Abstract Understanding factors intercepting response of rice farmers to climate change in Ebonyi State, Nigeria was investigated. A total of 70 rice farmers was sampled using multi-stage sampling technique and were administered with a questionnaire. Primary data was collected and were analyzed using descriptive statistics (mean, frequency, percentage, chart), and ordinary least square multiple regression model. Results shows that the rice farmers cultivated on small land holdings, relatively educated, sourced their land via inheritance and had 16 years of farming experience. Results reveals that 72% of the rice farmers are highly aware of climate change, while 17% and 11% are relatively aware and not aware respectively. Temperatures, rainfall, and number of rainy days have positive effects on rice production while sunshine hours and relative humidity had negative effects on rice production. Age, gender, education, farm size, extension contacts and participation in workshop were significant variables influencing rice production in the state. Capital, crude implements, pests and diseases, poor soil, lack of incentives and cultivation systems were the non-climatic factors that influenced rice cultivation in the state. Farmers were recommended to embrace climate smart cropping systems and seek for early climate change information to mitigate adverse effects of climate change on rice cultivation.

Abstract Automated intelligence platforms, i.e., machine learning, big data, and Internet of Things (IoT), provide new deployment opportunities within the agricultural marketing paradigm. This study attempts to derive a framework of predictive models to ameliorate crop yield and assists in understanding various features that affect crop yield. On the one hand, it investigates the impact of allied technologies, including networks with memory and generative models, and on the other, it quantitatively analyzes different agri-factors, including the management of plant growth, its quality, crop disease, inorganic fertilizer and pesticide deployment, weed management, irrigation, and field-level phenotyping. Further, the study analyzes the utilization of smart farming and the monitoring of highly dependent variables across the spectrum of precision agriculture. The conclusion is to manifest the importance of networks with memory and generative models and emphasize the vital role of artificial intelligence in transforming farm methods into a novel methodology of smart information communication technology (ICT) in fidelity agriculture. Apart from increased productivity, this study seeks to contribute to the ongoing efforts to reduce the incidence of malnutrition associated with limited access and lower production of food grains.

Abstract Mustard ( Brassica spp .) is a major oilseed crop and the world’s third largest source of vegetable oil. During the rabi season of 2022–2023, the experiment was carried out at the Regional Agricultural Research Station, Bangladesh Agricultural Research Institute (BARI), Barishal to evaluate the performance of 12 genotypes of Brassica rapa L., including the check variety BARI Sarisha-14. The experiment was conducted under randomized complete block design (RCBD) design with three replications. Analysis of variance demonstrated that a highly significant (p ≤ 0.01) differences for the traits viz., plant height, no. of primary branches, no. of secondary branches, and no. of seeds per siliqua whereas no. of siliqua per plant, 1000 seeds weight, yield kg per hectare had significant difference at p ≤ 0.05. Among the examined accessions, the unweighted pair group method with arithmetic mean (UPGMA) cluster analysis identified four different clusters. Cluster II (28.91%) with only one accession had the highest average yield, followed by Cluster I (26.25%) and Cluster IV (22.68%) with the best agronomic features. Furthermore, we observed 1.6% and 11.93% greater (+) mean yield compared to the grand mean yield (1502.33 kg ha −1 ) for cluster I and cluster II, respectively. Correlation analysis examine the positive and highly significant association among the yield with its related traits. Principal component analysis (PCA) revealed the total proportion of variation 54.86% for PC1 and 16.89% for PC2. The genotypes BC-100614(8)-7 gave 7.20% higher yield over the check variety. Considering the statistical results, maturity period, yield and yield contributing characters of Brassica rapa L. genotypes BC-100614(8)-7 (1681 kg ha −1 ), BC-100614(8)-1 (1594 kg ha −1 ) and BC-100614(7)-3 (1565 kg ha −1 ) were noted as promising lines among the evaluated genotypes and suggested for future breeding program.

Abstract Post-harvest spoilage of fruits and vegetables caused by fungal pathogens is a serious challenge to fruit production in many parts of the world. The study was conducted to evaluate the sensitivity of fungal pathogens associated with post-harvest rot of mango fruits to crude extracts from two edible plants, Allium sativum and Ocimum gratissimum , in the study area. Five different fungal isolates were isolated from diseased mango fruits collected from fruit stores in the study area and identified as Aspergillus spp. (M 1 ), Rhizopus spp. (M 2 ), Fusarium spp. (M 3 ), Penicillium spp. (M 4 ), Fusarium spp. (M 5 ), Penicillium spp. (M 6 ), Aspergillus spp. (M 7 ), and Colletotrichum spp. (M 8 ) using radial growth rate and morphological features of the mycelia. A constant concentration of each of the crude extracts was applied to the growth media containing the growing cultures of the fungal isolates. The radial extension of the colonies for each isolate was measured along pre-marked perpendicular axes on the base of the petri-dish after 24 h and this continued for 10–14 days. It was observed that Rhizopus spp., Fusarium spp., Penicillium spp ., and Colletotrichum spp. had the least growth rate when treated with the extracts.

