RESUMO
The long-term intensive production system employed in the Sugar Estates in Ethiopia, characterized by monoculture, preharvest burning, and excessive tillage, has led to soil degradation with a concomitant decline in sugarcane yield. Therefore, a study was conducted at Wonji-Shoa Sugar Estate (WSSE) with the objective of evaluating the effectiveness of different green manuring plant species and cane stool destruction methods (SDMs) in improving cane yield. To that end, seven green manure plant species (sunn-hemp, lablab, cowpea, soybean, mungbean, dhaincha, and sugarcane trash) were evaluated under three SDMs (cultivating-out, spraying-out with herbicide, and maintaining the stool as it is) using a split-plot design. The experimental fields were established on two major soil types, with green manure crops incorporated into the soil before planting the sugarcane. The dry matter production and nitrogen contribution of the green manure plants, as well as the height, population, diameter, and yields of sugarcane, were determined and subsequently subjected to statistical and economic analysis. The results showed that cowpea, followed by lablab, dhaincha, and sunn hemp, were the most effective green manures in terms of improving cane performance, with up to 17-20 % yield advantage and 21-40 % net economic benefits over the control treatment. Additionally, the spraying-out MSD was as effective as the cultivating-out MSD, but both outperformed maintaining the stool. In conclusion, utilizing these green manuring crops in combination with the spraying-out SDM presents notable advantages for improved cane yield and enhanced economic benefits in a sustainable manner. Adoption of these practices, therefore, holds significant potential for reversing the constantly declining sugarcane yields at WSSE.
RESUMO
Drastic and continuous decline in cane yields has become a major threat to sustainable sugarcane production in Ethiopia. Among the causes for the decline are the inefficient and ineffective system of monitoring sugarcane plantations. Adopting satellite-based crop monitoring through the Landviewer platform may circumvent this problem. However, the reliability of vegetation indexes calculated by the platform is unknown and thus requires evaluation. Accordingly, we tested the accuracy of selected Landviewer Calculated Vegetation Indexes (LCVIs) on three major sugarcane varieties and two cropping types. The goodness-of-fit of the sigmoid curve to the LCVIs profile of sugarcane was evaluated. The correlations between LCVIs and yield components, LCVIs and fractional green canopy cover (FGCC), as well as the time-serious Normalized Difference Vegetation Index (NDVI) and yields, were also analysed. We found that the goodness-of-fit of the sigmoid curve was significant (p < 0.001), with 84%-95% accuracy in all the indexes. The majority of LCVIs showed significant (p < 0.05) relationships with yield components and FGCC. The time-series NDVI also demonstrated a significant relationship with cane yield (R2 = 0.73-0.85) at the age of 10 months and above. The accuracy level of LCVIs varies with varieties and crop types, but the Normalized Difference Phenology Index (NDPI), Soil Adjusted Vegetation Index (SAVI), and NDVI were identified as the most consistent and effective LCVIs for sugarcane monitoring. Therefore, the accuracy of LCVIs was dependable and can be used effectively in monitoring sugarcane plantations to tackle the problem of continuous decline in the yield of the crop.
