Agroecology-based soil erosion assessment for better conservation planning in Ethiopian river basins

Comparative analysis of RUSLE and SWPT for sub-watershed conservation prioritization in the Ayu watershed, Abay basin, Ethiopia

Ethiopia is currently facing a major environmental problem caused by soil erosion. In order to tackle this problem, it is essential to implement a comprehensive watershed management approach and give priority to conservation efforts depending on the level of severity. Therefore, the objective of this research is to evaluate the mean annual soil erosion and rank the sub-watersheds for conservations in the Ayu watershed, utilizing the Revised Universal Soil Loss Equation (RUSLE) model and the Sub-Watershed Prioritization Tool (SWPT). RUSLE was utilized to predict the annual average soil erosion rate, while SWPT was applied to conduct Weighted Sum Analysis (WSA) for ranking sub-watersheds. Support Vector Machine (SVM) was employed for classifying land use and land cover. The Relative importance of morphometric and topo-hydrologic features in the SWPT was analyzed using a Random Forest model. The Bland-Altman plot and Wilcoxon Signed Rank Test were employed to assess the agreement in prioritizing watersheds between RUSLE results and the SWPT. Furthermore, field observations were conducted to validate the land use classification by collecting ground data. In addition, the study was enhanced with local viewpoints by conducting focus group discussions with agricultural experts and farmers to obtain qualitative insights and validation of resuts. The findings showed that soil loss varied from 0 to 110 t/ha/yr, with an average of 8.95 t/ha/yr, resulting in a total loss of 384365.3 tons annually. The comparison of RUSLE and SWPT showed a moderate positive relationship (r = 0.59). The results of the Bland-Altman plot indicate a consistent agreement between the two methods. However, there is inconsistency among the five sub watersheds. This study enhances the knowledge of soil erosion patterns and offers useful guidance for watershed conservation techniques. It can be also used as a beneficial framework for managing watersheds, with possible uses outside of the Ayu watershed.

Soil erosion assessment and identification of erosion hotspot areas in the upper Tekeze Basin, Northern Ethiopia

Soil erosion is a major environmental problem in Ethiopia, reducing topsoil and agricultural land productivity. Soil loss estimation is a critical component of sustainable land management practices because it provides important information about soil erosion hotspot areas and prioritizes areas that require immediate management interventions. This study integrates the Revised Universal Soil Loss Equation (RUSLE) with Google Earth Engine (GEE) to estimate soil erosion rates and map soil erosion in the Upper Tekeze Basin, Northern Ethiopia. SoilGrids250 m, CHIRPS-V2, SRTM-V3, MERIT Hydrograph, NDVI from sentinel collections and land use land cover (LULC) data were accessed and processed in the GEE Platform. LULC was classified using Random forest (RF) classification algorithm in the GEE platform. Landsat surface reflectance images from Landsat 8 Operational land imager (OLI) sensors (2021) was used for LULC classification. Besides, different auxiliary data were utilized to improve the classification accuracy. Using the RUSLE-GEE framework, we analyzed the soil loss rate in different agroecologies and LULC types in the upper Tekeze basin in Waghimra zone. The results showed that the average soil loss rate in the Upper Tekeze basin is 25.5 t ha-1 yr-1. About 63 % of the basin is experiencing soil erosion above the maximum tolerable rate, which should be targeted for land management interventions. Specifically, 55 % of the study area, which is covered by unprotected shrubland is experiencing mean annual soil loss of 34.75 t ha-1 yr-1 indicating the need for immediate soil conservation intervention. The study also revealed evidence that this high mean soil loss rate of the basin can be reduced to a tolerable rate by implementing integrative watershed management and exclosures. Furthermore, this study demonstrated that GEE could be a good source of datasets and a computing platform for RUSLE, in particular for data scarce semi-arid and arid environments. The results from this study are reliable for decision-making for rapid soil erosion assessment and intervention prioritization.

