Research Overview

Research Background: What Problem Did This Study Address?

Postharvest losses are a major challenge for smallholder farmers and food vendors in Sub-Saharan Africa. In countries such as Kenya, Uganda, and Nigeria, many fruits and vegetables are harvested, stored under natural shade, transported without refrigeration, and sold in local markets under high-temperature conditions. Without reliable cold storage, fresh produce loses water, softens, changes color, decays faster, and often becomes unsellable before reaching consumers.

Mechanical refrigeration and solar-powered cold rooms can help, but they are often too expensive, too complex, or inaccessible for remote smallholder communities. Traditional evaporative coolers, such as sand-brick coolers or charcoal cooling rooms, can also be difficult to build, scale, and move. This study addressed the need for a low-cost, electricity-free, portable cooling method that can be used in real farming and market conditions.

The researchers evaluated a passive cooling blanket, or PCB, across three countries: Kenya, Uganda, and Nigeria. The blanket was made from fabric compartments filled with porous cooling materials such as charcoal or sawdust. When water was added, evaporation absorbed heat from the surrounding air and fresh produce, lowering storage temperature and increasing relative humidity.

UbiBot WS1 Pro was used as part of the temperature and humidity monitoring setup. The monitored environmental data helped the research team compare storage conditions inside and outside the passive cooling blanket and assess how those conditions related to postharvest quality preservation.

The Specific Role of UbiBot in the Study

In this study, UbiBot WS1 Pro was used as part of the hygrothermal monitoring system for the passive cooling blanket trials. The paper does not state that UbiBot itself preserved the produce or proved the effectiveness of the blanket. Instead, UbiBot contributed environmental data—mainly temperature and relative humidity—that helped the researchers document cooling conditions and interpret produce quality outcomes.

The study was conducted across three field sites. In Kenya, trials were carried out at a mango processing farm in Karurumo, Embu County, during the dry season from July to September 2023. In Uganda, experiments were conducted at Makerere University Agricultural Research Institute Kabanyolo during the wet season from August to November 2023. In Nigeria, trials were hosted at the Nigerian Stored Products Research Institute in Ilorin between February and April 2024, during the dry-to-wet seasonal transition.

According to the sensor summary in Table 2 of the paper, UbiBot WS1 Pro was used in Kenya and Uganda as part of the ambient temperature and relative humidity monitoring setup. In these trials, the researchers also used other instruments, including Davis Vantage Pro2 in Kenya, Agriscope WS100 in Uganda, Onset HOBO devices in Nigeria, Sensirion SHT4x Smart Gadgets, and produce core-temperature loggers. This multi-sensor approach allowed the team to distinguish ambient conditions, blanket microclimate, and produce temperature responses.

UbiBot’s monitored environmental data supported three main research functions.

First, it helped document the field environment around the passive cooling blanket trials. Ambient temperature and relative humidity are essential because evaporative cooling performance depends on dry-bulb temperature, wet-bulb temperature, relative humidity, and airflow. Lower ambient humidity generally allows stronger evaporation and greater cooling.

Second, the temperature and humidity records helped evaluate the cooling performance of the passive cooling blanket. The researchers compared ambient shaded conditions with conditions created by the blanket. Across the three countries, the PCB consistently reduced storage temperature and increased relative humidity, although the magnitude differed by climate and season.

Third, these data were used together with produce quality measurements. The researchers measured weight loss, firmness, color change, total soluble solids, pH, and decay incidence. By combining environmental records with quality outcomes, the study could explain why produce stored inside the blanket experienced lower water loss, slower softening, delayed color changes, and extended shelf life.

Therefore, UbiBot’s role was environmental data collection for performance evaluation and contextual analysis. It provided part of the real-world temperature and humidity dataset needed to assess passive evaporative cooling under practical smallholder conditions.

Research Methods and Data Collection Approach

The study evaluated passive cooling blankets in Kenya, Uganda, and Nigeria under different climatic and operational conditions.

The blankets were constructed from burlap, hessian, or similar fabric divided into compartments and filled with locally available porous materials. Charcoal and sawdust were the main filler materials. Water was poured onto the outside of the blanket every one to three days, depending on local evaporative demand. The wet filler material then provided evaporative cooling, reducing storage temperature toward the local wet-bulb temperature.

