Peanut Crop Research Articles

Rotation of planting strips and reduction in nitrogen fertilizer application can reduce nitrogen loss and optimize its balance in maize–peanut intercropping

In dryland farming, maize (Zea mays L.) and peanut (Arachis hypogaea L.) intercropping has been widely practiced to achieve sustainable agriculture goals. However, only a few studies have investigated the effect of reducing nitrogen (N) application on the performance of maize and peanut crops in intercropping system based on rotation of the planting strip. Therefore, a field study was conducted from 2018 to 2020 in Yangling, China, where the treatments comprised peanut monoculture, maize monoculture, maize–peanut intercropping, maize–peanut rotational intercropping, and maize N reduction based on the rotational intercropping system. The N accumulation and yield in maize increased after intercropping, while the N accumulation, yield and N fixation capacity of peanut decreased than other treatments. In addition, soil residual N, ammonia volatilization, N leaching, and N2O emissions of maize–peanut intercropping significantly decreased than maize monoculture. The rotation of planting strips in maize–peanut intercropping had increased the land equivalent ratio by 3.06 % and 9.39 % and N recovery efficiency by 15.45 % and 27.37 % in the second and third years of planting, as well as alleviated the continuous cropping barrier for peanuts. N reduction does not affect N fixation capacity and yield of peanut and reduces ammonia volatilization and N leaching from farmland, although it does influence maize yield. The optimal cropping system was a 20 % N reduction in maize planting strip under rotational intercropping because N accumulation and the farmland productivity were not affected significantly, while the N losses to the environment also decreased by an average of 44.17 % and 14.87 % compared with traditional intercropping and monoculture in the second and third years of planting. These results are useful for optimizing cropping systems to promote sustainable development in dryland regions and mitigate N pollution.

Three-Dimensional Vulnerability Assessment of Peanut (Arachis hypogaea) Based on Comprehensive Drought Index and Vulnerability Surface: A Case Study of Shandong Province, China

Agricultural drought is a major problem facing China’s agricultural production. In this study, the cash crop ‘peanut’ was used as an example to explore vulnerability. Through the atmosphere–plant–soil continuum system, a single index that could represent different types of droughts affecting peanuts was selected and weighted using the CRITIC weighting method to construct a multi-source data fusion drought index (MFDI). Then, Pearson correlation analysis between the comprehensive drought index and relative meteorological yield and the Mann–Kendall trend test for different growth periods of peanuts were used to verify MFDI and analyze the variation over time. A three-dimensional vulnerability assessment method of drought intensity–drought duration–yield reduction rate was established based on the run theory and trend surface analysis. The results show that the constructed multi-source data fusion drought index (MFDI) can more accurately characterize the actual drought conditions of peanuts in Shandong Province. The MFDI results showed that the drought severity in the coastal areas of the study area decreased with the growth and development of peanuts, while the drought became more severe in the western and northern parts during the late growth period of peanuts. The vulnerability surface of the drought intensity–drought duration–yield reduction rate showed that when the drought intensity was < 0.8 and the duration was < 3.5 months, the vulnerability of peanut crops was low, and then with the increase in drought intensity or duration, the vulnerability increased. The impact of drought duration cannot be ignored. In contrast to traditional vulnerability assessment methods, this study established a three-dimensional vulnerability surface, which provides a new approach for agricultural drought vulnerability assessment. The research results are helpful for a deeper understanding of the relationship between drought and crop vulnerability and provide scientific support for local governments in formulating disaster prevention and mitigation policies.

Root Nodule Categorization and Their Relation with Plant Growth in Peanut Crop Grown in Alfisols

To investigate the relationship between nodule category and plant growth characteristics in peanut, nodules were classified into three categories: large size nodule (LSN) ( greater than 2 mm), medium size nodule (MSN) (1-2 mm) and small size nodule (SSN) ( less than 1 mm) and their position on roots (primary and lateral roots). The number of LSNs on primary roots was found to be much higher than on lateral roots. The number of MSN developed on primary and lateral roots was comparable, whereas, lateral roots had a higher SSN number. In addition, when comparing the LSN and MSN numbers to SSN number, the plant growth parameters showed a high positive correlation. Multivariate regression analysis yielded similar results. This nodule classification technique aids in the identification of peanut nodules and their role in quantification of plant growth characteristics. Further, this technique can be used in identifying/screening of efficient nodulating peanut genotypes.