Quantification of soil erosion and sediment yield using the RUSLE model in Boyo watershed, central Rift Valley Basin of Ethiopia

Changes in land use and land cover (LULC) are becoming recognized as critical to sustainability research, particularly in the context of changing landscapes. Soil erosion is one of the most important environmental challenges today, particularly in developing countries like Ethiopia. The objective of this study was evaluating the dynamics of soil loss, quantifying sediment yield, and detecting soil erosion hotspot fields in the Boyo watershed. To quantify the soil erosion risks, the Revised Universal Soil Loss Equation (RUSLE) model was used combined with remote sensing (RS) and geographic information system (GIS) technology, with land use/land cover, rainfall, soil, and management approaches as input variables. The sediment yield was estimated using the sediment delivery ratio (SDR) method. In contrast to a loss in forest land (1.7 %), water bodies (3.0 %), wetlands (1.5 %), and grassland (1.7 %), the analysis of LULC change (1991-2020) showed a yearly increase in the area of cultivated land (1.4 %), built-up land (0.8 %), and bare land (3.5 %). In 1991, 2000, and 2020, respectively, the watershed's mean annual soil loss increases by 15.5, 35.9, and 38.3 t/ha/y. Approximately 36 cm of the watershed's economically productive topsoil was lost throughout the study's twenty-nine-year period (1991-2020). According to the degree of erosion, 16 % of the watershed was deemed seriously damaged, while 70 % was deemed slightly degraded. Additionally, it is estimated for the year 2020 that 74,147.25 t/y of sediment (8.52 % of the total annual soil loss of 870,763.12 t) reach the Boyo watershed outlet. SW4 and SW5 were the two sub-watersheds with the highest erosion rates, requiring immediate conservation intervention to restore the ecology of the Boyo watershed.

An integrated modeling approach for estimating monthly global rainfall erosivity

Modeling monthly rainfall erosivity is vital to the optimization of measures to control soil erosion. Rain gauge data combined with satellite observations can aid in enhancing rainfall erosivity estimations. Here, we presented a framework which utilized Geographically Weighted Regression approach to model global monthly rainfall erosivity. The framework integrates long-term (2001-2020) mean annual rainfall erosivity estimates from IMERG (Global Precipitation Measurement (GPM) mission's Integrated Multi-satellitE Retrievals for GPM) with station data from GloREDa (Global Rainfall Erosivity Database, n = 3,286 stations). The merged mean annual rainfall erosivity was disaggregated into mean monthly values based on monthly rainfall erosivity fractions derived from the original IMERG data. Global mean monthly rainfall erosivity was distinctly seasonal; erosivity peaked at ~ 200 MJ mm ha-1 h-1 month-1 in June-August over the Northern Hemisphere and ~ 700 MJ mm ha-1 h-1 month-1 in December-February over the Southern Hemisphere, contributing to over 60% of the annual rainfall erosivity over large areas in each hemisphere. Rainfall erosivity was ~ 4 times higher during the most erosive months than the least erosive months (December-February and June-August in the Northern and Southern Hemisphere, respectively). The latitudinal distributions of monthly and seasonal rainfall erosivity were highly heterogeneous, with the tropics showing the greatest erosivity. The intra-annual variability of monthly rainfall erosivity was particularly high within 10-30° latitude in both hemispheres. The monthly rainfall erosivity maps can be used for improving spatiotemporal modeling of soil erosion and planning of soil conservation measures.

Evaluating the effects of DEM and soil data resolution on streamflow and sediment yield simulations in the Upper Blue Nile basin

While the availability of "big data" on biophysical parameters through citizen science and/or from public/private sources is expected to help in addressing data scarcity issues, there is little understanding of whether and/or how such data will improve watershed simulations. This research aimed to evaluate whether improvements in resolutions of Digital Elevation Model (DEM) and soil data will enhance streamflow and sediment yield simulations and thereby improve soil and water management decisions. The study was conducted in two different-sized watersheds (Anjeni and Gilgel Abay with ~ 1 km2 and ~ 1655 km2 area, respectively) in the Upper Blue Nile basin in Ethiopia. Effects of DEM and soil data resolutions on streamflow and sediment yield were evaluated using the Soil and Water Assessment Tool (SWAT). The results showed that the effect of DEM and soil data resolution on streamflow and sediment yield simulation was scale dependent finer resolution DEM and soil datasets improved streamflow and sediment yield simulations in the smaller Anjeni watershed, whereas DEM resolution had no effect in the bigger Gilgel Abay watershed. Small watersheds are often used to understand watershed processes, and thus the use of finer-resolution spatial data for watershed simulations could result in better results. Findings from the smaller Anjeni watershed suggested that the combined use of finer resolution DEM and soil data could potentially improve sediment yield simulations although the lack of observed sediment yield data did not allow verification of this at the larger Gilgel Abay watershed.

