Using Oil Palm Segregation Genetics to Decipher Illegitimate Seed Distribution Channels to Smallholder Farmers in Cameroon

Planting material or seed is the most determinant factor for oil palm productivity alongside agro climatological and management considerations. A study was conducted to determine the different varieties of oil palm planted in smallholders’ plantations, the distribution channels for oil palm seeds and all the actors involved in the seed trade sector in Cameroon. This is a bid to secure the supply of only improved planting materials to smallholder farmers. 230 oil palm smallholder plantations were surveyed and individual palms were subjected to varietal determination. The Chi-Square Test (c2) for Fixed Ratio Hypothesis (= 0.05) was used to determine whether the observed ratio deviates significantly from the Mendelian hypothesized genetic segregation ratio. Up to 65% of smallholder farms were found to be planted with poor planting material distributed in the different Mendelian ratios; 100% Dura, 50% Tenera and 50% Dura (1:1), 25% Dura, 50% Tenera and 25% Pisifera (1:2:1). The source of this poor quality planting material for these farms was deduced to come from private nursery entrepreneurs and workers of industrial plantations such as the Cameroon Development Corporation (CDC), Cameroon Palm Oil Company (SOCAPALM), Common Initiative Groups (CIG’s) and Non-Governmental Organisations (NGO’s). Farmers supplied by government services especially the Ministry of Agriculture and Rural Development and some of its specialized development projects all received good quality material. Thus, this is the only means now available which can assure the distribution of seeds good quality seed

Fruit Crop theft and its impacts on the productivity of oil palm agro-industries in Cameroon

Plantation agriculture and especially oil palm requires vast areas of land for their establishment. Rural livelihoods and neighboring agro industries may compete for the same available natural resources such as fertile land and water. This study was designed to assess the impact of indigenous livelihoods on the productivity of neighboring agro-industrial plantations. A total of 250 households located in settlements close to plantations were surveyed in 5 regencies of Cameroon. Farming was the principal occupation for 86% of the family heads with an average farm size of 2.22 hectares. Companies incurred an average loss in annual oil palm Fresh Fruit Bunches (FFB) production in the range of 20.67% and 77.44%. A strong positive correlation (R=0.644) was observed between production loss and total population of the settlements surrounding the plantation. In like manner, a strong negative correlation (R=-0.966) was observed between plantations’ production loss and the distance from indigenous settlements. There was a strong relationship between socio economic shocks on the local populations and the amount of security stationed in oil palm plantations. Fruit theft might have caused annual FFB loss of 36% - 45% on neighboring agro industrial plantations. It would be preferable for oil palm companies investing in rural proximities to implement strategies that can empower local communities to become economically independent. Keywords: Praedial larceny, rural livelihoods, sustainability, plantation security, oil palm development

Gene expression profiles of oil palm leaves from different oil yields and genetic population: Transcriptomic dataset

Oil palm (Elaeis guineensis Jacq.) is one of the most important oil-producing crops in the world. However, the demand for oil from this crop is expected to increase in the future. A comparative gene expression profile of the oil palm leaves was needed in order to understand the key factors that influence the oil production. Here, we reported an RNA-seq dataset from three different oil yields and three different genetic populations of oil palm. All raw sequencing reads were obtained from an Illumina NextSeq 500 platform. We also provide a list of the genes and their expression levels resulting from the RNA-sequencing. This transcriptomic dataset will provide a valuable resource for increasing oil yield