Modeling drought stress impacts under current and future climate for peanut in the semiarid pampas region of Argentina

In the semiarid pampas region of Argentina, peanut ( Arachis hypogaea L.) crop undergoes frequent and unpredictable drought stress periods, with high probability of occurrence under future climate change projections. However, the overall frequency of occurrence and timing of different drought stress patterns under current and future climates has not been well investigated for the main peanut region in central Argentina. The aims of this study were to: (i) define the main peanut drought stress patterns and their occurrence (frequency) during the peanut growing season, via a crop growth modeling approach, (ii) test seed yield stability of the formerly defined (in i) drought stress patterns under future climate scenarios, and (iii) analyze the effect of sowing dates on peanut seed yield as a management strategy to mitigate the impact of future climate scenarios for peanut seed yield in the semiarid pampas region of Argentina. The APSIM-peanut growth model was calibrated and validated for local genotypes and production environments. Our study simulated seasonal drought stress patterns at five representative locations across the region under current and future climate scenarios, and tested six sowing dates as a practice to mitigate the impact of climate change. Clustering analysis identified two contrasting environment types (ETs). The high stress ET showed greater frequency of occurrence (>50%) at the southern locations. Future climate conditions increased the frequency of high stress ET by roughly 6% and reduced peanut seed yield by 12%, as average across locations. For both current and future climates, earlier sowing dates maximized peanut seed yield, regardless the locations. Changing sowing date was not an effective practice to mitigate the negative impact of climate change on peanut seed yield. The defined ETs allowed identifying a target population of environments (TPE) having implications for optimizing peanut breeding and management strategies. The projected increase in the frequency of drought stress for all tested locations provides a challenging scenario for sustaining peanut productivity in this region. • The aims were to determine drought patterns under current and future climate, and to test sowing date as a mitigation tool • The defined drought stress patterns changed the frequency across locations, identifying a target population of environments • ·Future climate increased the frequency of drought stress by ~6% and reduced peanut seed yield by ~12% • Sowing date did not mitigate climate change impact. • This study provides insights to optimize breeding and management, and assists policy makers to address climate change.

Yield response to row spacing, irrigation and varieties of peanut in the semiarid region of Minas Gerais, Brazil

Studies on the management of peanut crops in the semiarid region of Minas Gerais are scarce. Therefore, the objective was to evaluate the agronomic performance of four peanut cultivars under different irrigation systems and row spacing in northern Minas Gerais. The cultivars IAC 503, Runner IAC 886, IAC Tatu ST, and Crioula were grown at row spacing of 0.5, 0.7, and 0.9 m and irrigated or not irrigated. The following variables were evaluated: Total number of pods, number of commercial pods, number of seeds, mass of one hundred grains, grain yield index, oil content, pod yield, grain yield and oil yield. After analysis of variance, the average values were compared using the Scott-Knott method with a probability of 5%. The spacing of 0.5 m promoted higher productivity in pods, grains, and oil in both systems. Under irrigation, IAC 503 and IAC 886 were the most productive, while the cultivars did not differ under non-irrigated cultivation. Finally, irrigation resulted in an increase in grain yield of up to 50% compared to non-irrigated cultivation.

Efficiency of different potassium and sulfur fertilizers on peanut (Arachis hypogaea) production in tropical sandy soil

In the sandy soil of Vietnam's South-Central Coast, peanuts are a significant crop. The application of K and S needs to crops has recently attracted a lot of interest, especially for peanut. However, a comparison on the effects of different types of K and S fertilizers viz., ammonium sulphate (AS), superphosphate (SP), NPKS, potassium sulphate (SOP), and potassium chloride (MOP) is to be evaluated on the yield, quality, and K and S content in peanut seed. This study was conducted during winter spring and summer seasons 2019 - 2020 at Binh Dinh province (SCCVN). Equal rate of 75 kg K/ha and 30 kg S/ha was applied as SOP, NPKS and a mixture of AS, SP, MOP and these were compared against a control which applied nitrogen (N) and phosphorus (P) fertilizers. SOP application resulted in the highest yield (2.93 - 4.92 t/ha), protein (24 %), lipid (53 %) and seed K (0.19-0.53 %) and seed S (0.57-0.69 %). The study concluded that application of 75 kg K/ha and 30 kg S/ha in SOP fertilizer based on @ 8 tons of cattle manure + 40 kg N + 40 kg P + 500 kg lime/ha is suitable for peanut crop in SCCVN.