Abstract This study evaluated the influence of waterlogging stress on the growth of six (6) accessions (TvSu-1, TvSu-2, TvSu-3, TvSu-4, TvSu-5, and TvSu-10) of Vigna subterranean in a pot experiment. The experiment was setup in a complete block design (CBD) with 3 replicates per treatment. Results of growth parameters of V. subterranean accessions under waterlogging stress such as; plant height, leaf area, petiole length, and number of nodes, were significantly ( p = 0.05) decreased when compared to their controls after 8 weeks of planting. For shoot length, TvSu-2 (1.60 ± 0.20 cm) and TvSu-4 (1.60 ± 0.20 cm) recorded the highest values while TvSu-5 (1.23 ± 0.03) and TvSu-10 (1.23 ± 0.03) had the lowest values respectively. TvSu-5 (19.03 ± 0.59 cm 2 ) and TvSu-10 (19.03 ± 0.59 cm 2 ) recorded the highest values in leaf area (LA), while TvSu-3 (14.40 ± 0.51 cm 2 ) had the lowest LA. For total photosynthetic pigment (TPP); TvSu-2, TvSu-4, TvSu-10 had the highest values with 57.35 ± 1.82 mg/kg, 55.80 ± 2.70 mg/kg, 55.77 ± 1.90 mg/kg respectively, TvSu-3 (41.50 ± 8.29 mg/kg) maintained the lowest value. In petiole length, TvSu-5 (15.23 ± 0.33 cm) and TvSu-4 (14.20 ± 0.66cm) had the highest values, while TvSu-3 (8.97 ± 0.33 cm) had the lowest. For number of nodes, TvSu-2 (15.00 ± 1.76) and TvSu-4 (12.00 ± 1.73) recorded the highest values, while TvSu-10 (10.00 ± 1.00) had the lowest value. Biomass yield analysis of the stressed V. subterranean showed that total fresh weight (TFW), root length (RL), root fresh weight (RFW), shoot fresh weight (SFW), leaf fresh weight (LFW), leaf turgid weight (LTW), total dry weight (TDW), root dry weight (RDW), shoot dry weight (SDW) and leaf dry weight (LDW) of the six accessions were significantly ( p = 0.05) decreased when compared to their control. Tvsu-5 had a better biomass yield when compared to other accessions recording the highest values in SDW (1.62 g), RDW (0.55 g), LFW (0.75 g), SFW (10.31 g) and RL (18.53 ± 0.66). Conclusively, waterlogging stress negatively impacted V. subterranean accessions, but Tvsu-5 had a better waterlogging stress tolerance than other accessions especially TvSu-3, which was generally poor.

Abstract All growing plant roots have the ability to produce root exudates to which soil microbes are attracted. The objective of this study was to utilise the Biolog EcoPlate™ system to indicate the impact of soil type on soil microbial communities in the rhizosphere following treatment with pot leachates that contain various plant root exudates. A greenhouse experiment was conducted during 2021 and repeated in 2022 from May until July (southern hemisphere) in this winter rainfall area with Mediterranean climatic conditions. This ensured that natural daylight hours in the greenhouse coincided with those experienced in the field by winter growing crops, from seeding until maturity (May to October). Pot leachate that contained various plant root exudates from six donor plant species (wheat, barley, two lupine cultivars, ryegrass pasture type and weedy ryegrass hybrid type) was utilised as treatment of respective recipient pots, in which wheat ( Triticum aestivum v. SST 027) was grown as a test plant. Recipient plants were grown in two sets of pots each with two different soil types. Soil samples from recipient pots were used to inoculate the Biolog EcoPlate™ system and the carbon utilisation patterns obtained in this process were compared to the soil microbial populations present in the soil samples collected prior to treatments. Pot leachate treatment effects on the two soil types differed. Similarly, the treatments had differential effects on the measured soil microbial populations of the recipient wheat plants. Results indicate that the pattern of substrate utilisation by the Biolog EcoPlate™ methodology indicates changes in the number of colony forming units in the soil. In this regard, it was clear that ryegrass pasture variety and weedy ryegrass hybrid type caused similar effects on the soil bacteria communities in the rhizosphere. It is concluded that the primary impact of soil type is distinct microbial communities as an important factor regulating plant and plant-microbe synergy. Secondly, due to the strong selective forces root exudates have on the soil microbiome, conspicuous microbial communities in the rhizosphere of each plant species will continue to develop over time.

