Having updated knowledge of cropland extent is essential for crop monitoring and food security early warning. Previous research has proposed different methods and adopted various datasets for mapping cropland areas at regional to global scales. However, most approaches did not consider the characteristics of farming systems and apply the same classification method in different agroecological zones (AEZs). Furthermore, the acquisition of in situ samples for classification training remains challenging. To address these knowledge gaps and challenges, this study applied a zone-specific classification by comparing four classifiers (random forest, the support vector machine (SVM), the classification and regression tree (CART) and minimum distance) for cropland mapping over four different AEZs in the Zambezi River basin (ZRB). Landsat-8 and Sentinel-2 data and derived indices were used and synthesized to generate thirty-five layers for classification on the Google Earth Engine platform. Training samples were derived from three existing landcover datasets to minimize the cost of sample acquisitions over the large area. The final cropland map was generated at a 10 m resolution. The performance of the four classifiers and the viability of training samples were analysed. All classifiers presented higher accuracy in cool AEZs than in warm AEZs, which may be attributed to field size and lower confusion between cropland and grassland classes. This indicates that agricultural landscape may impact classification results regardless of the classifiers. Random forest was found to be the most stable and accurate classifier across different agricultural systems, with an overall accuracy of 84% and a kappa coefficient of 0.67. Samples extracted over the full agreement areas among existing datasets reduced uncertainty and provided reliable calibration sets as a replacement of costly in situ measurements. The methodology proposed by this study can be used to generate periodical high-resolution cropland maps in ZRB, which is helpful for the analysis of cropland extension and abandonment as well as intensity changes in response to the escalating population and food insecurity.

Cassava is a staple food and a major source of income for many smallholder farmers. However, its yields are less than 6t ha⁻¹ compared to a potential yield of 2025t ha⁻¹ in Zambia. Understanding cropping practices and constraints in cassava production systems is imperative for sustainable intensification. Therefore, a survey of 40 households each with three fields of cassava at 12, 24, and 36 months after planting (MAP) was conducted. Analyzed soil data, leaf area index (LAI), intercepted photosynthetically active radiation, and management practices from 120 fields were collected and subjected to descriptive statistics. To explain yield differences within the same cassava growth stage group, the data were grouped into low- and high-yield categories using the median, before applying a nonparametric test for one independent sample. Stepwise regressions were performed on each growth stage and the whole dataset to determine factors affecting tuber yield. Cassava intercropping and monocropping systems were the main cropping systems for the 12 and 2436 MAP, respectively. Cassava yields declined by 209 and 633kg ha⁻¹ at 12 and 36 MAP due to soil nutrient depletion for each year of cultivation until field abandonment at 89 years. Fresh cassava yields ranged from 3.518.51, 13.5225.84, and 16.9230.98t ha⁻¹ at 12, 24, and 36 MAP, respectively. For every one unit increment in exchangeable K (cmol (+)/kg soil), cassava yield increased by 435, 268, and 406kg ha⁻¹ at 12, 24, and 36 MAP, respectively. One unit increment of magnesium (cmol (+)/kg soil) gave the highest yield increase of 525kg ha⁻¹ at 24 MAP. The low levels of soil organic carbon explained the deficient nitrogen in cassava fields, which limits the LAI growth and consequently reduced intercepted radiation and low yields. The effect of exchangeable K on growth was limited by the moderate availability of Mg and low N, thus the need for balanced fertilizer regimes.

The objective of this study was to evaluate the performances of three cassava genotypes on yield, physiology and morphological traits under different fertilization regimes. A field experiment was conducted in a split-plot design for two consecutive seasons in the Mansa district of the Luapula Province of Northern Zambia in the highly weathered Chromi-haplic Acrisol soils. Four fertilization regimes, control-M3, lime-M1, NPK fertilizer-M4 and NPK fertilizer + lime-M2 were the main plots, while three varieties (Mweru-V1, Bangweulu-V2 and Katobamputa (local)-V3) were subplots. Periodic measurements of leaf area index, light interception, yield and yield components from 75 days after planting (DAP) up to 410 DAP and daily weather measurements of data were recorded. Fertilization significantly increased the radiation use efficiency (RUE) and light extinction coefficient (K) in two seasons compared to the control. Significant fertilization regimes and varietal effects were observed for seasonal LAI, stem yield, root yield, biomass, harvest index (HI), tuber number, root diameter, plant height and SPAD (chlorophyll index). A significant year’s effects on root yield, yield components and physiological performances were observed while significant fertilization × variety interaction was observed on seasonal LAI, tuber number, root diameter, plant height and SPAD. Significant fertilization × year interaction effects were observed on root yield, yield components and physiological performances. Variety × year interaction was significant for seasonal LAI, stem yield, harvest index and plant height and no three-way interactions were observed on all the traits. NPK fertilizer + lime and NPK fertilizer treatments may be adopted to increase the response of cassava varietal yield, physiology and morphological traits in low soil nutrient conditions under high rain-fed conditions.