Efficiency of different potassium and sulfur fertilizers on peanut (Arachis hypogaea) production in tropical sandy soil

In the sandy soil of Vietnam's South-Central Coast, peanuts are a significant crop. The application of K and S needs to crops has recently attracted a lot of interest, especially for peanut. However, a comparison on the effects of different types of K and S fertilizers viz., ammonium sulphate (AS), superphosphate (SP), NPKS, potassium sulphate (SOP), and potassium chloride (MOP) is to be evaluated on the yield, quality, and K and S content in peanut seed. This study was conducted during winter spring and summer seasons 2019 - 2020 at Binh Dinh province (SCCVN). Equal rate of 75 kg K/ha and 30 kg S/ha was applied as SOP, NPKS and a mixture of AS, SP, MOP and these were compared against a control which applied nitrogen (N) and phosphorus (P) fertilizers. SOP application resulted in the highest yield (2.93 - 4.92 t/ha), protein (24 %), lipid (53 %) and seed K (0.19-0.53 %) and seed S (0.57-0.69 %). The study concluded that application of 75 kg K/ha and 30 kg S/ha in SOP fertilizer based on @ 8 tons of cattle manure + 40 kg N + 40 kg P + 500 kg lime/ha is suitable for peanut crop in SCCVN.

Color contour texture based peanut classification using deep spread spectral features classification model for assortment identification

Agriculture is one of great economic growth in India by producing variety of peanuts for various co products development. Peanut Crop and weed identification is an important step in developing a highly efficient automotive peanut production system. Most of the exiting classification fix the threshold margins to select the inappropriate features cause classification inaccuracy. Deep learning, as a powerful image processing technology, can extract conventional and characteristic features in layers. Spectral information is used as the input of the network, and the output spectral characteristics of the network are directly passed to the subsequent classifiers to achieve pixel-level classification. To resolve the classification categorization problem, we propose a Color contour texture based peanut classification using deep spread spectral features classification model for variety identification. Initial the Cascading subset Feature Filtering (CSFF) is applied to select the shape textures, color gradient rate form histogram equivalence and returns the feature scalar values. Based in CSFF the feature weight is attained to Social Spider Optimization to select the Impact Features Weight (SSO-IFW). The optimal object segmentation war applied based on cross fold object verification to select the shape projection features. Then Ada Boosting classifier generate the type of object structural for identifying type definition to generate pattern to produce peanut characteristic clusters. Based on Image Features recognition clusters, deep spread spectral neural classification is applied to train the features with soft-max logical activation function with Adaptive Convolution Neural Network (ACNN) to categorize the peanuts based on feature characteristics using image recognition, 20 varieties of peanut are collected through scanner type dataset to train the images into deep neural network. This produce high classification accuracy up to 89 %, high precision, recall rate under F-measure with low false rate. This achieves high classification than other existing methods.

Trocas gasosas e crescimento do amendoim submetido ao estresse salino e hídrico

ABSTRACT Peanut crops are of great economic interest because their seeds are used as an important source of vegetable protein and edible oil. The objective of this study was to evaluate the physiological indices and growth of peanut crops subjected to saline and water stress. The experiment was conducted in Auroras, Redenção, Ceará, Brazil using a completely randomized split plot statistical design. The plots were composed of irrigation water treatments with varying levels of electrical conductivity - ECw (1.0, 2.0, 3.0, 4.0 and 5.0 dS m-1), while the subplots were formed by the water regimes of 50% and 100% crop evapotranspiration. Plant height, leaf number, shoot dry matter, relative chlorophyll level, transpiration, and leaf temperature were affected by salt stress. The water regime of 100% ETc provided better performance for the variables stem diameter, leaf number, and shoot dry mass of peanuts.

Complete Genome Sequence of Bradyrhizobium sp. Strain C-145, a Nitrogen-Fixing Rhizobacterium Used as a Peanut Inoculant in Argentina.

ABSTRACTWe present the complete genome sequence of Bradyrhizobium sp. strain C-145, one of the most widely used nitrogen-fixing rhizobacteria for inoculating peanut crops in Argentina. The genome consists of 9.53 Mbp in a single circular chromosome and was determined using a hybrid long- and short-read assembly approach.