Abstract The goal of this study is to investigate the extreme rainfall indices and their consequences on the local farming crop calendar among agro-climatic zones (ACZs) of the Abiya watershed. Climate Hazards Group Infrared Precipitation (CHIRPS) provided long-term (1981–2019) rainfall data for 50 sample grid points with a spatial resolution of 5 × 5 km. Different crops are affected differently by the same extreme rainfall event depending on when it occurred and how extreme it was; this means crop calendars for a specific time may be properly governed by extreme climatic conditions. There hasn’t been a sufficient published study on extreme rainfall indices and their consequences on crop calendars by considering various ACZ in Ethiopia. The study defined local crop calendar timing and the consequences of the extreme rainfall indices through focus group discussions. INSTAT+ software was applied to calculate eight extreme rainfall indices. The indices were evaluated using Mann-Kendall’s (MK) and Sen’s slope techniques to identify trends and determine variations in the magnitude, respectively. Increase and decrease indications for various crop calendars were found in each ACZ. Further, going-up signals were seen in the highlands, midlands, and all ACZs for land preparation time (LPT), sowing and management time (SaMT), and harvesting and threshing time (HaTP), respectively. While HaTT was found to be uniform in all ACZs, some of the declining trends in the indices were detected for LPT and SaMT in the cold-highland and highland zones. The perceived trend in indices across the whole ACZ will have direct and unintended consequences for watershed crop production. The findings imply that to reduce the unfavourable consequences of these extreme rainfall indices occurrences in the agricultural sector, it is necessary to develop suitable crop varieties and drought-tolerant crops, as well as an effective early warning system.

Abstract Measurements of live weight in goats and sheep are an important source of information for a range of scientific fields and applications in animal husbandry activities. The study was conducted to investigate the relationship between body weight and body measurements and to predict live body weight from body measurements in indigenous Matabele goats and indigenous Sabi sheep at Matopos Research Station in Zimbabwe. For this purpose, data on body weight (BWT) and linear body measurements (LBM) such as heart girth (HG), body length (BL), wither height (WTH) and rump height (RH) were collected from randomly selected females of each species of the age of 4 years. The corresponding means, standard deviations (SD), and coefficients of variation (CV) were determined for body weight and linear body measurements. Bivariate correlations between bodyweight and linear body measures characteristics were also determined. Simple and multiple regression were used to develop a model to predict BWT using linear body measures. Indigenous Matabele goat females’ CV ranged from 15.77% to 22.68%, while indigenous Sabi sheep females’ CV ranged from 19.16% to 19.37%. The CV was calculated by dividing the mean by the standard deviation. At 4 years of age, the mean BWT of the indigenous Sabi sheep and female Matabele goat were 35.96 ± 0.83 kg and 27.90 ± 0.66 kg, respectively. In indigenous Matabele goat females, the average linear body measures were HW (74.20 ± 0.53 cm), WTH (48.55 ± 0.53 cm), BL (47.53 ± 0.61 cm), and RH (57.50 ± 0.88 cm). The mean values for native Sabi sheep were 63.33 ± 0.70 cm, WTH (52.00 ± 0.80 cm), BL (51.26 ± 0.78 cm), and HW (85.56 ± 1.04 cm). The results showed a strong and positive correlation between BWT and linear body measures in female indigenous Matabele goats. The phenotypic correlation values were HG ( r = 0.79), BL (r = 0.70), WTH ( r = 0.68), and RH ( r = 0.56), in decreasing order. In indigenous Sabi sheep the phenotypic correlation for BWT and linear body measurement was high and positive for HG ( r = 0.73) with positive and moderate to low with WTH ( r = 0.41), BL ( r = 0.32) and RH ( r = 0.36). Again, the results also indicated that HG had a high and positive phenotypic correlation with BL ( r = 0.53) while modest correlation was observed with HG and WTH ( r = 0.41) and HG and RH (0.32). The optimal regression models for easily measuring body weight using HHG are BWT = −46.711 + 1.006HG ( R 2 = 60%) and BWT = −15.209 + 0.586HG ( R 2 = 53%) for indigenous Matabele goats and indigenous Sabi sheep, respectively. It is recommended that smallholder farmers use HG measurements to estimate body weight in both indigenous Sabi sheep and indigenous Matabele goat females at the age of 4 years.

