CIRAD Dataverse
Not a member yet
921 research outputs found
Sort by
Corpus and list of agroecological experimental variables
No full textThis dataset includes a list of experimental variables from sugarcane agroecological systems, described by researchers (source variables), a list of candidate experimental variables (AEGIS) and a corpus generated by GPT Turbo on variable descriptions
Data for the calibration of STICS and yield gap analysis for maize, groundnut cowpea and pigeon pea in Murehwa district, sub-humid Zimbabwe published in "Identifying the drivers of yield gaps for maize and legumes in Zimbabwean smallholder farms using locally calibrated crop modelling"
No full textThe dataset contains data on the growth of maize, groundnut, cowpea and pigeon pea collected during two growing seasons in on-farm trials in the Murehwa district, sub-humid Zimbabwe. The observed climate data for the experimental seasons is provided, along with basic soil characteristics. Crop management (planting date, date of field operations) is also described, as well as initial conditions prior to planting. Eventually, observations of in-season leaf area index (when available), soil water (when available), biological nitrogen fixation (when available), crop nitrogen content (when available), aboveground biomass and grain yield at harvest (and biomass at flowering when available) are provided. Scores of weed infestation, pest and disease occurrence, waterlogging occurrence and phosphorus deficiency occurrence are included.
There is one simulation unit for each combination of crop, soil and climate, identified by an unique key (see usms file
Database of tropical weeds functional traits based on the species list of the Wiktrop portal and built using an automatic extraction with a conversational large language model from online botanical desctriptions of species
No full textThis database have been compiled based on the weed species list available on the Wiktrop online portal (https://wiktrop.org/fr, gathering 1049 species when the database was created). For each species, we used a conversational Large Language Model (LLM) to automatically extract functional traits values from different online sources (https://wiktrop.org/fr, https://www.worldfloraonline.org/, https://www.feedipedia.org/, https://tropical.theferns.info/, https://www.wikipedia.org/). The collected data has been cured and filtered to remove traits with a fuzzy definition and non realistic trait values while keeping only traits jugged as ecologically relevant (however, as the extraction method is based on an automatic process involving a LLM, and as the entire list of trait values are not human-verified, the dataset may partially contain spurious or erroneous values). For detailed methods, please refer to the related document (https://agritrop.cirad.fr/614130/)
Raw data on the fitness of Tuta absoluta and Nesidiocoris tenuis and predation at different temperatures and associated R code for model-based exploration of predator-prey dynamics
No full textThis dataset provides the results of several laboratory experiments in climatic chambers to assess longevity, mortality and fecundity of Tuta absoluta and Nesidiocoris tenuis from Senegalese populations under different temperature regimes. The R code provides the discrete-time stochastic individual-based model used to study predator-prey dynamics under different temperature regimes. Data and R code are presented in the article Predicting biological control performance under global change using model-based exploration of predator-prey dynamics
Body Condition Scoring Grid for Barbe Horse (Senegal)
No full textIn tropical countries, and especially in Sub-Saharan Africa (Sahel and Savannah areas), subject to significant quantitative and qualitative variations in the availability of fodder during the year, the dissatisfaction of feed needs is a frequent situation for animals reared in grazing systems without a sufficient supplementation with feed concentrates.
The Body Condition Scoring (BCS) is a useful way to assess the state of body reserves (subcutaneous fat, muscle mass) which reflects the animal's production (growth, milk, work) and reproduction capacities. The evaluation of the body reserves of an animal through the scoring of their body condition is important to adjust their diet and appreciate their general state of health, as well as their reproductive and production capacity (meat, milk, work, etc.). Managing body reserves is one way of responding to variability in quality and access to feed resources. In females, reserves play an important buffer role during lactation. They can make up for insufficient intakes from the ration. Indeed, the level of production depends on the nutrients provided by the feeds, but also on the animal's body reserves when the feed-based supplies do not fully cover their needs, especially during the dry season. The BCS impacts the interval between two foaling. Overly lean females show a delay in the return of heat after foaling, the direct consequence of which is the increase in the parturition interval and consequently a decrease in herd productivity.
The assessment of these reserves through Body Condition Scoring (BCS) represents a management tool for livestock farmers, agricultural advisors, and livestock development stakeholders. BCS is a simple, inexpensive and fast method. Several animals can be scored in one session. It allows to compare the BCS of individuals or herds: 1) raised in different production systems or environments, 2) or, during different seasons (dry season and rainy season). BCS can be used as a tool for monitoring and alerting the nutritional level of domestic animal populations. To do this, BCS alert thresholds and a BCS collection and monitoring system must be defined on reasoned samples of animal populations.
It is an easy-to-use field tool. However, a good mastery of the BCS grid as well as a regular practice of scoring are necessary to obtain precise and reproducible ratings. It can also be used as a tool for monitoring and alerting the nutritional level of animal populations. Thus, the farmer can be called at any time to intervene on the feed ration and / or the health of the animal.
In a study on the well-being of equines in Senegal, Diaw (2013) presents a BCS grid for horses comprising five levels of scoring. To harmonize the Barbe horse BCS grid with other species, we propose six levels scoring grid accepting the hypothesis that cachectic animals could be present in equine populations which are not considered in the study of Diaw (2013). The proposed grid is partly inspired by the BCS grid for sport horses by Carroll & Huntington (1988) including an BCS scale from 0 to 5.
