Agricultural Research最新文献

The main obstacles to rice cultivation in Egypt and the world are lack of irrigation water and elevated temperatures, because rice production is extremely sensitive to water shortage; there is a need for the evolution of genotypes that are tolerant to drought. To this achieved, 21 F1 hybrids developed from seven parental genotypes using half diallel mating design and assessed under normal and water stress at Sakha Agricultural Research Station, Kafr El-Sheikh, Egypt. The grain yield and most traits significantly differ (p < 0.01) between genotypes and their partition; parents, crosses, and their interaction as well general combining ability (GCA) and specific combining ability (SCA). Water stress significantly reduced grain yield and all traits in parents and hybrids compared to normal conditions. Also, most parents and hybrids significantly favor GCA and SCA effects for grain yield and all traits, respectively. Best mean performances, stress tolerance index (STI) and desirable GCA effects are noticed by SaKha108, Giza179. Based on principal component analysis (PCA), these parents can be used for generating superior rice hybrids under water stress. The hybrid combinations Giza177 × Azucena, Sakha108 × Azucena and Giza179 × Azucena discovered to be good specific combiners for grain yield and majority traits under water stress. For all traits, there were strong correlations among F1 hybrids’ performance, SCA and heterosis estimations. The above genotypes and these traits correlated could be exploited for improving rice grain yield and drought tolerance in future breeding programs.

Technology adoption requires technical information to support decision-making and encourage broader acceptance. Recognizing the significance of alternate wetting and drying technology in sustainable agriculture, this study aims to promote the adoption of this technology among both Good Agricultural Practices (GAP) and non-GAP farmers in Suburban, Bangkok, Thailand. Data were collected through a structured questionnaire, which gathered information on farmers' cost and return values, as well as their adoption opinions. The collected data were then analyzed using cost and return analysis, as well as stochastic frontier analysis. The results indicate that non-GAP farmers face significantly higher total costs due to increased fixed costs compared to GAP farmers. While there were no significant differences in yield between the two groups, GAP farmers achieved significantly higher total income and net profit due to lower total costs and higher selling prices. Furthermore, the analysis suggests that both groups of rice farmers have the potential to improve their efficiency levels, with non-GAP farmers showing a higher potential for improvement. In terms of adoption opinion, both farmer groups recognize the advantages of wet and dry farming technology over traditional flooded rice farming. This study highlights that the adoption levels of both GAP and non-GAP farmers can be significantly improved through the implementation of best management practices. Overall, the findings emphasize the importance of trustworthy information dissemination to encourage the adoption of wet and dry farming technology, as it enhances farmers' trust in the received information and their engagement with the technology. The study concludes by providing policy implications and recommendations to promote the wider adoption of wet and dry farming technology.

Chemical ripening is a promising technology at Metahara and Kessem sugarcane plantations where conditions are not optimal for natural ripening in the early and late period of sugarcane processing. However, the harvest age at which sucrose yield could be maximized with application of ripeners has not been established. Thus, field experiments were conducted to determine the effects of harvest age and chemical ripeners on yield and juice quality of sugarcane. The experiments were conducted in the late period (June) harvesting at Metahara, and in the early (October) and late period (June) harvesting at Kessem. A split plot design with three replications was used where the main plot treatments were two sugarcane varieties, viz. B52-298 and SP70-1284, and the sub-plot treatment consisted of combinations of four harvest ages (10, 12, 14 and 16 months) and two ripener treatments [Moddus™ at 250 g ai ha⁻¹ + Fusilade Forte™ (M + FF) at 25.6 g ai ha⁻¹ combination sequentially sprayed and unsprayed control]. The results showed significant difference between the varieties for stalk height and stalk weight in early period study at Kessem with variety SP70-1284 being superior as compared to variety B52-298. Furthermore, harvest age and ripener combination significantly affected all yield and quality parameters, while there was a significant cane and sucrose yield response at Kessem at both sites and seasons. The highest cane yield was recorded in the unsprayed 16-month harvest age treatment, while the highest sucrose yield was recorded in the M + FF ripener combination 12-month harvest age treatment in all the studies. The economic analysis showed the highest marginal rate of return and net revenue in the M + FF ripener combination 12-month harvest age treatment and represents the best cane quality management practice for varieties B52-298 and SP70-1284 at these plantations.

