Validation of CERES-Rice v3.5 under the climate of Andhra Pradesh state, India

Crop growth simulation models, properly validated against experimental data have the potential for tactical and strategic decision making in agriculture. Such validated models can also take the information generated through site specific experiments and trials to other sites and years. For proper calibration and evaluation of crop simulation models, there is a need for collection of a comprehensive minimum set of data on soil, weather and crop management in all agronomic experiments. Keeping this in view, field experiments were conducted at Rajendranagar (17°19' N, 78°23' E; 542.3 m amsl) during 1994-97 for three popular varieties of rice viz. Sambamasuri, Rajavadlu and Tellahamsa under irrigated conditions and data collected. Genetic coefficients required for running the CERES-Rice v3.5 model were calculated and the performance of the model under the climate of the area was evaluated. The results of the study show that the model simulations of date of flowering for Sambamasuri, Rajavadlu and Tellahamsa were within an average error of 6.2, 5.7 and 6.7 days respectively. Similar errors in predictions of physiological maturity dates were 7.6, 6.7 and 7.2 days. The error in grain yield predictions by the model averaged at 7.9%, 8.3%, and 5.7% respectively for the three crop varieties. These results indicate that the CERES Rice v3.5 model is capable of prediction of grain yield and phenological development of the crop in the climatic conditions of Andhra Pradesh with reasonable accuracy and hence, the model have the potential for its use as a tool in making various strategic and tactical decisions related to agricultural planning in the state.

Novel MicroRNAs and Their Functional Targets from Phytophthora infestans and Phytophthora cinnamomi

Background: Even though miRNAs play viral roles in developmental biology by regulating the translation of mRNAs, they are poorly studied in oomycetes, especially in plant pathogen Phytophthora. Objective: The study was aimed to predict and identify the putative miRNAs and their targets in Phytophthora infestans and Phytophthora cinnamomi. Methods: Homology based comparative method was used to identify the unique miRNA sequences in P. infestans and P. cinnamomi with 148,689 EST and TSA sequences of these species. Secondary structure prediction of sRNAs for the 76 resultant sequences has been performed with MFOLD tool and their targets were predicted using psRNAtarget. Result: Novel miRNAs, miR-8210 and miR-4968 were predicted from P. infestans and P. cinnamomi, respectively along with their structural features. The newly identified miRNAs were identified to play important roles in gene regulation, with few of their target genes predicted as transcription factors, tumor suppressor genes, stress responsive genes, DNA repairing genes etc. Conclusion: The miRNAs and their targets identified have opened new interference and editing targets for the development of Phytophthora resistant crop varieties.

Uptake of Climate Smart Agriculture in Peri-Urban Areas of South Africa's Economic Hub Requires Up-Scaling

Climate variability and change impact significantly on food security and the livelihoods of smallholder farmers making it necessary for the farmers to prioritize investment in adaptation and mitigation approaches, such as climate smart agriculture, to enhance resilience. Climate smart agriculture approaches have been adopted in many countries around the world to address the adverse impacts of climate change on agricultural production. There is limited information about climate smart agriculture adoption by peri-urban farmers in developing countries. The present study aimed to assess the extent to which agricultural activities by smallholder crop farmers in the City of Tshwane Metropolitan Municipality in Gauteng province of South Africa are climate smart, and to establish the sustainable measures to be put in place to enhance the adoption of climate smart agriculture. The study made use of a mixed method design combining qualitative and quantitative approaches. A combination of simple random and non-probability sampling techniques was employed to select the study locations and identify respondents. A sample of thirty-six farmers were selected for the study. The main findings revealed overwhelming awareness of climate change and the impacts thereof on crop productivity and yields. However, the respondents' level of awareness of climate smart agriculture technologies was generally low. Despite the lack of knowledge of climate smart agriculture practices, the farmers were, to an extent, utilizing adaptation mechanisms acquired from indigenous systems or scientific knowledge. Examples of these practices include mulching, cover cropping, crop rotation and use of crop varieties. The study concludes that much more can be done to scale up the uptake of climate smart agriculture in the Gauteng province. The study recommends formal and informal strategies including one-on-one extension programs to raise the awareness of climate smart agriculture technologies appropriate to the unique conditions of the farmers.

Estimation of genetic erosion on Ethiopian tetraploid wheat landraces using different approaches

The demand and use of improved crop varieties by farmers has increased in the central highlands of Ethiopia, where continuous loss of local traditional varieties has been occurring in the last two to three decades. The objectives of the study were to assess the extent of genetic erosion and perception of farmers and associated causes for the reduction of traditional farmers' varieties. Direct field assessment covering 56 wheat farms and a survey in which 149 farmers participated were carried out in three districts of central Ethiopia. Based on data collected during direct farm assessment, the loss of genotypes was found to be 88% in Ada followed by 80% and 60% in Lume and Gimbichu districts, respectively. The farmer survey indicated an even greater loss of diversity of100% in Ada followed by Lume (93%) and Gimbichu (67%). Diseases and pests as well as shorter growing seasons associated with climate change were identified as main causes for farmers to switch to modern varieties. The expansion of high yielding improved bread and durum wheat varieties also contributed to gradually replace local durum wheat varieties by local farmers of these districts. Overall, genetic erosion of tetraploid wheat varied among the three districts of central Ethiopia. Reductions in the number of farmers and area coverage in the study districts could be used as good indicators for the existence of genetic erosion.

