Agriculture and bioactives: achieving both crop yield and phytochemicals.
Ontology highlight
ABSTRACT:
SUBMITTER: Garcia-Mier L
PROVIDER: S-EPMC3588095 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Therefore, remote sensing and GIS techniques were employed, in this study, to predict potato tuber crop yield on three 30 ha center pivot irrigated fields in an agricultural scheme located in the Eastern Region of Saudi Arabia. Landsat-8 and Sentinel-2 satellite images were acquired during the potato growth stages and two vegetation indices (the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI)) were generated from the images. Vegetation index maps were developed and classified into zones based on vegetation health statements, where the stratified random sampling points were accordingly initiated. Potato yield samples were collected 2-3 days prior to the harvest time and were correlated to the adjacent NDVI and SAVI, where yield prediction algorithms were developed and used to generate prediction yield maps. Results of the study revealed that the difference between predicted yield values and actual ones (prediction error) ranged between 7.9 and 13.5% for Landsat-8 images and between 3.8 and 10.2% for Sentinel-2 images. The relationship between actual and predicted yield values produced R2 values ranging between 0.39 and 0.65 for Landsat-8 images and between 0.47 and 0.65 for Sentinel-2 images. Results of this study revealed a considerable variation in field productivity across the three fields, where high-yield areas produced an average yield of above 40 t ha-1; while, the low-yield areas produced, on the average, less than 21 t ha-1. Identifying such great variation in field productivity will assist farmers and decision makers in managing their practices.
| S-EPMC5017787 | 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:Urban agriculture is making an increasing contribution to food security in large cities around the world. The potential contribution of biodiversity to ecological intensification in urban agricultural systems has not been investigated. We present monitoring data collected from rice fields in 34 community farms in mega-urban Shanghai, China, from 2001 to 2015, and show that the presence of a border crop of soybeans and neighboring crops (maize, eggplant and Chinese cabbage), both without weed control, increased invertebrate predator abundance, decreased the abundance of pests and dependence on insecticides, and increased grain yield and economic profits. Two 2 year randomized experiments with the low and high diversity practices in the same locations confirmed these results. Our study shows that diversifying farming practices can make an important contribution to ecological intensification and the sustainable use of associated ecosystem services in an urban ecosystem.
| S-EPMC5967864 | 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:Climate models predict increasing weather variability, with negative consequences for crop production. Conservation agriculture (CA) may enhance climate resilience by generating certain soil improvements. However, the rate at which these improvements accrue is unclear, and some evidence suggests CA can lower yields relative to conventional systems unless all three CA elements are implemented: reduced tillage, sustained soil cover, and crop rotational diversity. These cost-benefit issues are important considerations for potential adopters of CA. Given that CA can be implemented across a wide variety of regions and cropping systems, more detailed and mechanistic understanding is required on whether and how regionally-adapted CA can improve soil properties while minimizing potential negative crop yield impacts. Across four US states, we assessed short-term impacts of regionally-adapted CA systems on soil properties and explored linkages with maize and soybean yield stability. Structural equation modeling revealed increases in soil organic matter generated by cover cropping increased soil cation exchange capacity, which improved soybean yield stability. Cover cropping also enhanced maize minimum yield potential. Our results demonstrate individual CA elements can deliver rapid improvements in soil properties associated with crop yield stability, suggesting that regionally-adapted CA may play an important role in developing high-yielding, climate-resilient agricultural systems.
| S-EPMC5981580 | biostudies-literature
Project description:Best management practices (BMPs) are commonly used to reduce sediment loadings. In this study, we modeled the Fort Cobb Reservoir watershed located in southwestern Oklahoma, USA using the Soil and Water Assessment Tool (SWAT) and evaluated the impacts of five agricultural BMP scenarios on surface runoff, sediment yield, and crop yield. The hydrological model, with 43 sub-basins and 15,217 hydrological response units, was calibrated (1991-2000) and validated (2001-2010) against the monthly observations of streamflow, sediment grab samples, and crop-yields. The coefficient of determination (R 2), Nash-Sutcliffe efficiency (NS) and percentage bias (PB) were used to determine model performance with satisfactory values of R 2 (0.64 and 0.79) and NS (0.61 and 0.62) in the calibration and validation period respectively for streamflow. We found that contouring practice reduced surface runoff by more than 18% in both conservation tillage and no-till practices for all crops used in this modeling study. In addition, contour farming with either conservation tillage or no-till practice reduced sediment yield by almost half. Compared to the conservation tillage practice, no-till practice decreased sediment yield by 25.3% and 9.0% for cotton and grain sorghum, respectively. Using wheat as cover crop for grain sorghum generated the lowest runoff followed by its rotation with canola and cotton regardless of contouring. Converting all the crops in the watershed into Bermuda grass resulted in significant reduction in sediment yield (72.5-96.3%) and surface runoff (6.8-38.5%). The model can be used to provide useful information for stakeholders to prioritize ecologically sound and feasible BMPs at fields that are capable of reducing sediment yield while increasing crop yield.