An integrated framework for improving watershed management planning

Proper land use and management (LUM) planning is pivotal to curbing land degradation and ensuring sustainable use of limited watershed resources. Despite decades of research and development efforts, land degradation remains a serious environmental problem in many parts of the world. Issues regarding the sustainability of current LUM initiatives are due to poor linkages between the ecological and socio-economic dimensions of LUM decisions, and an integrated framework allowing LUM interventions to be properly planned and implemented is lacking. In this study, we developed an integrated framework to identify, evaluate, and propose LUM alternatives with ecological and socio-economic benefits. The framework comprises six components: (i) identification of land use problems and setting of objectives, (ii) identification of the best-performing land use-based integrated solutions, (iii) formulation of LUM alternatives and modeling of key indicators, (iv) cost-benefit analysis, (v) evaluation of the LUM alternatives with stakeholders engagement, and (vi) communication of the LUM alternatives to relevant stakeholders to obtain institutional and financial support for implementation. To demonstrate the use of this framework, we conducted a case study in the Aba Gerima watershed of the Upper Blue Nile basin in Ethiopia. This study used extensive plot- and watershed-scale observations (2015-2019) obtained under both conventional and improved sustainable land management practices. We analyzed changes in runoff, soil loss, soil organic carbon (SOC) stock, and land productivity of five LUM alternatives as compared to a baseline scenario (existing farming practices). The results showed that the LUM alternatives reduced runoff by 11-71% and soil loss by 66-95%, and SOC stock and watershed-scale land productivity were improved by 36-104% and 48-134%, respectively. Evaluation of LUM alternatives by stakeholders, including land users, policy makers, and researchers, produced divergent results. In particular, land users prioritized implementation of sustainable land management practices without altering existing land uses. The integrated framework developed in this study can serve as a valuable tool for identifying, evaluating, and proposing LUM alternatives and facilitating decision-making in planning and implementation of LUM practices in watersheds experiencing land degradation.

Improving estimation of water soil erosion by introducing lithological formation for environmental remediation

Soil erosion is a serious and complex environmental problem worldwide, especially in the centre west of Tunisia. Whereas the construction of hill reservoirs is part of the soil and water conservation strategy, many of these have a siltation problem. Dhkekira is one of the smallest watersheds in central Tunisia whose most lithological formation consists of materials that are quite susceptible to water erosion. Due to the lack of low-scale lithological data, digital IR aerial photos with 2 m spatial resolution were considered. A semi-automatic classification of aerial photos, based on the image's textural indices is developed. The lithologic map extracted from aerial photos was used as input for ANSWERS-2000 water erosion model. Results obtained indicate first, with the semi-automatic classification of the mean and standard deviation of the thumbnail histograms that image output could help to give an idea about the existence of some surface lithological formation. The model applied to Dhkekira watershed showed that the spatial difference in water erosion was not caused only by land cover and slope, but also by lithological formation. The percentage of each lithological formation in sediment yield at the Dhkekira hill reservoir was estimated to be 69% sediment yield from Pleistocene and 19.7% from Lutetian-Priabonian.

Predicting runoff and sediment responses to climate-resilient land use and management scenarios

Soil erosion is the predominant agent affecting ecosystem services in the Ethiopian highlands. However, land management interventions aimed at controlling erosion in the region are hampered, mainly by a lack of watershed-based appropriate management practices and anticipated climate changes. This study examined the effectiveness of different land use changes and management scenarios in decreasing runoff and sediment loss under current and future climates in the drought-prone humid watershed of the Ethiopian highlands. We employed a modeling approach integrating observed data at watershed and plot scales with Soil and Water Assessment Tool. In the first step, we evaluated the impact of land use changes between 2006 and 2017 on runoff and sediment loss. Then, we developed five land use and management scenarios based on watershed land capabilities and selected land management practices. Model parameters were modified based on runoff and sediment loss results obtained from experimental plots of biophysical and agronomical land management practices in the watershed. The runoff and sediment loss were simulated under current (2014-2019) and future climates (the 2050s) for each land use and management scenario. Results revealed that land use changes (mainly an increase in Acacia decurrens plantations by 206%) alone between 2006 and 2017 reduced runoff by 31% and sediment loss by 45%. Under the current climate, the five land use and management scenarios reduced runoff by 71-95% and sediment loss by 75-96% compared to the baseline scenario. Under the future climate (2050s), these scenarios decreased runoff by 48-90% and sediment loss by 54-91%. However, their effectiveness was slightly decreased (5-23%) as a result of increases in rainfall (10-46%) and mean temperature (1.7-1.9 °C) in the 2050s. The scenario of improving vegetation cover through forage production and plantations in appropriate areas plus best land management practices was the most effective and climate-resilient of the five scenarios. This study suggests that evaluating the impact of land use and management practices under future climate change shows promise for guiding effective and sustainable interventions to adapt to climate change.