In 2020, Vall proposed a standardized BCS scoring system for tropical livestock animals for large animals (cattle, camels), small animals (sheep, and goats) and for donkeys, and horses. This document presents this BCS system applied to the Barbe horses living in Sahel and Savannah areas. We propose a BCS grid with six levels admitting the hypothesis that in the horse populations extreme animals could be present, being very thin (nutritional state worsened by parasitism), or very fatty
Phenology of Hyalomma marginatum in southern France (2016-2022)
No full textData collected during the study carried out between 2016 and 2022 to identify the phenology of the tick Hyalomma marginatum in southern France. The studies were implemented in a land located at the border of Gard and Hérault departments, Occitanie, France
Body Condition Scoring Grid for Yellow Cattle (Vietnam)
No full textIn tropical countries subject to significant quantitative and qualitative variations in the availability of fodder during the year, the dissatisfaction of feed needs is a frequent situation for animals reared in grazing systems without a sufficient supplementation with feed concentrates.
The Body Condition Scoring (BCS) is a useful way to assess the state of body reserves (subcutaneous fat, muscle mass) which reflects the animal's production (growth, milk, work) and reproduction capacities. The evaluation of the body reserves of an animal through the scoring of their body condition is important to adjust their diet and appreciate their general state of health, as well as their reproductive and production capacity (meat, milk, work, etc.). Managing body reserves is one way of responding to variability in quality and access to feed resources. In females, reserves play an important buffer role during lactation. They can make up for insufficient intakes from the ration. Indeed, the level of production depends on the nutrients provided by the feeds, but also on the animal's body reserves when the feed-based supplies do not fully cover their needs, especially during the dry season. The BCS impacts the interval between two calving. Overly lean cows show a delay in the return of heat after calving, the direct consequence of which is the increase in the parturition interval and consequently a decrease in herd productivity.
The assessment of these reserves through Body Condition Scoring (BCS) represents a management tool for livestock farmers, agricultural advisors, and livestock development stakeholders. BCS is a simple, inexpensive and fast method. Several animals can be scored in one session. It allows to compare the BCS of individuals or herds: 1) raised in different production systems or environments, 2) or, during different seasons (dry season and rainy season). BCS can be used as a tool for monitoring and alerting the nutritional level of domestic animal populations. To do this, BCS alert thresholds and a BCS collection and monitoring system must be defined on reasoned samples of animal populations.
It is an easy-to-use field tool. However, a good mastery of the BCS grid as well as a regular practice of scoring are necessary to obtain precise and reproducible ratings. It can also be used as a tool for monitoring and alerting the nutritional level of animal populations. Thus, the farmer can be called at any time to intervene on the feed ration and / or the health of the animal.
The BCS grid currently used in the intervention area of the Beef Cattle 2 project, does not seem to have been developed with reference to the breeds of cattle present in Northern Vietnam. This is the reason why we propose this BCS grid adapted to Yellow Cattle (crossbred Bos indicus x Bos taurus).
In 2020, Vall proposed a standardized BCS scoring system for tropical livestock animals for large animals (cattle, camels), small animals (sheep, and goats) and for donkeys, and horses. This document presents this BCS system applied to the Yellow cattle
ForestScan
No full textThis data package contains data from: ForestScan: a unique multiscale dataset of tropical forest structure across 3 continents including terrestrial, UAV and airborne LiDAR and in-situ forest census dat
NIRS Calibration for sensory attributes on raw fresh intact sweetpotato at CIP, Uganda.
No full textThe document highlights the NIR prediction models developed using spectra of raw intact sweetpotato roots collected across different genotypes and CIP trials in Uganda, in 2023. The process of sample and spectra collection has been documented earlier (https://doi.org/10.18167/agritrop/00708). Sensory reference data was collected according to documented protocols (Nakitto et al. 2022). Reference values (n=306 samples, 102 genotypes) and spectra were collected in first season of 2023 (2023A). Orange color intensity has consistently been modelled with higher accuracy (R2=0.88)
Replication Data for: A dataset of soil properties and crop observations from a long-term organic fertilization trial in Sub-Sahelian market gardening
No full textRecycling the growing stock of organic waste products (OWP) from cities, factories, and farms is a key challenge for sustainable agriculture. However, it must be done with awareness of potential long-term environmental and health risks. The SOERE PRO observatory was created in this context, including the trial in Sangalkam, Dakar region (Senegal), where these data were collected. Since 2016, four fertiliser types - one mineral (synthetic) and three organic - were applied on three crops a year (tomato, lettuce, carrot). A multi-variable dataset was consistently documented, including soil physico-chemical parameters measured at three depth once a year, OWP characterization, crop parameters, and management activities. All soil, OWP and vegetables samples are stored in a sample bank in Dakar, also described in the dataset, and available for additional analyses. The dataset has been shared in a Dataverse repository for free (re)use in meta-analyses, process modelling and other environmental studies or new projects (the trial is still running), in particular for understanding tropical ecosystem dynamics (nutrients, contaminants, biodiversity), and guiding sustainable land management practices