Over the years there was a shift in consumer preferences toward specialty rice due to health consciousness and lifestyle. Took initiatives, four types of fragrant rice known as MRQ 50, MRQ 74, MRQ 76 and MRQ 88 then were developed by the Malaysian Agricultural Research and Development Institute (MARDI) with different characteristics. For example, MRQ 88 was an aromatic, long and slender shape with non-sticky Basmati features while other varieties were characterized by sticky, soft and aromatic which is similar to the existing fragrant rice in the market. Therefore, the study attempts to explore the specific characteristics of fragrant rice that influence the consumer’s purchasing decision. A face-to-face survey was conducted involving 774 respondents in Peninsular Malaysia, Sabah and Sarawak using a structured questionnaire with selected criteria of respondents. Conditional logit (CL) in Choice Experiment (CE) analysis was then conducted. The results showed the choice of attributes that were significant at a 1% level were softness (moderate and very soft), aromatic, and non-stickiness stated at the moderate level of preference. These factors were identified to influence consumers’ choice of preferences in purchasing fragrant rice. The highest level of softness showed the most important attribute that influenced the willingness to pay followed by the attribute of moderate aroma. However, the attribute of non-stickiness/moderate flakiness shows a relatively low value of willingness to pay. Hence, the development of fragrant rice characteristics should consider the highest level of softness with a moderate level of aroma and non-stickiness as a priority. It will be the main reference of rice attributes for more specific profile characteristics in developing the market potential of specialty rice in the future.

Bitter fennel (Foeniculum vulgare var. Vulgare), hereafter just called fennel, is an open-pollinated plant, and controlling pollination can be very difficult. Most fennel growers are reliant on local landraces, as there is no commercial cultivar. Here, we developed five fennel synthetic cultivars with different maturity habits, three with the goal of high essential oil yield, and the other two with the goal of high seed yield in drought. For each of the five synthetic cultivars, elite parents based on General combining ability (GCA) for either essential oil yield or seed yield in drought conditions were selected, and allowed to freely cross-pollinate. After developing the first generation of synthetic cultivars, their performances were evaluated against some of their elite parents under both well-irrigated and drought conditions. Altogether, the five synthetic cultivars had higher essential oil yield and seed yield than their parents in drought stress, although SynEMOY (16.5 l/ha, 848.3 kg/ha) and SynEMSY (20 l/ha, 562.9 kg/ha) were more promising. In well-irrigated conditions, SynMMOY gave the highest essential oil yield (49.94 l/ha) and seed yield (2357.1 kg/ha), and performances of the synthetic cultivars were like their elite parents. Our result here showed synthetic cultivar has the potential to be an efficient, reliable, and sustainable breeding method to develop high-yielding and drought-tolerant fennel cultivars, especially for early and medium maturities.

Understanding the trends in crop diversity in context of changing socioeconomic and climatic factors are essential for implementing sustainable agricultural practices. The Shannon Index was adopted to calculate crop diversity across all districts of India from 2001 to 2021. High-resolution Standardized Precipitation Eevapotranspiration Index (SPEI) data was developed using the Climate Hazards Group InfraRed Precipitation (CHIRPS) and Global Land Evaporation Amsterdam Model's (GLEAM) data to capture climate variability. A panel regression was employed using ordinary least squares, fixed effects, and random effects models. Crop diversity in India experiences an increase of 2.6% between 2001 and 2021. During the study period, India experienced an increase in the proportion of land dedicated to non-food crops, rising from 19.79% to 22.80%. The area allocated to cereal and millet crops experienced a decline, decreasing from 54.51% to 50.61%. SPEI is a significant factor in diversified agriculture, showing a negative association. Higher urbanization, road density, number of markets, the presence of organic carbon in the soil, improved seeds, fertilizers, and credit facilities for farmers reduce crop diversity. Access to irrigation increases the likelihood of practicing in diversified crop. Increasing education level of farmers positively influences the practice of crop diversity in India. Farmers in droughtprone areas of India often adopted diversified cropping practices.