Spatial and temporal patterns of supply and demand risk for ecosystem services in the Weihe River Main Stream, NW China

The rapid development of society and economy in the post-industrial era has exacerbated the spatial matching contradiction between the demand of humans and the supply of the natural environment, while ecosystem service (ES) as a bridge linking nature and society, identifying and assessing its supply-demand risk, was beneficial to ecosystem management and promoted regional high-quality development. Based on the data of multi-source remote sensing and statistics, the supply and demand levels of four ESs, which contain food supply, carbon storage, soil conservation, and water yield in the main stem of the Weihe River in 2000, 2010, and 2020, were quantitatively measured. The spatial and temporal analysis of the supply, demand, and supply-demand ratio of each service was carried out using spatial mapping. The spatio-temporal pattern of the supply-demand risk was recognized by the method of spatial overlay, which means overlaying the supply and demand for material quality, ratio, trend, and the degree of trade-off coordination together between each service. The results showed that (1) the demand for water yield decreased slightly while the demand for food and the supply of carbon storage remained stable. In addition, the supply and demand of other services showed an upward trend. (2) The spatial distribution of the supply-demand ratio of each service shows "high in the south and low in the north" and "high in the east and low in the west," among which the supply-demand ratio of carbon storage is decreasing. (3) The overall supply-demand risk of soil conservation in the study area is low with characteristics of small range and high degree, the risk distribution characteristics of the other services are high in the east and low in the west, and the risk is high in the city center and low around. Otherwise, the supply-demand risk of food supply showed a downward trend, the risk of carbon storage showed an upward trend, the risk of soil conservation remained stable, and the risk of water yield showed a significant downward trend. Based on static supply-demand risk identification, this study assesses supply-demand risk over two periods and analyzes the trend of supply-demand risk changes over time. It clarifies the extent and direction of supply-demand risk shifts, as well as provides improved theoretical support for ecosystem service management.

Land use, management and climate effects on runoff and soil loss responses in the highlands of Ethiopia

Soil erosion by water is a major cause of land degradation in the highlands of Ethiopia and anywhere else in the world, but its magnitude and variability are rarely documented across land uses and climatological conditions. The purpose of this study was to examine runoff and soil loss responses under cropland (CL) and grazing land (GL) management practices in three climatic regions of the Ethiopian highlands: semi-arid (Mayleba), dry sub-humid (Gumara), and humid (Guder). We measured runoff and soil loss using runoff plots with and without soil and water conservation (SWC) measures (trenches, stone/soil bunds [embankments] with trenches on the upslope side, and exclosure) during the rainy season (July-September). The results revealed significant variation in runoff and soil loss amounts across land uses, SWC measures, and climatic regions. At Mayleba, seasonal runoff and soil loss in control plot were far higher from GL (280 mm, 26.5 t ha^-1) than from CL (108 mm, 7.0 t ha^-1) largely due to lack of protective vegetation cover and soil disruption because of intense grazing. In contrast, at Gumara and Guder, seasonal soil loss values were much higher from CL (21.4-71.2 t ha^-1) than from GL (0.6-24.2 t ha^-1) irrespective of runoff values. This was attributed to the excessive tillage/weeding operations involved in cultivation of teff (cereal crop) at Gumara and potato at Guder. Although SWC measures (practices) substantially reduced runoff and soil loss (decreased by 23%-86%) relative to control plot, seasonal soil loss under GL uses with trenches at Mayleba (12.6 t ha^-1), CL with soil bunds and trenches at Gumara (22.1 t ha^-1), and Guder (21.4 t ha^-1) remained higher than the average tolerable soil loss rate (10 t ha^-1 year^-1) proposed for the Ethiopian highlands. This suggests that SWC measures should be carefully designed and evaluated specific to land use and climatic conditions. Overall, the results of this study can help improve SWC planning in regions where land use and climate impact on soil erosion vary across geographical areas, as they do in Ethiopia and anywhere else. However, further investigation is crucial with replication of measurements over years and locations to provide more accurate information on land use, management and climate controls on hydrological and soil erosion processes.

