In the modern global economy, members&#x2019; active participation is critical to the successful implementation of cooperative groups&#x2019; planned activities. The objectives of this study were to investigate the participation of cooperative members in MPPCs activities and to determine the factors that influence the participation of members in multipurpose cooperatives in the Kindo Koysha district. The study location was chosen for this purpose because no prior in-depth research had been conducted. The multipurpose primary cooperatives were chosen from among the four in the study area based on agro-ecological classifications such as high land, medium land, and low land. The target population of 752 people (M&#x2009;&#x3d;&#x2009;594 and F&#x2009;&#x3d;&#x2009;158) was chosen using a simple random sample technique with a probability proportional to the size sampling technique (PPS), whereas 106 sample respondents (M&#x2009;&#x3d;&#x2009;84 and F&#x2009;&#x3d;&#x2009;22) were chosen using (Yamane) implified formula. Primary data were collected using the interview schedule supplied to sample respondents, focus group discussion checklists, and key informant interviews. Secondary data were also collected from several public and unpublished sources. The level of participation in multipurpose cooperatives was measured by computing the participation index score value. The participation of members has been classified as low, medium, or high based on the mean value, which is 40 (37.5&#x0025;), 50 (47.2&#x0025;), and 16 (15.1&#x0025;), respectively. The ordered logit model was utilized for data analysis, and percentages, mean differences, one-way ANOVA, Spearman correlation, and the chi-square test were performed. According to the findings, education level, family size, total annual income, shareholding amount, access to saving and credit, distance from the cooperative service center, access to and utilization of agricultural inputs, services rendered by MPPCs, perceived challenges of MPPCs that discourage membership, and perceived members satisfaction with cooperative services are the determinant factors that affect the level of membership participation. Continuous education and training, encouraging the issue of family planning, diversification of income-generating schemes, encouraging existing members to buy additional shares, creating the best opportunity for saving and credit, need-based supply of agricultural inputs, resolving the internal and external constraints of multipurpose cooperatives, and strengthening the MPPCs through research-based technical support and follow-up are some of the suggested implications.

Hiskeal Hando

Marisennayya Senapathy

Elias Bojago

Determinants of Member Participation in Activities of Multipurpose Primary Cooperatives: The Case of Kindo Koysha District, Southern Ethiopia

No research has been done to assess the genetic diversity of Okra (Abelmoschus esculentus) genotypes in Ethiopia based on the combination of agromorphology and biochemical traits of the crop. Such an assessment would assist in the development of high fruit yield and nutritionally good cultivars. Therefore, 36 okra genotypes were evaluated for 29 agromorphological and biochemical traits at the Melkassa Agricultural Research Center (Ethiopia) during the 2018 main rainy season, using a 6&#x2009;&#xd7;&#x2009;6 simple lattice design. Analysis of variance showed significant differences among genotypes for all the studied traits, except number of flower epicalyxes and fruit diameter. Genotypic coefficients of variation and phenotypic coefficient of variation were high for number of branches, internode length, fresh fruit weight, number of mature pods, fruit yield per plant, fruit yield per hectare, seed yield per plant, seed yield per hectare, and seed protein content. Heritability values ranged between 33.63 and 99.81&#x0025;, while the genetic advance as percentage of mean ranged between 4.29 and 95.45&#x0025;. High broad sense heritability was coupled with high GAM for plant height, branch, internod length, fruit length, panicle length, fresh fruit weight, number of fruits per plant, number of mature pods, seed yield per plant, seed yield per hectare, and fibre and protein content. In conclusion, this study showed the presence of genetic variation among genotypes for fruit yield, seed yield, and nutritional content, indicating the potential success of developing okra varieties for high fruit yielding and good nutritional content.

