How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia.
Ontology highlight
ABSTRACT:
SUBMITTER: Kosmowski F
PROVIDER: S-EPMC8639447 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Intra-plot heterogeneity in yield is often observed in smallholder farming systems, although its implications for yield measurement remain under-investigated. Using a unique dataset on smallholder maize production in Ethiopia, we quantify the magnitude of inter- and intra-plot heterogeneity, describe the relationship between intra-plot heterogeneity and maize productivity, and document the implications of intra-field heterogeneity on the accuracy of alternative yield estimation protocols. Our data include five common yield estimation protocols, as well as full plot harvests of 230 smallholder maize fields. We surveyed agronomic decisions, biophysical variables, and accessibility characteristics of the surveyed fields. We quantify intra-plot heterogeneity using the coefficient of variation (CV) of stand density, cob weight, and maize grain yield. A generalized linear mixed model is used to explore the relationship between these variables and the method- and heterogeneity-dependence of yield estimation accuracy. We find inter-plot CV values ranging from 32 to 56 %, 22 to 73 % and 39 to 49 % in population density, cob weight and grain yield, respectively. Intra-plot heterogeneity constituted most of this variation, with across-method mean CV values of 41 %, 82 % and 63 %, respectively, of the total variability in population density, cob weight and grain yield. A rise in intra-plot heterogeneity of 0.5 % to 0.8 % is associated with a significant increase in yield estimation error under alternative yield estimation protocols. Regression analysis shows that interactions in agronomic decisions, input intensity and plot accessibility factors dictate intra-plot heterogeneity and method accuracy in smallholder systems. Intra-plot heterogeneity is larger than inter-plot heterogeneity in the current study area. Our analysis shows that the effect of intra-plot heterogeneity on yield estimation accuracies is method-dependent and yield estimation methods that fail to capture true intra-plot heterogeneity are more error-prone. Results of such estimations should be considered with caution when used as the basis of decision-making.
| S-EPMC8146729 | biostudies-literature
Project description:Yield gaps of maize (Zea mays L.) in the smallholder farms of eastern India are outcomes of a complex interplay of climatic variations, soil fertility gradients, socio-economic factors, and differential management intensities. Several machine learning approaches were used in this study to investigate the relative influences of multiple biophysical, socio-economic, and crop management features in determining maize yield variability using several machine learning approaches. Soil fertility status was assessed in 180 farms and paired with the surveyed data on maize yield, socio-economic conditions, and agronomic management. The C&RT relative variable importance plot identified farm size, total labor, soil factors, seed rate, fertilizer, and organic manure as influential factors. Among the three approaches compared for classifying maize yield, the artificial neural network (ANN) yielded the least (25%) misclassification on validation samples. The random forest partial dependence plots revealed a positive association between farm size and maize productivity. Nonlinear support vector machine boundary analysis for the eight top important variables revealed complex interactions underpinning maize yield response. Notably, farm size and total labor synergistically increased maize yield. Future research integrating these algorithms with empirical crop growth models and crop simulation models for ex-ante yield estimations could result in further improvement.
| S-EPMC7039445 | biostudies-literature
Project description:Improving fertilizer recommendations for farmers is essential to increase food security in smallholder landscapes. Currently, blanket recommendations are provided across agro-ecological zones, although fertilizer response and nutrient use efficiency by maize crop are spatially variable. We aimed to identify factors that could help to refine fertilizer recommendation by analyzing the variability in fertilizer response (FR) and the agronomic nitrogen use efficiency (N-AE). A literature search for on-farm studies across Kenya and Sub-Sahara Africa (SSA), excluding Kenya, yielded 71 publications. The variability in FR was studied using a meta-analysis whereas key factors that influence FR and N-AE were studied with linear regression models. On average, the FR was 2, but it varied considerably from 1 to 28.5 (excluding outliers). In SSA, 18% of the plots were non-responsive plots with an FR < 1. The main factors affecting N-AE for Kenya were P-Olsen, silt content, soil pH, clay and rainfall, whereas only soil pH, exchangeable K and texture were important for SSA. However, our study indicates that available data on soil, climate and management factors could explain only a small part (< 33%) of the variation in FR and N-AE. Soil pH, P-Olsen, silt content, and rainfall had significant but low levels of power in explaining variation in FR and N-AE. Our findings indicate that strategies to refine fertilizer recommendation should include information on soil types and soil properties.