Farmers' adoption of soil and water conservation practices: The case of Lege-Lafto Watershed, Dessie Zuria District, South Wollo, Ethiopia

In Ethiopia, soil degradation is one of the major causes of low and declining agricultural productivity. As a result of this challenge, the country has been battling to adopt conservation practices. The main objective of this study was to assess farmers' adoption decisions of soil and water conservation (SWC) practices. For the survey, 304 farmers were selected from farming communities in Lege-Lafto Watershed, South Wollo,Ethiopia. Information were gathered using a household survey, and through focus group discussions, key informant interviews, and field observation. A binary logistic regression model and descriptive statistics were used to analyze the data. The results indicated that about 64% of the farmers adopted soil and water conservation practices in the study area. The findings depicted that soil bund, stone bund, stone-faced soil bund, loose stone and brush-wood check dams, hillside terrace, and bund stabilized with vegetation are practiced in the watershed. The analysis result revealed adoption of soil and water conservation practices is significantly and positively influenced by the perception of farmers on erosion problems and SWC practices, family labour, educational level, and membership in local institutions. However, distance from residence to the nearest market and farmland, off-farm activities, and the ratio of cultivable land to family size influenced the adoption of SWC practices negatively. Therefore, improving farmers' educational status, and strengthening local institutions are vital for sustainable land management practices in the country.

Assessment of environmentally sensitive areas to desertification in the Blue Nile Basin driven by the MEDALUS-GEE framework

Assessing environmentally sensitive areas (ESA) to desertification and understanding their primary drivers are necessary for applying targeted management practices to combat land degradation at the basin scale. We have developed the MEditerranean Desertification And Land Use framework in the Google Earth Engine cloud platform (MEDALUS-GEE) to map and assess the ESA index at 300 m grids in the Blue Nile Basin (BNB). The ESA index was derived from elaborating 19 key indicators representing soil, climate, vegetation, and management through the geometric mean of their sensitivity scores. The results showed that 43.4%, 28.8%, and 70.4% of the entire BNB, Upper BNB, and Lower BNB, respectively, are highly susceptible to desertification, indicating appropriate land and water management measures should be urgently implemented. Our findings also showed that the main land degradation drivers are moderate to intensive cultivation across the BNB, high slope gradient and water erosion in the Upper BNB, and low soil organic matter and vegetation cover in the Lower BNB. The study presented an integrated monitoring and assessment framework for understanding desertification processes to help achieve land-related sustainable development goals.

Assessment of soil erosion extent using RUSLE model integrated with GIS and RS: the case of Megech-Dirma watershed, Northwest Ethiopia

Soil erosion valuation at a spatial scale is crucial for assessing natural resource quality in a farming country like Ethiopia. The study's goal was to determine the rate of soil erosion in the Megech-Dirma catchment in Northwest Ethiopia using the Revised Universal Soil Loss Equation model aggregation with Geographic Information System and Remote Sensing. Sediment yield and transport were also estimated using sediment delivery ratio. Revised Universal Soil Loss Equation model data inputs included precipitation data for the R value, soil data for the K value, land cover data from satellite images for the C and P value, and topographical data from a Digital Elevation Model for the LS component. It was completed using the ArcGIS 10.4 software. The mean annual soil loss is 110.60 t ha^-1 yr^-1. Each year, a total of 8499.74 t ha^-1 yr^-1 of soil eroded and on average resulting in 1605.30 t/km²/yr, sediment material has been transported to the stream channels and deposited with a sediment delivery ratio of 1.87. The strength of soil erosion in the area is divided into six categories. The erosion rate classes were 46.38 percent (0-12 t ha^-1 yr^-1) low, 13.63 percent (12-20 ha^-1 yr^-1) moderate, 9.22 percent (20-35 ha^-1 yr^-1) high, 12.30 percent (35-50 ha^-1 yr^-1) very high, 7.20 percent (50 up to 100 ha^-1 yr^-1) severe, and 11.27 percent (>100 ha^-1 yr^-1) very severe erosion. According to erosion severity, 46.38 percent of the watershed is at risk of low erosion, while 11.27 percent is at risk of extremely severe erosion. The north and northeastern sections of the watershed have a moderate to extremely severe erosion risk due to steep slopes, high rainfall, and weak conservation measures. The severely eroded parts of the plateau and steep portions are proposed to be covered by plantation, stone bund, and check dam constructions.