Abstract For this purpose, a moisture sensor device was designed and constructed in February and March 2019 to determine the appropriate time to stop irrigation in furrow irrigation. Testing the device in the laboratory and its application in the Farm of the Campus of Agriculture and Natural Resources, University of Tehran (Mohammad Shahr), Iran, from April to July 2019. The purpose of this study was to evaluate the performance of a smart sensor of soil moisture to determine the optimum depth of installation and recording of soil moisture at 10, 30, and 50 cm depths and different length ratios in furrow irrigation. Initially, calibration of the device was carried out on field soil, and based on the obtained validation, the device was transferred to the field. To achieve the goals of optimum depth of installation and optimum length, 36-meter furrows with a distance of 0.75 m were created in the field. Sensitive lengths in furrows with 0.5 L, 0.75 L, and 0.85 L ratios were selected as the starting points. The results showed that in the calibration and validation phases, the R 2 values were 0.93 and 0.95, respectively, and in the calibration and validation stages, the value of nRMSE was 80 and 13.81%, indicating good model training in the calibration stage. Also, the average RE parameter in estimating soil moisture was 2.74%, indicating the high accuracy of the device in estimating soil moisture. The results also showed that if the device was installed at a depth of 30 cm from the soil surface of the furrow and at 75% from the beginning of the field, the depth and runoff losses would be minimal and irrigation adequacy would be best compared to other depths and lengths. It is expected that with optimal water consumption and timely interruption of irrigation, deep losses and runoff will be avoided, and with low water consumption, the productivity of crops will increase.

Abstract The lack of affordable and lightweight mechanized maize planters suitable for small-scale farms in Botswana, where donkeys serve as the primary source of draught power, poses a significant challenge. This study addresses this issue by designing a cost-effective model of a two-row donkey-drawn maize planter. A comprehensive analysis of various existing planter technologies was conducted, and their principles were carefully adapted to develop an optimal two-row planter suitable for donkey traction. The selection of appropriate materials for each component, accompanied using solid-works software for detailed drawings and fabrication, resulted in a user-friendly planter design. The mass estimation of the assembled planter was calculated to be 48.93 Kg, making it light enough to be drawn by three donkeys. Notably, the estimated cost of the unit planter assembly is approximately 200 USD. Despite these advancements, it is important to acknowledge certain limitations. This study introduces an innovative solution to address the need for affordable, lightweight, and donkey-drawn maize planters in Sub-Saharan Africa. By leveraging existing technologies and employing appropriate materials, the proposed design offers a practical and cost-effective option for small-scale farmers. Further research is necessary to assess the planter’s performance under varying soil conditions, evaluate its long-term durability, and optimize its planting efficiency. Additionally, considerations should be given to implementing additional features such as seed depth control mechanisms and adjustable row spacing to enhance the versatility of the planter.

Abstract The application of biofertilizers (beneficial microbes) represents a transformative paradigm in modern agriculture. This paper delves into the multifaceted benefits of biofertilizers in the context of crop production. It examines how biofertilizers work their magic in enhancing crop growth, yield, and quality, underpinning their pivotal role in sustainable agriculture. Beyond these primary advantages, the paper explores the ripple effects of biofertilizer utilization, where it emerges as a linchpin in the global quest for food security. Biofertilizers not only reduce the environmental footprint of agriculture but also contribute to improving human health. This paper synthesizes current knowledge, revealing that biofertilizers have emerged as a potent tool in addressing the challenges of modern agriculture, from crop enhancement to environmental conservation and public health. It serves as a call to action for their wider adoption, heralding the era of biofertilizers as a cornerstone of sustainable agricultural practices.

Abstract Implementing practices such as organic agriculture, sustainable agriculture, or ecological agriculture can greatly reduce and eliminate the harmful effects of synthetic fertilizers on both human health and the environment. In efforts to promote a more environmentally friendly approach, this study was conducted at the Department of Horticulture and Agronomy, Midlands State University in Zimbabwe. The focus was on the use of Trichoderma bio-fertilizer at various levels to determine its impact on the growth of horned melon ( Cucumis metuliferus ) in a greenhouse setting. The experiment followed a Complete Randomized Design (CRD) and included four different Trichoderma-based biofertilizer treatments, as well as a control treatment [0 g/pot (control), 0.1 g/pot, 0.2 g/pot, 0.3 g/pot, and 0.4 g/pot], all replicated four times. The research findings indicate that the biofertilizer utilized had a significant impact ( p ≤ 0.05) on vine length, number of leaves, and branches for growth characteristics. However, the biofertilizer did not have a significant effect ( p ≥ 0.05) on stem girth, chlorophyll content, or branching pattern. This study reveals that the horned melon plants treated with the Trichoderma-based biofertilizer exhibited noticeable changes in their vegetative growth, flowering patterns, and fruiting features at different application levels. Further investigation is required to fully understand the potential benefits of using Trichoderma-based biofertilizer in horned melon cultivation.

Abstract