Jemal Mohammed

Wassu Mohammed

Eleni Shiferaw

Performance and Genetic Variability of Okra (Abelmoschus esculentus (L.) Moench) Genotypes in Ethiopia for Agromorphology and Biochemical Traits

There is a distinct seasonality in the availability of feeds in the highlands of Ethiopia, reaching a peak and low levels towards the end of the rainy and dry season, respectively. Consequently, this trial was conducted to assess the yield performance and nutritive value of nine perennial grasses accessions from seven grass species under supplementary irrigation to produce feed year-round. The evaluated grasses species were two Urochloa (U. decumbens cv. ILRI-10871 and ILRI-13205), two Setaria (S. sphacelata cv. ILRI-143 and ILRI-6543), one Phalaris (Phalaris aquatica cv. Sirrosa), coloured Guinea (Panicum coloratum cv. Coloratum), Desho (Pennisetum glaucifolium cv. Kindu kosha), Napier (Pennisetum purpureum cv, ILRI-16791), and Rhodes (Chloris gayana cv. Massaba) variety. The experiment was carried out in a randomized complete block design. The chemical compositions of the grasses were scanned by, the near infrared spectroscopy (NIRS). Results indicated that the plant height, dry matter, and crude protein yield were significantly affected by year, species (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="19.289pt" style="vertical-align:-0.6370001pt" id="M1" height="9.2729pt" version="1.1" viewBox="-0.0498162 -8.6359 19.289 9.2729"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-81" d="M600 480C600 590 528 650 384 650H143L137 622C222 614 225 607 210 531L130 127C113 41 106 36 23 28L17 0H294L300 28C204 36 195 42 212 127L243 284L314 263C327 263 339 263 352 264C465 271 600 337 600 480ZM508 481C508 351 402 304 329 304C289 304 265 311 250 317L295 559C302 594 310 606 323 611C335 616 350 619 367 619C455 619 508 573 508 481Z"/></g><g transform="matrix(.013,0,0,-0.013,11.658,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="28.182pt" style="vertical-align:-0.6370001pt" height="9.2729pt" version="1.1" viewBox="22.8711838 -8.6359 28.182 9.2729"><g transform="matrix(.013,0,0,-0.013,22.921,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,29.161,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,32.125,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.365,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,44.605,0)"><path id="g113-50" d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"/></g></svg>), and their interaction (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="19.289pt" style="vertical-align:-0.6370001pt" id="M2" height="9.2729pt" version="1.1" viewBox="-0.0498162 -8.6359 19.289 9.2729"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-81"/></g><g transform="matrix(.013,0,0,-0.013,11.658,0)"><use xlink:href="#g117-91"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.918pt" style="vertical-align:-0.6370001pt" height="9.2729pt" version="1.1" viewBox="22.8711838 -8.6359 21.918 9.2729"><g transform="matrix(.013,0,0,-0.013,22.921,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,29.161,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,32.125,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.365,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g></svg>). Moreover, species were significantly influenced in vitro dry matter digestible yield, relative feed value, and nutrient content (DM, CP, NDF, ADF, ADL, and IVDMD). Napier grass had superior in dry matter, crude protein, and in vitro dry matter digestible yield than the other perennial grasses species tested together. Thus, among the tested grasses species, Napier grass showed outstanding potential as a forage plant followed by Phalaris and Desho grass under supplementary irrigation in the central highland of Ethiopia.

Mulisa Faji

Gezahagn Kebede

Fekede Feyissa

Kedir Mohammed

Gezahegn Mengistu

Yield, Yield Components, and Nutritive Value of Perennial Forage Grass Grown under Supplementary Irrigation