| S-EPMC7357725 | biostudies-literature
Project description:The impacts of rhizobium inoculation on growth and yield of chickpea have mainly been tested in experiments conducted in greenhouses or on research stations. We report the response of the crop to inoculation (I) and phosphorus fertilizer (P) application across a large number of smallholder's farms over four regions of Ethiopia, covering diverse soil fertility and agro-ecological conditions. Increased grain yields due to the soil fertility treatments was evident for 99% target farmers. On average, I and P increased grain yield by 21% and 25% respectively, while the combined application of I and P resulted in a 38% increase. However, observed grain yields on control plots and responses to the treatments on individual farms varied greatly, and relative yield responses (%; yield of P and/I minus control yield, divided by control yield) ranged from 3% to 138%. With the exception of a few extremely poorly yielding locations, average responses to P and I were high across a wide range of control yields, indicating the possibility of boosting chickpea productivity for smallholders with P fertilizer and inoculant technology. Variation in response to rhizobium inoculation was mostly independent of agro-ecology and soil type although it was found to be low on a number of farms with extremely high N contents (%). Assuming that a relative yield increase of 10% due to treatment effects is required to be visible, 71%, 73% and 92% of the farmers observed a yield benefit by applying P, I, and P?+?I, respectively. The results are discussed with respect to the additive benefits of P fertilizers and rhizobial inoculation and their implications for wide scale promotion of inoculant technology to smallholders.
| S-EPMC5946702 | biostudies-literature
Project description:Calf morbidity and mortality are serious constraints in the success of dairy calf production. Thus, the current study was carried out with the objective to estimate the incidence of calf morbidity and mortality and associated risk factors in milk-shed districts of Gamo Zone, Southern Ethiopia. A prospective cohort and cross-sectional survey were employed from November 2019 to April 2020. A total of 196 calves were recruited by simple random sampling. Recruitment of calves was deployed by both the concurrent and prospective cohorts in calves aged below three months in study herds. The crude incidence of calf morbidity and mortality was 30.9% and 8.64%, respectively. The most frequently encountered disorder was calf diarrhea (10.17%), followed by pneumonia (6.5%). The other disorders were septicemia, omphalitis, arthritis, eye problem and miscellaneous cases. Multivariable Cox regression was revealed significant association for the calf vigor status, colostrum ingestion time, colostrum feeding status, dam parity, age at first calving, and related disorders were found risk factors of calf morbidity; likewise, calf vigor status at birth, time of colostrum ingestion and weaning were risk factors determining calf mortality. Calf morbidity and mortality rates recorded in this study were marginally higher than economically tolerable level, therefore, could affect the productivity of smallholder dairying by decreasing the obtainability of replacement heifers. Among significant explanatory factors investigated, colostrum ingestion time, method and amount were found important determinant factors of calf mortality and morbidity under the small-holder farming in the milk-shed districts of the Gamo zone. Therefore, rigorous calf husbandry practice is a need to manipulate the aforementioned calf determinants with subsequent application of tailor-made interventions.
| S-EPMC8445444 | biostudies-literature
Project description:The present study examined the livestock feed balance of smallholder farmers in Tanqua-Abergelle district of central Tigray, northern Ethiopia. Sixty livestock households were randomly selected from two farmer associations chosen systematically based on their livestock production potential. Data were collected on household characteristics, land holding, livestock ownership, feed inventory, feed supply and feed demand using household interviews (N = 60). Field feed samples were collected and representative samples analysed for dry matter content (DM), metabolizable energy (ME) and digestible crude protein (DCP). Annual DM, ME and DCP supply and demand were estimated using proper scientific procedures. Feed balance was quantified by comparing the feed demand with the supply. Data were analysed using descriptive statistics of SPSS statistical software. Crop residues, grazing lands, crop stubble and mixed hay were investigated as the major feed resources for livestock. On average, annual feed production was 3.96 tonnes DM, 30,138 MJ ME and 171 kg DCP at household level for 4.85 TLU. Crop residues contributed to 52 % of the total annual feed supply and grazing lands to 29 %. The feed requirement for maintenance of the livestock holding was estimated at 11.06 tonnes DM, 45,580 MJ ME and 253 kg DCP. The feed balance analysis estimated a 64 % deficiency of dry matter, 34 % of ME and 32 % of protein. Based on the present findings, it is clear that either the quantitative and qualitative feed supply of the livestock must be improved or the number of livestock kept in Tanqua-Abergelle district must be reduced in order to close the feed gap.
| S-EPMC10694160 | biostudies-literature
Project description:Despite the importance of naturally available wild pollination ecosystem services in enhancing sub-Saharan African smallholder farms' productivity, their values to actual farming systems remain unknown. We develop a nationally representative empirical assessment by integrating nationally representative plot level panel data with spatially and temporally matched land cover maps to identify the contribution of wild pollinators to crop revenue. Our estimation results reveal distinct and robust contributions by natural habitats of wild pollinators - forests - to plot-level crop revenue, where habitats in near proximity to plots contribute much more value than those farther away. When contrasting between pollinator-dependent and pollinator-independent crops, we find that the positive effects emerge only for pollinator-dependent crops, while pollinator-independent crops show no benefits. We conclude the empirical assessment by using our estimates to evaluate changes in crop revenue associated with the actual habitat reduction during 2008-2013. We find that this change in the natural habitats of wild pollinators has reduced crop revenue possibly by as much as 29% (mean) and 4% (median). To our knowledge, this is the first empirical assessment to use nationally representative smallholder farms to assess the value of naturally available wild pollination ecosystem services. Our results magnify the documented benefits of forest conservation, as this preserves pollinators' natural habitats, and by extension its inhabitants, who play an important role in boosting crop yields of nature dependent smallholder farms.