Cassava yields of 6tha⁻¹ are lower than the potential yield of 2025tha⁻¹ obtained in Northern Zambia. It is grown in legume intercropping with little or no fertilizer, causing nutrient depletion with consequent land abandonment. Therefore, the study objective was to investigate the performance of cassava under lime, fertilizer, and grain legume intercropping on exhausted land in Northern Zambia. A split-split plot design experiment was conducted over two seasons, comprising two lime rates (0 and 300kgha⁻¹), two fertilizer rates (0 and 100N:23P:80Kkgha⁻¹), and three grain legumes (common beans, cowpea, and soybean) intercropped in cassava and sole cassava arranged in RCBD with three replications. Periodic measurements of leaf area index (LAI), light interception, weather data, and yield components were recorded. A linear mixed model with year as a random factor was performed to assess the treatment effect of lime, fertilizer, and legume species intercropping on cassava growth characteristics, radiation-use efficiency (RUE), and selected yield components. Lime, fertilizer rates, and legume species intercropping were assigned as main, sub-, and sub-sub-treatments, respectively. Fertilization and fertilization+lime treatments in sole cassava and cassava-common bean intercropping significantly increased the RUE and light extinction coefficient (k) compared to nonfertilized and only lime treatments. Lime x fertilizer x cropping system interaction was significant on chlorophyll index and plant height, RUE, tuber yield, HI, and total dry matter (TDM) yield. Cropping system x year interactions were significant on season LAI. On average, every kg of cassava yield loss in intercropping was compensated by 0.46kg soybean, 0.20kg common beans, and 0.26kg of cowpea. NPK fertilizer+lime, NPK fertilizer, and grain legume intercropping may be adopted to increase cassava tuber yields and legume grain yield response on nutrient-depleted soils in high rainfall areas of Zambia.

The nanoparticles processed from non-edible crop materials and residues have evoked great use in the food and non-food industry. The diversity in agricultural waste biomass and differences in extraction techniques account for variations in end-product properties, and would require examination of waste crop types (source) to determine suitability for the production of cellulose, nanocellulose and graphene particles. This review showed that screening criteria of end-user properties include chemical composition, cellulose contents, morphology, crystallinity, thermal stability, rheology, surface charge and zeta potential. The literature shows that the end-user properties vary with plant source (that is crop type) and extraction techniques. In this review, the cellulose content and percentage crystallinity are primary parameters for selecting agricultural waste biomass for the production of nanocellulose and nanofibrils. Additionally, zeta potential and surface charge can determine polymer interaction for suitability in industrial applications. Moreover, nanocellulose and biochar were found to have various industrial applications as ingredients in the production of food packaging including active packaging, rheological modifiers and thickeners. Pyrolysis is the eminent strategy for the transformation of agricultural waste into biochar-derived nanoparticles and carbon-rich materials.

The nanoparticles processed from non-edible crop materials and residues have evoked great use in the food and non-food industry. The diversity in agricultural waste biomass and differences in extraction techniques account for variations in end-product properties, and would require examination of waste crop types (source) for suitability of production of cellulose, and nanocellulose including graphene particles. This review showed that screening criteria of end-user properties include chemical composition, cellulose contents, morphology, crystallinity, thermal stability, rheology, surface charge and zeta potential. Literature shows that the end-user properties vary with plant source (that is crop type) and extraction techniques. In this review, the cellulose content and percentage crystallinity are primary parameters for selecting agricultural waste biomass for production of nano-cellulose and nanofibrils. Additionally, zeta potential and surface charge can determine polymer interaction for suitability of industrial applications. Moreover, nanocellulose in-cluding biochar were found to have various industrial application as ingredients in pro-duction of food packaging including active packaging, rheological modifiers and thicken-ers. Pyrosis is eminently the strategy for transformation of agricultural waste into bio-char-derived nanoparticles and carbon-rich materials.