How to control bacterial blight of pomegranate using weather station or IoT device or Farm…

How to control bacterial blight of pomegranate using weather station or IoT device or Farm monitoring device?

Fyllo executive explaining how to manage bacterial blight using Kairo device

The major production constraint in pomegranate is bacterial blight disease caused by the pathogen Xanthomonas axonopodis pv. punicae. The disease is more severe in all the pomegranate growing areas of Maharashtra, Karnataka, Andhra Pradesh, Assam, Rajasthan, Gujarat and Tamil Nadu resulting in 60–80% yield losses under favourable environmental conditions (Sharma et al., 2021).

Symptoms:

Bacterial blight (telya disease in marathi) of pomegranate produced different kinds of symptoms on the leaves, stems and fruits. On the leaves, the symptoms appear as small, irregular prominent water-soaked spots, which later become necrotic with a light to dark brown centre surrounded by water-soaked margin. At the advanced stage, the individual spots coalesced, giving them a blight appearance. Fruits exhibit isolated water-soaked lesions followed by necrosis with small cracks, leading to splitting of the entire fruit, which leads to ‘Y’ or ‘L’ shaped cracking. Also cause lesions on twigs and shoots, leading to dieback and stunted growth. ​Infected areas may exude a gummy substance.

Water-soaked lesions in initial stage, water-soaked lesions in advanced stage, enlarged necrotic lesions with cracks and dried white encrustation of bacterial ooze on spots

Favourable Conditions:

Environmental factors such as high humidity (>60%) and temperature (25–33°C) coupled with intermittent rainfall (>10mm) and cloudy weather can create favourable conditions for the occurrence of bacterial blight of pomegranate. Above mentioned parameters are in general but the multiple abiotic factors contributing to the disease severity will differ. At Fyllo, we employ real-time data from your farm to forecast disease occurrences in advance. Below, we present a graphical depiction of disease prediction in two distinct Indian locations: Gujarat and Solapur.

Case study:

Disease prediction models developed by Fyllo were deployed across different geographical locations of India. Models deployed at Solapur and Gujarat showed a high probability of bacterial blight occurrence in pomegranate crops in Solapur compared to Gujarat, consistently from September to April, except for May due to sudden high rainfall in Gujarat. Analysis of weather patterns in both locations revealed that Solapur experienced uniform rainfall distribution throughout the analysed months, while Gujarat showed sporadic rainfall, particularly in September and May. Additionally, Solapur maintained higher average relative humidity levels. Given that wind-borne rain splashes are essential for bacterial pathogen spread, these findings highlight the crucial role of rainfall in pathogen occurrence and dissemination, as supported by both predictive models and field observations. Consequently, leveraging weather-based predictions through IoT technologies becomes imperative for proactively managing farm operations in such conditions.

Graphs for case study on pomegranate
Graph for case study on pomegranate

Management:

The most crucial aspect of managing bacterial blight in pomegranate orchards is maintaining field sanitation; affected leaves, stems, and fruits should be removed and burned. Immediately after pruning, 1% Bordeaux mixture should be sprayed, and in severely affected orchards, the cuts should be treated with Bordeaux paste. And also apply bleaching powder (20–25 kg/ha) at the base of the plant in the early morning (100 g/plant). Once new growth starts, during the cropping season, the crop should be sprayed with either Streptocyclin 0.5g + Copper Oxychloride 2.5 g/L or Streptocyclin 0.5g + Captan 2.5 g/L, or Kasugamycin + Copper Oxychloride 1–1.5 g/L. It is important not to use a single combination continuously; instead, alternate between the above-mentioned treatments at 15-day intervals. If the disease pressure is high, then Hasta Bahar is effective in reducing the disease.

It is difficult to control the disease once it’s established in the field, so continuous monitoring of the disease is required under field conditions, which is possible through agriculture IOT devices. Fyllo’s data-driven insights can help farmers to predict the occurrence of diseases and pests. This allows farmers to take preventive measures to protect their crops, such as spraying pesticides or applying fertilizers at the right doses.

Listen to one of our farmer Bapu Dabade from Solapur district (Maharashtra) who is using Fyllo device to manage his pomegranate farm.

https://youtu.be/_-GERAO2KXY

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