Prevalence and Distribution of Weed Flora in Some Major Sugarcane Growing Areas of Southern Guinea Savanna, Nigeria

Weed population survey was undertaken to determine prevalence and distribution of weeds, and asses weed flora shift in major sugarcane growing areas in Southern guinea savanna of Nigeria. The selected areas surveyed are namely Badeggi, Sulti, and Isenyi. The Sugarcane fields were assessed using 1.0 m x 1.0 m quadrat placed randomly at vegetative stage. Weed seedlings in each quadrat were clipped at the soil level and identified according to standards. Result revealed that a total of 38 weed species were recorded. Graminaea and compositae were most abundant and diversified families based on the number of species recorded. Individual weed species shows variation in their abundance, dominance and frequency. The most frequent weed species in the Sugarcane fields irrespective of the soil, climate and crop varieties were Hyptis suaveolens, Paspalum scrobiculata, Kyllinga squamulata, Dactylactenum aegypium and Cynadon dactylon and were considered as the most important species in the surveyed areas. From Similarity indices, variations were observed between locations. Accordingly, areas having similarity indices more than 60 % indicate similarities in weed community. Thus, when devising a weed control strategies same control option should be considered for the location that have similar weed flora and vise-versa.

Why farmers use so many different maize varieties in West Kenya

In this article we reflect on the discussions as to whether breeding and seed system development should proceed along its current well established route of developing varieties with a higher agricultural productivity or if the diversity of farmers, their contexts and rationales requires broader approaches. We make use of data from a recently held survey (2018) in West Kenya. The data show that some 80% of the households in the survey planted both local and hybrid maize varieties. The choices that people make about which variety to plant are many. Apart from rainfall, the availability of cash, the promise of a good yield, the presence of projects and programs and the culture of seed also influences these choices. We argue that an inclusive demand-oriented maize breeding and seed system needs to include a range of varieties and seed sources and to develop and support different delivery pathways to fit farmers’ diverse use of seeds and varieties. Our findings also indicate the need for more systematic study of the diversity of farmers’ rationales and the performance of crop varieties. This would provide useful information for all the actors involved.

Mechanized Blueberry Harvesting: Preliminary Results in the Italian Context

This study reports some preliminary results on mechanical blueberry harvesting for the fresh market of cv. Cargo® in the Piedmont region (northwest Italy). The investigated area is one of the most productive areas of Italy, which specializes in fresh blueberry production. The automatization of harvesting operations could represent a competitive advantage for the area’s blueberry supply chain but could limit the quality of fresh-picked berries. A prototype machine and a commercial harvester (Easy Harvester®) were compared with manual picking, considering the harvesting efficiency, labor productivity, harvesting cost and farm rentability. In this context, the labor cost for manual harvesting exceeds EUR 2.00 per kg of saleable product. The prototype allowed a 39% cost reduction, and the Easy Harvester® reduced it by about half. Nevertheless, these positive performances do not consider the reduction in the net sale price of EUR 0.40 due to the selection costs in the warehouse. In this study, we highlight that the transition to mechanical harvesting requires the transformation of several farming and packhouse operations, such as new crop varieties, field configurations and cultivation techniques. However, a possible technical improvement of the Easy Harvester® could represent an opportunity for Italian farms in the planning of berry production and marketing, involving all of the supply chain actors. Further research on the use of mechanization in the sector must continue and be supported.

Using Crop Databases to Explore Phenotypes: From QTL to Candidate Genes

Seeds, especially those of certain grasses and legumes, provide the majority of the protein and carbohydrates for much of the world’s population. Therefore, improvements in seed quality and yield are important drivers for the development of new crop varieties to feed a growing population. Quantitative Trait Loci (QTL) have been identified for many biologically interesting and agronomically important traits, including many seed quality traits. QTL can help explain the genetic architecture of the traits and can also be used to incorporate traits into new crop cultivars during breeding. Despite the important contributions that QTL have made to basic studies and plant breeding, knowing the exact gene(s) conditioning each QTL would greatly improve our ability to study the underlying genetics, biochemistry and regulatory networks. The data sets needed for identifying these genes are increasingly available and often housed in species- or clade-specific genetics and genomics databases. In this demonstration, we present a generalized walkthrough of how such databases can be used in these studies using SoyBase, the USDA soybean Genetics and Genomics Database, as an example.

Utility and Triggers in Uptake of Agricultural Weather and Climate Information Services in Senegal, West Africa

Weather and climate information services (WCIS) are gaining recognition among scientists and governments as an essential adaptation tool for agriculture, especially in the drylands of Africa. In Senegal, the widespread production and dissemination of WCIS was initiated in 2015 to cover the agricultural, pastoral and fishing sectors. This paper analyzes the types of decisions made by WCIS users, their preferences and level of satisfaction, and explores the triggers of agricultural WCIS adoption. We collected data during the onset and cessation of the rainy seasons to understand the utility and reliability of WCIS by farmers across all stages of the growing season. Data were analyzed using descriptive statistics. A binary logistic regression was tested to understand the socio-economic triggers in uptake of WCIS. Results showed that rainfall forecast is the most preferred WCIS (49% of the respondents) followed by extreme wind forecast. At the beginning of the rainy season, nearly 80% of the respondents have chosen the sowing date and about 60% have chosen crop varieties based on disseminated WCIS. In the middle of the growing season, about 70% of the respondents used WCIS to decide on fertilizer application dates. Results also showed that age and level of education, being trained on WCIS use, membership to farmers’ organizations, owning a radio have a significant effect on WCIS-based decision-making. These factors are essential for triggering the uptake of WCIS, and therefore are required to improve the implementation of existing weather climate services in Africa.