In Kenya, the trials were conducted at Karurumo, Embu County, during the dry season. The produce tested included tomatoes, kale, peas, and courgettes. Both small and large passive cooling blankets were tested. The study compared airflow cooling, direct-contact cooling, natural shade storage, and a traditional large charcoal cooler. The Kenya setup is shown in the paper’s Figure 3, where produce crates and blanket configurations are displayed.

In Uganda, the trials were conducted at MUARIK during the wet season. The focus was tomato cv. Ansal at green, breaker, and red ripening stages. The passive cooling blanket was wrapped around plastic crates, and a transport simulation was also performed using local motorcycle transport from farm to market. The Uganda setup in Figure 3 shows crates under shade and a passive cooling blanket wrapped around tomato crates.

In Nigeria, the trials took place at NSPRI in Ilorin. Tomato cv. UTC was tested using a larger passive cooling blanket designed for bulk vendor storage. Natural shade was used as the benchmark. The Nigeria setup in Figure 3 shows tomatoes, quality measurement, and the larger outdoor blanket structure.

Environmental parameters, including ambient temperature and relative humidity, were monitored continuously using calibrated automated weather stations and hygrothermal sensors. UbiBot WS1 Pro was listed among the instruments used in Kenya and Uganda for ambient temperature and relative humidity monitoring. Additional sensors were placed inside produce crates, between blanket layers, and in shaded ambient air. Produce core-temperature loggers were also used to assess internal produce temperature.

Quality was evaluated through weight loss, firmness, color, pH, total soluble solids, and decay incidence. Statistical methods included repeated-measures ANOVA, one-way ANOVA, Kruskal–Wallis tests when needed, Dunn’s post hoc tests, and Pearson correlation analysis.

Key Research Findings

The passive cooling blanket consistently reduced temperature and increased relative humidity across Kenya, Uganda, and Nigeria.

In Kenya, the passive cooling blanket reduced produce temperature by an average of about 5 °C, with peak reductions up to 10 °C compared with ambient shaded storage. Relative humidity inside the blanket remained around 95%, about 26% higher than ambient conditions. Cooling efficiency reached up to 70% under the site’s dry-season conditions.

In Uganda, the trials were conducted during the wet season, when high ambient humidity reduced evaporative cooling potential. Even so, the charcoal-filled blanket lowered fruit temperature by an average of about 2 °C, with short-term peak reductions up to 20 °C after wetting events during midday heat. The blanket maintained average relative humidity of about 88%, around 14% higher than ambient conditions. Cooling efficiency ranged from 68% to 87%.

In Nigeria, the larger blanket reduced average air temperature by about 5 °C, with occasional peak reductions of about 20 °C. It maintained average relative humidity around 85%, about 25% higher than ambient conditions. Cooling efficiency reached up to 80% during the dry-to-wet transition season.

The quality benefits varied by country and crop. In Kenya, the blanket reduced overall postharvest quality losses by up to 45% compared with natural shade. Weight loss was reduced by as much as 60%, firmness loss by about 35%, and color change by up to 6%, depending on crop type. Leafy vegetables such as kale showed strong benefits, maintaining marketable quality for two additional days.

In Uganda, the blanket slowed tomato ripening and improved marketability. Green and breaker tomatoes stored under the blanket lost 5%–10% less weight and retained 15%–20% more firmness than tomatoes stored under natural shade. Transport simulation showed that vendors using the blanket lost only about two tomatoes per crate, compared with about 25 tomatoes per crate under ambient storage.

In Nigeria, the blanket reduced tomato fresh weight loss by about 32% and postharvest rot by about 20% compared with shaded ambient storage. Firmness loss was reduced from 17% to 12%, and tomatoes stored in the blanket retained higher total soluble solids values than ambient-stored fruit.

Across all three countries, the study estimated that passive cooling blankets reduced postharvest losses by approximately 30%.

What This Means for Postharvest Cooling in Sub-Saharan Africa

This study shows that passive cooling blankets can provide a practical cold-chain alternative for smallholder farmers and vendors who lack access to refrigeration.

For postharvest handling, the key value is the combination of lower temperature and higher relative humidity. Lower temperature slows respiration, ripening, and microbial spoilage. Higher relative humidity reduces water loss, helping produce retain firmness, weight, and visual freshness.

For smallholder farming systems, the technology is attractive because it does not require electricity. The blanket can be made from locally available materials such as jute, burlap, sisal, charcoal, sawdust, or other porous fillers. It is portable, scalable, and easier to deploy than permanent charcoal cooling rooms.

