Can Small-Scale Dairy Farm Profitability Increase with the Use of Solar Energy Technology? An Experimental Study in Central Tunisia

The dairy sector in Tunisia is based on small-scale farms, with 81% of the breeders owning less than five cows. On these farms, milk is stored in plastic containers, resulting in post-production losses estimated at 10% in the studied region. Due to high temperatures, the present paper aims to study the implementation of an innovative solar-powered milk cooling system in Central Tunisia and assess its profitability for dairy farmers. The methodology is based on a comparison of three small-scale farm business models: a farm without any milk cooling equipment, a farm using an innovative milk cooling technology, and a farm using an electrical cooling tank. Results showed the significance of milk cooling in reducing milk rejection to 0%, leading to a total production of 6400 L per cow by the fifth year. Additionally, milk sales were found to increase due to the premium of 0.010 TND/L for cooled milk paid. In addition, farms utilizing solar-powered milk cooling technology exhibited superior profitability in terms of financial indicators. This research offers a sustainable energy solution for milk cooling on small farms, specifically addressing the challenges faced by these farms located in isolated areas where access to electricity is limited and the availability of milk cooling equipment is lacking

Profitability of Manufactured Feed Pellets for Small-Scale Crop-Livestock Farmers in Tunisia

The aim of this R4D Initiatives is to explore the profitability of manufactured feed pellets for small-scale crop-livestock farmers in Tunisia. During the past few growing seasons, within several R4D initiatives and projects (the SWC@Scale as part of the global GIZ ProSol Program; the CRP-Livestock “feed and forages”, and the International Fund for Agricultural Development (IFAD) funded CLCA phase 2), ICARDA and its national partners have introduced imported feed pellet machines that were donated with a 10% financial contribution (to ensure strong ownership of the technology) to some pre-selected professional farmer organizations (FO) (SMSA and GDA5) and individual farmers including agri-preneurs, with the idea of developing small feed businesses using these machines and boosting the nutrition of local herds. After assessing the available feed resources for each region (Northern, Center, and Southern), the leading members of each FO, under the supervision of the project’s scientific teams, developed various feeding formulas. Other farmers have been developing their own formulas based on consultation with local extension agents. Some of the formulas used by farmers are still under experimentation and will be the subject of this brief, aiming at validating their economic viabilities

Faisabilité technico-économique des bouchons alimentaires fabriqués pour les petits éleveurs en Tunisie

Les bouchons alimentaires représentent une technologie prometteuse pour l’alimentation du bétail en Tunisie. Cette Technologie offre des multiples intérêts économiques, financiers, et techniques pour les petits agriculteurs et éleveurs dans les systèmes mixtes "Culture-Elevage". Cette fiche démontre la faisabilité technico-économique des bouchons alimentaires fabriqués pour les petits éleveurs en Tunisie

الجدوى التقنية والإقتصادية للمكعبات الغذائية المصنعة لدى صغار المزارعين في البلاد التونسية

تناقش هذه الجذاذة الفنية تقنية المكعبات الغذائية للحيوانات، مبرزة مزاياها في تغذية الماشية. كما تبين حدود هذه التقنية، و العوامل التي تؤثر على جودة المكعبات الغذائية للحيوانات. وفي النهاية، تقترح البطاقة الفنية نموذج أعمال للإنتاج المحلي للمكعبات الغذائية للحيوانات، مع التركيز على الجوانب الاقتصادية والمالية لهذه النشاط، بالإضافة إلى الاستنتاجات والآفاق المتعلقة بالاستدام

Resilient Project Scheduling Using Artificial Intelligence: A Conceptual Framework.

International audienceThis paper explores the role that Articial Intelligence (AI) can play in building resilient project schedules. Based on a literature review and brainstorming sessions, we introduce a conceptual framework that details how AI-enabled predictive and prescriptive analytics can be leveraged to improve project schedule resilience. The latter species the potential of AI to make use of historical and real-time data to better contain the eect of disruptions on project schedules