| S-EPMC6612418 | biostudies-literature
Project description:Most business-as-usual scenarios for farming under changing climate regimes project that the agriculture sector will be significantly impacted from increased temperatures and shifting precipitation patterns. Perhaps ironically, agricultural production contributes substantially to the problem with yearly greenhouse gas (GHG) emissions of about 11% of total anthropogenic GHG emissions, not including land use change. It is partly because of this tension that Climate Smart Agriculture (CSA) has attracted interest given its promise to increase agricultural productivity under a changing climate while reducing emissions. Considerable resources have been mobilized to promote CSA globally even though the potential effects of its widespread adoption have not yet been studied. Here we show that a subset of agronomic practices that are often included under the rubric of CSA can contribute to increasing agricultural production under unfavorable climate regimes while contributing to the reduction of GHG. However, for CSA to make a significant impact important investments and coordination are required and its principles must be implemented widely across the entire sector.
| S-EPMC7190105 | biostudies-literature
Project description:Although food crop yields per hectare have generally been increasing in Cameroon since 1961, the food price crisis of 2008 and the ensuing social unrest and fatalities raised concerns about the country's ability to meet the food needs of its population. This study examines the country's potential for increasing crop yields and food production to meet this food security challenge. Fuzzy set theory is used to develop a biophysical spatial suitability model for different crops, which in turn is employed to ascertain whether crop production is carried out in biophysically suited areas. We use linear regression to examine the trend of yield development over the last half century. On the basis of yield data from experimental stations and farmers' fields we assess the yield gap for major food crops. We find that yields have generally been increasing over the last half century and that agricultural policies can have significant effects on them. To a large extent, food crops are cultivated in areas that are biophysically suited for their cultivation, meaning that the yield gap is not a problem of biophysical suitability. Notwithstanding, there are significantly large yield gaps between actual yields on farmers' farms and maximum attainable yields from research stations. We conclude that agronomy and policies are likely to be the reasons for these large yield gaps. A key challenge to be addressed in closing the yield gaps is that of replenishing and properly managing soil nutrients.
| S-EPMC3906480 | biostudies-literature
Project description:Since its origins, thousands of years ago, agriculture has been challenged by the presence of evolving plant pathogens. Temporal rotations of host and non-host crops have helped farmers to control epidemics among other utilities, but further efforts for strategy assessment are needed. Here, we present a methodology for developing crop rotation strategies optimal for control of pathogens informed by numerical simulations of eco-evolutionary dynamics in one field. This approach can integrate agronomic criteria used in crop rotations-soil quality and cash yield-and the analysis of pathogen evolution in systems where hosts are artificially selected. Our analysis shows which rotation patterns perform better in maximising crop yield when an unspecified infection occurs, with yield being dependent on both soil quality and the strength of the epidemic. Importantly, the use of non-host crops, which both improve soil quality and control the epidemic results in similar rational rotation strategies for diverse agronomic and infection conditions. We test the repeatability of the best rotation patterns over multiple decades, an essential end-user goal. Our results provide sustainable strategies for optimal resource investment for increased food production and lead to further insights into the minimisation of pesticide use in a society demanding ever more efficient agriculture.
| S-EPMC6964815 | biostudies-literature
Project description:The appearance of agriculture in the Fertile Crescent propelled the development of Western civilization. Here we investigate the evolution of agronomic conditions in this region by reconstructing cereal kernel weight and using stable carbon and nitrogen isotope signatures of kernels and charcoal from a set of 11 Upper Mesopotamia archaeological sites, with chronologies spanning from the onset of agriculture to the turn of the era. We show that water availability for crops, inferred from carbon isotope discrimination (?(13)C), was two- to fourfold higher in the past than at present, with a maximum between 10,000 and 8,000 cal BP. Nitrogen isotope composition (?(15)N) decreased over time, which suggests cultivation occurring under gradually less-fertile soil conditions. Domesticated cereals showed a progressive increase in kernel weight over several millennia following domestication. Our results provide a first comprehensive view of agricultural evolution in the Near East inferred directly from archaeobotanical remains.
| S-EPMC4046107 | biostudies-literature