For local food markets, even a few extra days of shelf life can reduce waste and improve income. The Uganda vendor example showed that reduced tomato spoilage can directly lower economic losses at the crate level.

For research and deployment, the findings also show that local climate matters. The strongest cooling effects occurred in Kenya and Nigeria, where lower ambient humidity increased evaporative potential. Uganda’s wet-season results were more conservative but still useful, showing that the blanket can provide benefits even under humid conditions.

Application Value of UbiBot Devices

UbiBot WS1 Pro demonstrated value as part of the environmental monitoring workflow for passive evaporative cooling research.

First, it contributed temperature and relative humidity data under field conditions. These measurements are essential for understanding how the blanket performs in real climates rather than only in laboratory settings.

Second, UbiBot data helped quantify the environmental context of each trial. Because evaporative cooling depends on ambient temperature and humidity, field monitoring allowed the researchers to compare cooling performance across countries and seasons.

Third, the environmental data supported cooling efficiency analysis. Dry-bulb and wet-bulb temperature relationships were used to evaluate how closely the passive cooling blanket approached its theoretical evaporative cooling potential.

Fourth, UbiBot-supported monitoring helped link storage microclimate with produce quality. Weight loss, firmness, color, and decay outcomes could be interpreted in relation to recorded temperature and humidity conditions.

Fifth, the use of compact IoT-style environmental sensors supports future digital integration. The paper’s future research section explicitly highlights sensor integration and digital models as an important direction for turning hygrothermal data into real-time quality indicators such as mass loss and remaining shelf life.

Overall, UbiBot’s value in this study was not direct produce preservation. Its value was providing field environmental data that helped researchers evaluate, compare, and explain passive cooling blanket performance across different Sub-Saharan climates.

Extended Application Scenarios

The monitoring approach used in this study can be extended to several related scenarios:

1. Passive cooling blanket deployment
   Used to monitor temperature and relative humidity during on-farm and market storage.
2. Smallholder postharvest storage
   Used to support low-cost cold-chain alternatives for farmers without refrigeration.
3. Fresh produce market monitoring
   Used to track storage conditions in open markets and roadside vendor stalls.
4. Evaporative cooling performance testing
   Used to compare charcoal, sawdust, rice husk, sisal, coconut fiber, or other filler materials.
5. Farm-to-market transport monitoring
   Used to record environmental conditions during motorcycle, cart, truck, or local market transport.
6. Quality-loss modeling
   Used to connect temperature and humidity data with predicted mass loss, firmness loss, and remaining shelf life.
7. Digital twin development
   Used as a sensor layer for real-time passive cooler models and actionable produce-quality analytics.
8. Multi-country food loss studies
   Used to compare cooling performance across climate zones, seasons, and produce types.

FAQ

1. Which UbiBot product was used in the study?

The paper lists UbiBot WS1 Pro among the instruments used for ambient temperature and relative humidity monitoring in the Kenya and Uganda trials.

2. What data did UbiBot collect?

UbiBot WS1 Pro contributed temperature and relative humidity data used to document environmental conditions around passive cooling blanket trials.

3. Where was UbiBot deployed?

The paper lists UbiBot WS1 Pro in the measurement setup for Kenya and Uganda. The broader study monitored passive cooling blanket trials in Kenya, Uganda, and Nigeria.

4. What was the sampling frequency?

The paper states that environmental parameters were continuously monitored, but it does not explicitly specify the raw UbiBot logging interval.

5. How were the UbiBot data used?

The environmental data helped evaluate cooling performance, compare ambient and blanket storage conditions, and interpret produce quality changes such as weight loss, firmness loss, color change, and decay.

6. Did UbiBot measure produce quality directly?

No. Produce quality was measured separately through weight loss, firmness, color, pH, total soluble solids, and decay incidence. UbiBot measured environmental conditions.

7. Did UbiBot prove that passive cooling blankets reduce losses?

No. UbiBot collected environmental data. The researchers combined these data with produce quality measurements and statistical analysis to evaluate passive cooling blanket performance.

8. What countries were included in the study?

The study evaluated passive cooling blankets in Kenya, Uganda, and Nigeria.

9. What was the main result?

Across the three countries, passive cooling blankets reduced storage temperature, increased relative humidity, and reduced postharvest losses by approximately 30%, with site-specific benefits depending on climate and crop type.

10. Why is this research important?

It shows that low-cost, electricity-free evaporative cooling can help preserve fresh produce in resource-limited supply chains, while temperature and humidity monitoring helps quantify and optimize real field performance.