This experimental study was conducted to augment farm productivity and possibly reduce the interface of farmers and pesticides. The pilot study explored scalable and sustainable agricultural techniques by an adoption of specific precision agriculture features which can improve the hunger-index of tribal families whose livelihoods are farming of arid lands. The study engineered, executed and evaluated the field experiment and gathered data (time series) associated to two water intensive crops Paddy and Cotton in the Kharif Season over one crop cycle (6 months) spanning 108 square kilometers of hostile and arid tribal land by the deployment of an Artificial Intelligence (AI) powered Unmanned Arial Vehicle (UAV). This calibrated UAV performed automated optical sensing and intelligent planning options apart from data collection which was subjected to 3D spectral analysis and derive functions of Leaf Area Index Curve Fit Models, Logistic and S-Curve functions. The schematics embedded in the UAV were re-designed and iterated to obtain ordinal data that was classified into hyperspectral information by way of a k-means algorithm to function as a text stream cluster based on adaptive feature selection. The study endorsed that Object Based Image Analysis with algorithms of AI asymptotically can derive yields that was previously thought of as impossible. The study also reinforces that conjoining UAV technology and transportation science can address challenges across the commercial spectrum in an analytical and portable pattern by looping the routing and scheduling path (fixed interval repetition) of UAV’s which is of paramount importance and unique to this current study.

Knowledge about the critical production components and the key loss factors is essential for adequately managing the Common beans crop. Therefore, this study aimed to identify and quantify the losses in the production components, determining the critical components and key loss factors for three growing seasons and two planting systems and associating the loss factor in the production components with the relative abundance of insect pests on the Common beans crop. The planting system did not influence losses and productivity. Note that the lowest yields and highest losses were found in spring–summer. The critical production component was a flower for the winter–spring, spring–summer and summer–autumn seasons and ovules for the spring–summer period. Flower abortion was the key loss factor for the critical flower component, and ovule poor formation was the key loss factor for the critical ovule component.

Bombyx mori bidensovirus (BmBDV) causes “Flacherie” disease leading to significant economic loss to sericulture industry. Resistance to BmBDV is controlled by the recessive gene, nsd-2 (non-susceptible to DNV-2). Consequently, screening and development of silkworm breeds for BmBDV resistance by artificial inoculation may not work as the nsd-2 resistant allele is in heterozygous condition. Deletion in nsd-2 gene is associated with the BmBDV resistance and hence can be used as a molecular marker. Silkworm breeds with nsd-2 resistant allele in heterozygous condition can be identified and selectively bred through marker assisted breeding. In the present study, twenty productive bivoltine breeds popular among the breeders for development of hybrids for tropical climatic conditions of West Bengal & Northeast region of India were screened to detect the presence of nsd-2 resistant allele. Out of twenty breeds, ten revealed the presence of nsd-2 resistant allele in heterozygous condition. Among the breeds which carried the nsd-2 resistant allele, SK6 and SK7, popular parental silkworm breeds of ruling hybrid for Northeast India were made homozygous for the nsd-2 resistant allele through marker assisted selection and were observed to be resistant to BmBDV infection and designated as SK6R and SK7R. The improved breeds SK6R and SK7R were further crossed to develop hybrids and these hybrids were also resistant to BmBDV infection retaining all the economic traits. The SK6R and SK7R breeds and their hybrids can be utilized for commercial silkworm seed production. This study also demonstrates utility of molecular marker, nsd-2 as a complementary tool to develop breeds and hybrids resistant to BmBDV infection.

Understanding the genetic and environmental causes of genotype-by-environment (GE) interaction for grain yield is of fundamental importance in plant breeding. This study aimed at investigating the GE interaction and the stability of durum wheat (Tritium turgidum L. ssp. durum) genotypes evaluated for grain yield across different locations and years, using empirical and analytical models. The study used 19 genotypes in 14 environments, representative of rainfed durum wheat-growing areas. The genotype main effect plus GE interaction (GGE) biplot model, partial least squares regression and factorial regression models were applied for data analysis. The combined ANOVA revealed significant genotype, environment and GE interaction effects, with the environmental main effect as a main source of variation (77.9% of total variation). The mean yield of the genotypes ranged from 486 to 5594 kg/ha across environments. Using GGE biplot analysis, the test environments were classified into four groups, each with different winning genotypes. Based on mean yield and stability performance across environments, breeding lines G17 and G15 significantly out-yielded the best national check and could be recommended for release as new varieties. Rainfalls in March, June, November and May, average temperatures in June and May, heading date and 1000-kernel weight were among the explanatory covariates that significantly (P < 0.01) affected the GE interaction for grain yield.