Water shortage is a real problem in many parts of the world and finding alternative solutions such as the application of saline water in cropping systems is highly appreciated. Research on drip irrigation and soil salinity is still inadequate, and their effect on crop yield and water use efficiency (WUE) is a huge challenge for small farmers. The present study was conducted in Malir, a semiarid region in the Sindh province of Pakistan. The purpose was to estimate the effects of two different qualities of irrigation water including fresh quality water (IT1 0.56 dS m−1) and saline groundwater (IT2 2.89 dS m−1) on WUE using drip irrigation technology in 2018–19. The experimental design was complete randomized block design (RCBD) with two treatments of irrigation: (1) freshwater (IT1) with 0.56 dS m−1 electrical conductivity and (2) saline water (IT2) with 2.89 dS m−1 electrical conductivity. The average biomass and crop yield under IT1 were 10.2 t.ha−1 and 7.4 t.ha−1, respectively, and were found higher than those under IT2 (7.3 t−1 and 4.2 t.ha−1, respectively). Hence, both the treatments remained equally effective in season 1 as compared to season 2 (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M1" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-113" d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path id="g117-93" d="M531 71V127L115 310L531 494V550L57 335V285L531 71ZM531 -40V10H57V-40H531Z"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.921pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 21.921 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g></svg>). The WUE of bitter melon under IT1 was 1.60 and 1.56 kg.m−3 in seasons 1 and 2, respectively, and was higher than those under IT2 which were observed 1.21 and 1.07 kg.m−3 in seasons 1 and 2, respectively.

Kamran Baksh Soomro

M. M. Shaikh

Sanyogita Andriyas

Muhammad Rizwan Shahid

Saline Water Impact on Water Use Efficiency of Bitter Melon (Momordica charantia L) Using Drip Irrigation

Waterlogging is a common form of abiotic stress that severely impedes global soybean production. Targeting this issue, an experiment was carried out at Sher-e-Bangla Agricultural University during August&#x2013;November 2019 to screen out the waterlogging tolerance and yield performances of selected soybean genotypes. The experiment was laid out in a completely randomized design (CRD) with three replications consisting of 2 water levels (control and waterlogging) and 12 genotypes (Sohag, BARI Soybean-5, BINAsoybean-1, BINAsoybean-2, BINAsoybean-3, BINAsoybean-5, BINAsoybean-6, SGB-1, SGB-3, SGB-4, SGB-5, and GC-840). On the 15th day after sowing, plants were exposed to waterlogging for 12 days. Waterlogging remarkably declined the growth and yield of all the soybean genotypes compared to control. Reduced plant height, relative water content, above-ground fresh and dry weight, SPAD value, leaf area, number of leaves, branches, pods, seeds pod&#x2212;1, 100-seed weight, and seed yield plant&#x2212;1 were observed under waterlogging stress. Conversely, mortality rate and electrolyte leakage were increased under the same condition. The waterlogged plants showed delayed flowering and maturity compared with the control plants. However, among the 12 genotypes, Sohag, BARI Soybean-5, GC-840, BINAsoybean-1, and BINAsoybean-2 showed better waterlogging tolerance. These genotypes showed a greater number of adventitious roots in the base of their stem, which probably helped plants to thrive under waterlogging conditions.

Khadeja Sultana Sathi

Abdul Awal Chowdhury Masud

Maliha Rahman Falguni

Naznin Ahmed

Khussboo Rahman

Mirza Hasanuzzaman

Screening of Soybean Genotypes for Waterlogging Stress Tolerance and Understanding the Physiological Mechanisms

About this journal

Advances in Agriculture publishes research on the cultivation of soil and crops, and the rearing of livestock. Its focus is on new methods and technologies for improving agricultural processes, increasing yield, conservation and breeding.

Journal profile

Meet the editorial board

Advances in Agriculture maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor spotlight

Find out more

This journal's articles appear in a wide range of abstracting and indexing databases, and are covered by numerous other services that aid discovery and access. Find out more about where and how the content of this journal is available.

Abstracting and Indexing

Author guidelines

Editorial board

Databases and indexing

Advances in Agriculture - Table of contents 2022

title

Advances in Agriculture publishes research on the cultivation of soil and crops, and the rearing of livestock. Its focus is on new methods and technologies for improving agricultural processes, increasing yield, conservation and breeding.

Advances in Agriculture