Spatial modeling of soil erosion hazards and crop diversity change with rainfall variation in the Central Highlands of Sri Lanka

The spatial variation of soil erosion is essential for farming system management and resilience development, specifically in the high climate hazard vulnerable tropical countries like Sri Lanka. This study aimed to investigate climate and human-induced soil erosion through spatial modeling. Remote sensing was used for spatial modeling to detect soil erosion, crop diversity, and rainfall variation. The study employed a time-series analysis of several variables such as rainfall, land-use land-cover (LULC) and crop diversity to detect the spatial variability of soil erosion in farming systems. Rain-use efficiency (RUE) and residual trend analysis (RESTREND) combined with a regression approach were applied to partition the soil erosion due to human and climate-induced land degradation. Results showed that soil erosion has increased from 9.08 Mg/ha/yr to 11.08 Mg/ha/yr from 2000 to 2019 in the Central Highlands of Sri Lanka. The average annual rainfall has increased in the western part of the Central Highlands, and soil erosion hazards such as landslides incidence also increased during this period. However, crop diversity has been decreasing in farming systems, namely wet zone low country (WL1a) and wet zone mid-country (WM1a), in the western part of the Central Highlands. The RUE and RESTREND analyses reveal climate-induced soil erosion is responsible for land degradation in these farming systems and is a threat to sustainable food production in the farming systems of the Central Highlands.

Soil erosion assessment in the Blue Nile Basin driven by a novel RUSLE-GEE framework

Assessment of soil loss and understanding its major drivers are essential to implement targeted management interventions. We have proposed and developed a Revised Universal Soil Loss Equation framework fully implemented in the Google Earth Engine cloud platform (RUSLE-GEE) for high spatial resolution (90 m) soil erosion assessment. Using RUSLE-GEE, we analyzed the soil loss rate for different erosion levels, land cover types, and slopes in the Blue Nile Basin. The results showed that the mean soil loss rate is 39.73, 57.98, and 6.40 t ha^-1 yr^-1 for the entire Blue Nile, Upper Blue Nile, and Lower Blue Nile Basins, respectively. Our results also indicated that soil protection measures should be implemented in approximately 27% of the Blue Nile Basin, as these areas face a moderate to high risk of erosion (>10 t ha^-1 yr^-1). In addition, downscaling the Tropical Rainfall Measuring Mission (TRMM) precipitation data from 25 km to 1 km spatial resolution significantly impacts rainfall erosivity and soil loss rate. In terms of soil erosion assessment, the study showed the rapid characterization of soil loss rates that could be used to prioritize erosion mitigation plans to support sustainable land resources and tackle land degradation in the Blue Nile Basin.

Nutritional, physicochemical and sensorial acceptance of functional cookies enriched with xiquexique (Pilosocereus gounellei) flour

The objective of this study was the production of innovative functional cookies enriched with two different sizes (100 and 28 mesh) xiquexique flour by substitution ratio 50% of wheat flour and monitoring the impact of these enrichments on the nutritional, physicochemical, texture characteristics and consumer acceptance. The physicochemical characteristics and sensorial properties of the xiquexique cookies were evaluated in a pursuit to identify an innovative bakery ingredient with high nutritional value and potential function that could be exploited by the food industry. The water activity and moisture values were low, which can provide greater stability during storage of food matrices, such as cookies. The xiquexique cookies had greater ash (2.47-2.74%), protein (0.94-1.36%), fiber (4.41-8.10%), and resistant starch (3.65-2.10%) contents than their respective controls with 100% wheat flour. The functional cookies were rich in minerals: mainly calcium, iron, potassium, magnesium and manganese and can be consumed by all individuals to help meet daily needs, especially those of people who have increased needs for these essential nutrients. In addition to the darker color of the xiquexique cookies, the hardness of these was higher than that of the control cookies, while the expansion index was smaller. The data from the Check All That Apply sensory method, which consists of a test used mainly for recipe adjustments and the development of ideal food products, confirmed that xiquexique flour have the potential for the development of bakery products such as cookies.