Crescimento e nutrição da cultura do amendoim submetida ao estresse salino e adubação organomineral

ABSTRACT The peanut crop, owing to its microbiological and nutritional aspects, is of great economic importance for agriculture and the food industry. However, salt stress can negatively affect nutrient uptake and plant growth. The objective of this study was to evaluate the growth and foliar nutrient concentrations of peanut plants subjected to irrigation with saline water and different forms of organomineral fertilization. The experiment was conducted in a greenhouse in a completely randomized design (5 × 2 factorial scheme) with five forms of fertilization (F1 = 100% mineral; F2 = 100% bovine biofertilizer; F3 = 100% vegetal ash; F4 = 50% mineral + 50% bovine biofertilizer; and F5 = 50% mineral + 50% vegetal ash), two levels of electrical conductivity of the irrigation water (ECw) (1.0 and 5.0 dS m-1), and five replicates. Salt stress inhibited plant growth and the number of leaves, but increased the average stem diameter with the use of 100% bovine biofertilizer and higher salinity water. When ECw of 5.0 dS m-1 was used along with the bovine biofertilizer (100%), the P concentration in plants increased. The K concentration was reduced in plants fertilized with bovine biofertilizer (100%) and vegetal ash (100%), while Mg concertation was reduced in plants fertilized with bovine biofertilizer (100%) or mineral fertilizer (50%) + bovine biofertilizer (50%) with irrigation water of 5.0 dS m-1.

Effect of Bacteria Inoculation and Iron Application Rates on Nodulation and Yield of Different Peanut Varieties

Farklı yerfıstığı çeşitlerinde bakteri aşılaması ve demir uygulamalarının nodülasyon ve verime etkisini araştırmak amacıyla yapılan bu çalışma, Adana İl’i Ceyhan İlçesi Altıkara köyünde 2 yıl süreyle yürütülmüştür. Araştırmada, I. ürün olarak NC-7, Halisbey, Arıoğlu 2003 ve Osmaniye 2005 yefıstığı çeşitleri kullanılmıştır. Denemede üç farklı demir sülfat dozu (Fe0, Fe1: 5 kg Fe/da, Fe2: 10 kg Fe/da) ve 2 farklı bakteri uygulaması (B0: aşılamasız; B1: 380 nolu R.leguminosarum suşuyla aşılanmış) yapılmıştır. Birinci ürün olarak ekilen yerfıstığı bitkisinin çiçeklenme döneminde kök ve yeşil aksam örneklemesi; hasat döneminde ise kök, yeşil aksam ve dane örneklemesi yapılmıştır. Sonuçlar gerek 1. yıl gerekse 2. yıl bitkilerde nodül oluşumu olmadığını göstermiştir. Dolayısıyla nodülasyon, biyomas ve çeşitli aksamların N içeriklerinde bakteri aşılamasına bağlı herhangi bir etki de görülmemiştir. Demir uygulamasına bağlı olarak ise incelenen parametrelerde çiçeklenme ve hasat dönemine ve denemede kullanılan yerfıstığı çeşitlerine bağlı olarak farklı etkiler görülmüştür. İncelenen parametreler açısından kullanılan çeşitlere göre değişen farklılıklar belirlenmiştir. Meyve verimi açısından Halisbey çeşidi 1. yıl en yüksek verim değeri gösterirken (694 kg/da) bunu Osmaniye 2005 (686 kg/da) ve Arıoğlu 2003 (644 kg/da) izlemiş, 2. yıl ise her üç çeşit de 700-721 kg/da arasında verim değeri göstermiş, NC-7’den 1. yıl 457 kg/da, 2. yıl 458 kg/da verim alınmıştır.

Maximizing crop water productivity from the water unit

Egypt is currently suffering from the vast increase in population that is increasing water consumption whether for domestic use or by other sectors especially, the agricultural one, which consumed more than 80 % of the water income. Experiment was conducted under drip irrigation system in the sandy soils of the experimental Farm of the National Research Centre, El-Nubaria, El-Behera governorate. The aim of this work is to study the effect of the N (0, 25; 50 kg/fed) and P (0, 10, 20, 30) fertilizers at different rates on the growth, yield parameters and crop water productivity (CWP) of peanut plant. Resulted data showed that application of N and P at the rates of and kg/fed, respectively on peanut crop to increase yield and enhance quality. CWP increased in the current experiments in the following order of 60>80>100 % ETo despite the reduction in crop yield. The quality attributes of oil and protein contents significantly improved by irrigation levels, N and/or P fertilizers application rates and their interactions.