| S-EPMC6401091 | biostudies-literature
Project description:Crop yield prediction provides information to policymakers in the agricultural production system. This study used leaf reflectance from a spectroradiometer to model grain yield (GY) and aboveground biomass yield (ABY) of maize (Zea mays L.) at Aba Gerima catchment, Ethiopia. A FieldSpec IV (350–2,500 nm wavelengths) spectroradiometer was used to estimate the spectral reflectance of crop leaves during the grain-filling phase. The spectral vegetation indices, such as enhanced vegetation index (EVI), normalized difference VI (NDVI), green NDVI (GNDVI), soil adjusted VI, red NDVI, and simple ratio were deduced from the spectral reflectance. We used regression analyses to identify and predict GY and ABY at the catchment level. The coefficient of determination (R2), the root mean square error (RMSE), and relative importance (RI) were used for evaluating model performance. The findings revealed that the best-fitting curve was obtained between GY and NDVI (R2 = 0.70; RMSE = 0.065; P < 0.0001; RI = 0.19), followed by EVI (R2 = 0.65; RMSE = 0.024; RI = 0.61; P < 0.0001). While the best-fitting curve was obtained between ABY and GNDVI (R2 = 0.71; RI = 0.24; P < 0.0001), followed by NDVI (R2 = 0.77; RI = 0.17; P < 0.0001). The highest GY (7.18 ton/ha) and ABY (18.71 ton/ha) of maize were recorded at a soil bunded plot on a gentle slope. Combined spectral indices were also employed to predict GY with R2 (0.83) and RMSE (0.24) and ABY with R2 (0.78) and RMSE (0.12). Thus, the maize’s GY and ABY can be predicted with acceptable accuracy using spectral reflectance indices derived from spectroradiometer in an area like the Aba Gerima catchment. An estimation model of crop yields could help policy-makers in identifying yield-limiting factors and achieve decisive actions to get better crop yields and food security for Ethiopia.
| S-EPMC9202864 | biostudies-literature
Project description:Conservation agriculture (CA) practices are being widely promoted in many areas in sub-Saharan Africa to recuperate degraded soils and improve ecosystem services. This study examined the effects of three tillage practices [conventional moldboard plowing (CT), hand hoeing (MT) and no-tillage (NT)], and three cropping systems (continuous maize, soybean-maize annual rotation, and soybean/maize intercropping) on soil quality, crop productivity, and profitability in researcher and farmer managed on-farm trials from 2010 to 2013 in northwestern Ghana. In the researcher managed mother trial, the CA practices of NT, residue retention and crop rotation/intercropping maintained higher soil organic carbon, and total soil N compared to conventional tillage practices after 4 years. Soil bulk density was higher under NT than under CT soils in the researcher managed mother trails or farmers managed baby trials after 4 years. In the researcher managed mother trial, there was no significant difference between tillage systems or cropping systems in maize or soybean yields in the first three seasons. In the fourth season, crop rotation had the greatest impact on maize yields with CT maize following soybean increasing yields by 41 and 49% compared to MT and NT maize, respectively. In the farmers' managed trials, maize yield ranged from 520 to 2700 kg ha-1 and 300 to 2000 kg ha-1 for CT and NT, respectively, reflecting differences in experience of farmers with NT. Averaged across farmers, CT cropping systems increased maize and soybean yield ranging from 23 to 39% compared with NT cropping systems. Partial budget analysis showed that the cost of producing maize or soybean is 20-29% cheaper with NT systems and gives higher returns to labor compared to CT practice. Benefit-to-cost ratios also show that NT cropping systems are more profitable than CT systems. We conclude that with time, implementation of CA practices involving NT, crop rotation, intercropping of maize and soybean along with crop residue retention presents a win-win scenario due to improved crop yield, increased economic return, and trends of increasing soil fertility. The biggest challenge, however, remains with producing enough biomass and retaining same on the field.
| S-EPMC5478712 | biostudies-literature
Project description:Organic matter inputs positively affect soil fertility and quality but management effects on the soil and plant microbiome are less understood. Therefore, we studied the response of microbial colonization of the East African highland banana cultivar "Mpologoma" (AAA genome) under different mulch and manure treatments on three representative smallholder farms in Uganda. In general, the gammaproteobacterial community appeared stable with no significant response to organic matter inputs after 24 months of treatment. Significant differences (p < 0.05) in the plant-associated carpo-, phyllo-, and rhizosphere microbial community composition and diversity were found among individual sampled farms, independent of added soil inputs. Across farms, banana fruit harbored a richer and more balanced gammaproteobacterial community than the rhizo- and endospheres. Gammaproteobacterial beta diversity was shaped by the microenvironment (44%) as well as the sampling site (4%). Global effects of treatments in the rhizosphere analyzed using linear discriminant analysis effect size showed significantly enriched genera, such as Enterobacter, under manure and mulch treatments. As shown in previous works, bunch size and total yield were highly increased with manure and mulch, however, our results highlight general short-term microbial stability of Ugandan banana cropping systems with increases in the gammaproteobacterial community.
| S-EPMC8847376 | biostudies-literature