembly and Network of Cannabis sativa-Associated Microbiome

Interactions between plants and microbes may promote the growth of plants and regulate the production of secondary metabolites. Hemp (Cannabis sativa) is an annual herb and an important commercial crop. However, the assembly and network of hemp-associated microbiomes inhabiting in soil and plant compartments have not been comprehensively understood. This work investigated the assembly and network of bacterial and fungal communities living in soils (bulk and rhizosphere) and plant compartments (root, stem, leaf, and flower) of four hemp ecotypes cultivated in the same habitat. Microbiome assembly was predominantly shaped by compartment niche. Microbial alpha diversity was the highest in soil, continually decreased from root to flower. Core bacterial genera Pseudomonas, Bacillus, Rhizobium, Planococcus, and Sphingomonas were mostly enriched in aerial endosphere niches; Clitopilus, Plectosphaerella, and Mortierella were enriched in belowground endosphere. Microbial network complexity and connectivity decreased from root to flower. According to source tracking analysis, hemp microbiota primarily originated from soil and were subsequently filtered in different plant compartments. This work provides details on hemp-associated microbiome along the soil–plant continuum and a comprehensive understanding of the origin and transmission mode of endophytes in hemp.

Fusarium oxysporum f. sp. niveum Molecular Diagnostics Past, Present and Future

Watermelon is an important commercial crop in the Southeastern United States and around the world. However, production is significantly limited by biotic factors including fusarium wilt caused by the hemibiotrophic fungus Fusarium oxysporum forma specialis niveum (Fon). Unfortunately, this disease has increased significantly in its presence over the last several decades as races have emerged which can overcome the available commercial resistance. Management strategies include rotation, improved crop resistance, and chemical control, but early and accurate diagnostics are required for appropriate management. Accurate diagnostics require molecular and genomic strategies due to the near identical genomic sequences of the various races. Bioassays exist for evaluating both the pathogenicity and virulence of an isolate but are limited by the time and resources required. Molecular strategies are still imperfect but greatly reduce the time to complete the diagnosis. This article presents the current state of the research surrounding races, both how races have been detected and diagnosed in the past and future prospects for improving the system of differentiation. Additionally, the available Fon genomes were analyzed using a strategy previously described in separate formae speciales avirulence gene association studies in Fusarium oxysporum races.

​An Economic Analysis of Chilli Production in Tripura, India

Background: Chillies are one of the most widely used spices and a commercial crop. It is the most widely used universal spice and is named as the wonder spice. Tripura is one of the largest producers of a commercial crop of chilli in the entire north eastern state. Commercial cultivation of chilli is very profitable and can expect high revenue because of high market value or market demand in local markets. Under this backdrop, the paper attempts to study the economics of chilli production in Tripura, India. Methods: This study was conducted on a sample of 150 chilli growers in Dhalai district, West Tripura and the Sipahijala district of Tripura during 2019-20 as it is the highest chilli growing area. A personal interview method was used to collect the data and suitable statistical tools were used for analyzing the data. The cost of cultivation for chilli was calculated by using the CACP (Commission on Agriculture Cost and Prices) approach. Result: The study revealed that the majority of the respondents were under the age of 54 years, belonged to the schedule tribe category i.e., 48.66 per cent (24.33) followed by the general category i.e., 34.66 (17.33) and the schedule caste category i.e., 16.66 per cent (8.33). All the respondents were from farming families, mainly belonging to marginal and small land holdings. It has been observed that the maximum cost was incurred on total family labour, i.e., Rs. 41230.11, Rs. 56769.23 and Rs. 51972.17 respectively in West Tripura, Unakoti and South Tripura, whereas in the case of total hired labour cost, no was involved by the growers of South Tripura district. The total production of chilli was 2894.45 kg/ha and the overall return over cost C was determined at Rs. 104572.94 per ha. In the different districts, the return per rupee over cost C ranged from 1.99 to 2.44.

IoT Based Greenhouse Monitoring System Using Raspberry Pi

Whilst computerized greenhouse systems are common in commercial crop production, there are few equivalent, but less expensive, systems available for home greenhouses. As a result, the scope of this study is to build and make a smart greenhouse system that monitors and regulate domestic greenhouses both locally and remotely. This thesis concentrated on the design and implementation of a smart greenhouse system's user interface and networking paradigm. This concept presents a conceptual framework for transforming a traditional greenhouse into a smart greenhouse. The goal is for customers to be able to control and manage critical crop aspects depending on their own needs. A user-friendly Thingspeak service where real data is synced from the greenhouse to the cloud and a responsive greenhouse system are the end results.