Potential Environmental Impacts of Peanut Using Water Footprint Assessment: A Case Study in Georgia

The recent decade has witnessed an increase in irrigated acreage in the southeast United States due to the shift in cropping patterns, climatic conditions, and water availability. Peanut, a major legume crop cultivated in Georgia, Southeast United States, has been a staple food in the American household. Regardless of its significant contribution to the global production of peanuts (fourth largest), studies related to local or regional scale water consumption in peanut production and its significant environmental impacts are scarce. Therefore, the present research contributes to the water footprint of peanut crops in eight counties of Georgia and its potential ecological impacts. The impact categories relative to water consumption (water depletion—green and blue water scarcity) and pesticide use (water degradation—potential freshwater ecotoxicity) using crop-specific characterization factors are estimated for the period 2007 to 2017 at the mid-point level. These impacts are transformed into damages to the area of protection in terms of ecosystem quality at the end-point level. This is the first county-wise quantification of the water footprint and its impact assessment using ISO 14046 framework in the southeast United States. The results suggest inter-county differences in water consumption of crops with higher blue water requirements than green and grey water. According to the water footprint analysis of the peanut crop conducted in this study, additional irrigation is recommended in eight Georgia counties. The mid-point level impact assessment owing to water consumption and pesticide application reveals that the potential freshwater ecotoxicity impacts at the planting and growing stages are higher for chemicals with high characterization factors regardless of lower pesticide application rates. Multiple regression analysis indicates blue water, yield, precipitation, maximum surface temperature, and growing degree days are the potential factors influencing freshwater ecotoxicity impacts. Accordingly, a possible impact pathway of freshwater ecotoxicity connecting the inventory flows and the ecosystem quality is defined. This analysis is helpful in the comparative environmental impact assessments for other major crops in Georgia and aids in water resource management decisions. The results from the study could be of great relevance to the southeast United States, as well as other regions with similar climatic zones and land use patterns. The assessment of water use impacts relative to resource availability can assist farmers in determining the timing and layout of crop planting.

Implementasi Data Mining Untuk Memprediksi Masa Panen Dalam Bercocok Tanam Dengan Menggunakan Algoritma Naive Bayes Classifier

Abstract−This study intends to predict the harvest period in farming at the Regional Technical Implementation Unit of Gabe Hutaraja Various Crops. The method used in this study is the Naive Bayes Classifier. The data used in this study are time series data from 2015 to 2017. The results of this study are predictions of rice, peanut, and corn crops in the future.
 Naive Bayes Classifier is a simple probabilistic classification process based on the application of Bayes' Theorem (Bayes rule) with the assumption of strong independence, in other words, in Naive Bayes, the model used is an independent feature model. Implementation using RapidMinner5.3 is used to help find an accurate value.
 The benefits of writing this research are that it can predict rice, peanut, and corn crops so that it is needed in farming as a field of planning and improving the quality of crop yields that aim to reduce farmers' losses.

Food Grade Oil Quality of Peanut (Arachis hypogaea L.)

High-oil crop peanut has about 50% edible oil content. Major components of fatty acids of peanut oil are unsaturated fatty acids (oleic acid and linoleic acid). Oxidative stability is an important factor in peanut process industry. High-oleic peanut contains ≥72% oleate and <8% linoleate and preferred by oil processors and consumers. High-oleic peanuts provide a spectrum of nutrients and have improved sensory properties and technological advances beyond conventional peanuts. Also relation of enviromental stress factors with quality are mentioned here below in this review.

Physiological quality of peanut seed affected by tomato spotted wilt disease

AbstractTomato spotted wilt disease (TSW) caused by tomato spotted wilt virus (TSWV) (genus Orthotospovirus) is a relevant disease in the peanut (Arachis hypogaea L.) crop. The effects of TSW in the plant are well documented. However, its effect on the seed physiology is unknown. The objective of this study was to evaluate the vigor and germination of peanut seeds from different genotypes with TSW symptoms. One cultivar and six germplasm lines related to A. ipaënsis Krapov. & W.C. Gregory and A. duranensis Krapov. & W.C. Gregory in addition to two U.S. cultivars (resistant and susceptible checks) were evaluated. Seeds were separated into symptomatic and asymptomatic classes. The mass of 100 seeds varied from 31 to 72 g among the genotypes. Germination and vigor were assessed by using a thermal gradient table (12–32 °C). Seeds that did not germinate during the test on the table were transferred to an incubator at 25 °C for three additional days to quantify total germination. Seed vigor was high across all genotypes and symptomology classes. Total germination was reduced for seeds kept at low temperature (12–16 °C) in the thermal table, regardless of genotype or symptomology. Overall, TSW symptoms did not affect germination, vigor, and seed size negatively.

Energetics and profitability of peanut (Arachis hypogaea)-based cropping systems as influenced with conservation agricultural practices

Increasing energy use efficiency and reducing greenhouse gases (GHGs) emissions from agriculture are majorchallenges to achieve sustainable development goals (SDGs). An experiment, comprising 14 treatments, viz. sole peanut (Arachis hypogaea L.), peanut-fallow-sesbania, peanut-fallow-green gram (GG), peanut-conventional tilled wheat (CTW), peanut-CTW-sesbania, peanut-CTW-GG, peanut-CTW-wheat straw incorporation (WSI), peanut-zero tilled wheat (ZTW), peanut-ZTW-sesbania, peanut-ZTW-GG, peanut-ZTW-WSI, peanut+pigeonpea, peanut+pigeonpeasesbania and peanut+pigeonpea-GG was laid out in randomized block design with three replications for five consecutive years (2011–12 to 2015–16) at Junagadh, Gujarat, at fixed site to study the influence of conservation agricultural practices on energetics and profitability of peanut-based cropping systems. Green manuring with sesbania significantly improved the pod yield of peanut (12.8%) and seed yield of pigeonpea (8.9%). Zero tillage (ZT) improved wheat yield by 4.8% over Conventional tillage (CT). The energy requirement of peanut+pigeonpea intercropping was 16.7% lower than peanut–wheat cropping system irrespective of GM and WSI. Peanut–ZT wheat with sesbania green manure recorded highest energy output (251.2 × 103 MJ/ha) and net energy (201.0 × 103 MJ/ha). This cropping system also fetched the highest system productivity (4551 kg/ha), and system profitability (` 125.7 × 103/ha) followed by peanut–ZT wheat (INR 120.6/ha × 103/ha). Therefore, peanut–ZT wheat–green manuring (sesbania/greengram) cropping system was found as productive, economical and energy efficient which might be promoted to intensify the sole peanut cropping in Saurashtra region of Gujarat.

"Unmasking the Villain": Integrative Taxonomy Reveals the Real Identity of the Key Pest (Thysanoptera: Thripidae) of Peanuts (Arachis hypogaea L.) in South America.

Simple SummaryIn this work, we aimed to resolve the identification of the peanut thrips, the key pest of Arachis hypogaea in South America. Based on morphological, biological, and molecular data, we conclude that the name historically applied to this pest, Enneothrips flavens, constitutes a misidentification and that the peanut thrips is actually an undescribed species, Enneothrips enigmaticus sp. n.The peanut thrips, Enneothrips enigmaticus sp. n., is the key pest of Arachis hypogaea L. in South America, where it can cause yield losses of up to 85%. This species has historically been identified as Enneothrips flavens, but access to the holotype of this species and freshly collected material from southeastern and northern Brazil revealed that specimens commonly collected on peanut crops are not conspecific with E. flavens. Biological, molecular, and morphological assessments were carried out and led to the conclusion that the key pest of A. hypogaea belongs to a previously undescribed species: Enneothrips enigmaticus sp. n.

AgMIP Regional Integrated Assessment of Agricultural Systems in Nioro, Senegal

The Agricultural Model Intercomparison and Improvement Project (AgMIP) developed protocol-based methods for Regional Integrated Assessment (RIA) of agricultural systems. These methods have been applied by teams of scientists working with regional and national stakeholders across Sub-Saharan Africa and South Asia. This paper describes the data sets that were used to implement the AgMIP RIA methods for the Nioro region of Senegal. The goal of the RIA is to assess the potential impacts of climate change on the principal agricultural system in the Senegal peanut basin comprised of peanut, millet, maize and other minor crops and livestock, and to assess adaptations of that system to climate change, under current as well as future climate and socio-economic conditions. The data sets include: the Representative Agricultural Pathways (RAPs) developed for Nioro from 2000-2050; climate data used to implement crop yield simulations; the data used to parameterize the Agricultural Production Systems sIMulator (APSIM) and the Decision Support System for Agrotechnology Transfer (DSSAT) crop models, which include historical climate data and future climate scenarios; and the data used to parameterize the Tradeoff Analysis Model for Multi-dimensional Impact Assessment (TOA-MD) economic simulation model. The analysis is structured around four AgMIP “core questions'' of climate impact assessment.